8th Solar & 17th Wind Integration Workshop // E-Mobility Integration Symposium 2018 (SIW / WIW / E-Mobility 2018 // Stockholm, Sweden)
Stockholm / Sweden, 15 to 19 October 2018

E-Mobility Integration Symposium 2018



Solar powered EV smart charging station with Tesla Powerwall
Submission-ID 003
Novy Francis
DNV GL, Netherlands
In this paper a power management algorithm is proposed along with experimental results which combines electricity prices, PV generation profile along with the charging demand required for EVs. A smart way to effectively reduce the cost of charging by actively controlling the power flow in the charging infrastructure Modelling load demand for a fleet of EVs in an urban workspace environment. Providing a complete PV system design to realize an EV charging infrastructure with an economic evaluation to devise charging facility. Charting out the process to realize the experimental set-up and test the Tesla Powerwall set-up to reduce the cost of EV charging. A 19.5 kW PV system is designed. A mathematical model is built to determine the energy demand required for charging a fleet of 10 EVs. This tool is of vital importance as it can be extended to effectively estimate the charging energy demand for other cases and can be efficiently used in scenarios where the presence of various variables makes the estimation of required charging energy demand arduous. A normal probability distribution function is used to calculate the cumulative driving pattern for all EV. The average daily charging demand is 73 kWh and an annual demand of 20 MWh. . The PV system is designed with a tilt of 28 ˚ facing south for yearly optimum PV module position for a grid tied system with battery backup. The available energy amounts to 1.2 MWh/m2. The chosen 19.5kWp PV system is arranged in a layout of 25 modules in series with 3 parallel strings constituting a 75 module system. The total investment costs for the E-Hub amounts to € 50398. Linear programming algorithm is used to realize the smart charging strategy. The implementation of smart charging algorithms in summer makes the E-Hub grid independent even without the Powerwall. In winter with peak shaving and smart charging the peak grid import power is reduced by 88% which drastically helps in reducing demand charges levied on the charging infrastructure. It is also calculated that a fully charged battery at 09:00 on both summer and winter days help in maximizing the profit by combining smart charging algorithms with peak shaving. An experimental test-set up was hence built to implement the designed smart charging algorithm. It was essential to explore the control of both the inverter and powerwall set-up to dynamically charge and discharge to deliver charge to the EVs. The set-up was controlled through a cloud based monitoring portal to which pre-determined models were uploaded. It was noticed that when the electricity prices are high the available PV power is fed to the grid to gain revenue and the peak is shifted to off-peak hours where EVs are charged with maximum grid import limited to 10kW to prevent excess demand charges. It is interesting to observe that the Tesla Powerwall is charged and discharged with respect to grid prices for providing the most cost effective charging case.


Mitigation of the impacts of EV inclusion into electricity markets through Demand Aggregators
Submission-ID 007
David Toquica
Student University of Los Andes, Colombia
The uncoordinated charge of a large fleet of electric vehicles (EV) will create difficulties in the management and technical operation of power systems, because it'll increase the peak of the daily load profile. In order to avoid that effect, this paper presents a coordinate charging model creating a new agent that aggregate the energy demand of EVs and also exploit business opportunities of the batteries in electricity markets. In this context, aggregators will achieve two main goals: first, allow network operators to improve system performance by given control over demand side variables; second, aggregators will remove barriers to having more EVs on the roads. Nevertheless, is important to say that aggregators won't come up as a market solution to the problems of uncoordinated charge, because providing services to the grid will cause the degradation of expensive batteries.


The mobile transition - it is more then eMobility
Submission-ID 014
Daniel Lautensack
ABB Automation Products GmbH, Germany
Most of all the consulting papers are calculating their figure based on a one to one transition from the combustion engine to the electric drive system. But this will not solve our mobility and transport challenges, it needs more.

Some question we will cover in our presentation:

- What would be the ideal KPI to measure success? Heads per vehicle?

- How we gain more space in our cities?

- What is the economic impact for countries without automotive industry and with automotive industry?

We will try to give answers and explain the complexity moving from the technical and economical perspective deeper in the mobility and e-mobility market.



Impact of increasing E-mobility on a distribution grid at the medium voltage level
Submission-ID 023
Julia Vopava, Thomas Kienberger
Montanuniversität Leoben, Austria
To achieve the aims of decarbonisation, it is necessary to change to alternative drives in the field of traffic, for example E-mobility. In case of this, it is important to provide the increasing energy demand for charging processes from renewable energies. In order to establish electric mobility, it`s needed to set up an area-covering charging infrastructure. This integration of an increasing number of electric vehicles in existing grid infrastructures represent a new challenge. To identify optimum installation sites for charging stations, the overlap of the existing demand of households and industry with future charging processes and the interaction with renewable energy plants with its fluctuating energy generation need to be taken into account.

In order to study the interactions between electric mobility and renewable energy plants as well as the optimum installation areas, a model based on a cellular approach for an urban distribution grid at medium voltage level (approximately 30.000 inhabitants) is developed during the FFG research project “Move2Grid”. This model simplifies the complex grid structure, reduces the calculation time and enables a temporally resolved load flow calculation with annual load profiles. Based on, this model the impact of an increasing number of charging stations and the interaction with photovoltaic potentials are studied for different E-mobility and photovoltaic potentials penetration rates. The required charging profiles are modelled by using traffic analyses and probabilistic approaches. The determination of temporally resolved photovoltaic potentials are based on data from the “Styrian Solar-Roof Cadaster” [1] and weather data from the Austrian Zentralanstalt für Meteorologie und Geodynamik (ZAMG) [2].

The aim of the proposed paper is to show the impact and interaction of E-mobility and photovoltaic potentials for different penetration rates of both. Besides the determination of the self-sufficiency level, load flow calculations with annual load profiles are performed and are benchmarked in term of equipment overloads and deviations of the voltage range. This is done by using a newly developed evaluation tool. With this tool a quick determination of areas which are susceptible for equipment overloads and deviations of the voltage range, as well as the exact time of them and their duration for further analyses becomes possible. In order to avoid equipment overloads and deviations of the voltage range and the associated necessary grid expansion, demand side measures and the use of electrical storages are implemented in the power grid model, followed by load flow calculations and analyses.

  1. Amt der Steiermärkischen Landesregierung, „Solardachkataster Steiermark“, http://www.gis.steiermark.at/cms/beitrag/11864478/73081691/ , 26.01.2016
  2. ZAMG, Einstrahlungsmessdaten und Temperaturmesswerte des Jahres 2014 für Kapfenberg


Electric Vehicle CPMS and Secondary Substation Management
Submission-ID 024
Luis Marques, KONSTANTINOS KOTSALOS, Ivan Sousa
Efacec, Portugal
The increasing adoption of Electric Vehicles (EVs) is leading to a fast transition on electrical distribution networks, where charging stations are being deployed on a large scale to accommodate the EV users’ needs. Considering distribution networks were typically not prepared to accommodate a large deployment of EV charging stations, as they tend to require large amounts of energy from the grid in short periods of time – leading among others to lines congestions and voltage issues- and with a volatile demand profile resulting from the variability of consumption, there is the need of finding new solutions to cope with these challenges in order to guarantee the efficient and safe operation of the networks, while maximizing the availability of power to satisfy consumers’ needs. This paper presents an innovative Electric Vehicle Charging Point Management System (EVCPMS) that more than a solution capable of effectively tackling these technical operation problems through the management of charging infrastructures is also endowed with customer-oriented services, enabling user’s management, such as automatic billing different energy profiles and administration functionalities.


Electric Vehicle Destination Charging Demand Characterizations at Popular Amenities
Submission-ID 025
James Dixon, Ian Elders, Keith Bell
Department of Electronic and Electrical Engineering University of Strathclyde Glasgow United Kingdom, United Kingdom
The UK Government has pledged to outlaw the sale of purely petrol or diesel-powered cars by 2040. Given the current market dominance of battery Electric Vehicles (EVs) over other alternative forms of private vehicle propulsion such as hydrogen fuel cells, it is reasonable to expect that within the next two to three decades a significant proportion of Britain’s 31 million cars could be replaced with plug-in EVs; likely a combination of pure battery EVs (BEVs) and plug-in hybrid EVs (PHEVs).

While it is often assumed in the academic literature that EVs will be charged slowly overnight at home, a significant proportion of EV charging could exist as ‘destination' charging while parked during their users’ visits to workplaces or amenities such as shopping centres, supermarkets, gyms, cinemas and motorway service stations - where cars are left for durations ranging from ten minutes to three hours. A move from a solely domestic charging-based EV uptake to one focused on the widespread availability of public charging could serve to enhance the convenience of EV usership, enable EV access to those without off-street parking (which applies to 43% of households in the UK) and has the potential to reduce system cost: according to findings from the 'My Electric Avenue' project, 32% of local electricity networks across GB will require intervention when 40% - 70% of customers have at-home EV charging. By instead encouraging users to charge away from home at their place of work or other places where they leave their car, the installation of charging infrastructure can be directed towards areas of greater spare capacity or with more potential for ‘smarter’ network operation which could allow a higher penetration of EV charging.

This paper presents a Monte Carlo (MC)-based method for the characterization of likely demand profiles of EV destination charging at these locations based on smartphone users’ anonymised positional data captured in the Google Maps Popular Times feature. Unlike the majority of academic works on the subject, which tend to rely on users’ responses to surveys, these data represent individuals’ actual movements rather than how they might recall or divulge them. Through a smart charging approach proposed in this paper, likely electrical demand profiles for EV destination charging at different amenities are presented.

The method is demonstrated by way of two case studies. Firstly, it is applied to a large GB shopping centre to show how the approach can be used to derive suitable specifications for large charging infrastructure to maximise revenue or EV service provision. Secondly, it is applied to a GB supermarket in a residential area to show how the approach can be used to examine network impact for a distribution-connected destination charging facility.



CleanMobilEnergy- A Smart Energy Management System Integrating Renewable Energy and Electric Vehicles
Submission-ID 028
Peter Swart
City of Arnhem, Netherlands
Electric vehicles are mostly powered by fossil fuel generated electricity. At the same time, renewable energy is inefficiently utilised because production and demand are not synchronised across the city. The project CleanMobilEnergy will integrate various renewable energy sources, storage devices, electric vehicles and optimisation of energy consumption through one unique smart energy management system. The development of this intelligent Energy Management System (iEMS) will increase the economic value of renewable energy and significantly reduce CO2 emissions. The iEMS will assure the smart integration through interoperability based on open standards for data flows and analysis tools. CleanMobilEnergy will make it possible for renewable energy sources to be used locally, so electric vehicles can be charged with 100 % renewable energy offered at an optimum price. The iEMS monitors and optimises the system 24hours a day, 7 days a week. One generic transnational iEMS will be adapted to the 4 specific city pilots in Arnhem, London, Schwäbisch Gmünd and Nottingham. These pilots range from small towns to large cities. The 4 city pilots cover different types of renewable energy, storage and electric vehicles as well as different contexts and diverse city environments. The 4 CME City Pilots are: 1) Arnhem: medium size city, large renewable energy production, large storage in industrial area, power used for moored ships and EV's in charging plaza; 2) Nottingham: medium size city, large renewable energy production, medium size storage, electric vehicles and bi-directional chargers in a controlled area (depot); 3) London: large city, large renewable energy production at multiple locations, large storage, electric vehicles and bi-directional chargers in controlled areas with separate grid (depot); 4) Schwäbisch Gmünd: small city, small renewable energy production, storage facilities and electric bikes in residential area. The city pilots will utilise different state-of-the art storage media in various environments, which are representative of North West Europe and are easily replicated in other cities across Europe. Specifically in London and Nottingham, for example, electric vehicles themselves will be used to power the buildings and depot by using innovative bi-directional chargers controlled by the integrated energy management system iEMS. In Arnhem, on the other hand, renewable energy (a 10 MW solar field) will be supplied to ships in the harbour adjacent to its industrial site and to a charging plaza for EV's. Pilots were chosen to represent a wide range of city sizes and environments, which are essential to developing a widely applicable system for future implementation across Europe.

The project has started in january 2018 en will run until march 2021, will yield at project end a reduction in CO2 of 2400 ton/year and 12,4 MW of extra renewable energy production.



REQUIRED TECHNOLOGIES FOR GRID INTEGRATION OF CHARGING INFRASTRUCTURE
Submission-ID 030
Juliane Selle 1, Johannes Brombach 2
1 ENERCON GmbH, Germany
2 Innovation for ENERCON GmbH, Germany
This paper presents expected grid integration technologies for electric vehicle (EV) charging infrastructure which will be required to ensure the future stability of the power system. Technologies well known from modern inverter-based renewable energy systems are suggested to be implemented also in electric vehicle supply equipment (EVSE).

The first chapter describes the challenges for the power system and for grid operators when electrifying the transportation sector to meet international climate goals. In the second chapter, a standard load profile for the charging process of EVs based on assumptions for the future electricity demand of the transportation sector and a standard business load profile is introduced. The third chapter reflects today’s state-of-the-art grid integration of EVSE, whereas Chapter IV describes expected future levels of the grid integration of EVSE. Chapter V analyses the behavior of EVSE and EV in case of grid faults. A summary and outlook is given in Chapter VI.



Aggregated Approach to use the Flexibility of PEVs for Grid Support in local Energy Communities
Submission-ID 033
Evgeny Schnittmann 1, Jan Meese 1, Robert Schmidt 1, Schaugar Azad 1, Markus Zdrallek 1, Thomas Armoneit 2
1 University of Wuppertal, Germany
2 Stadtwerke Iserlohn, Germany
Current changes in the energy sector towards a more decentralized and renewable supply system are especially noticeable in the form of voltage range and utilization-limit violations in the distribution grid. Conventional low-voltage networks are not designed for a rapid increase of uncontrolled energy consumption by power-intensive consumers such as plug-in electric vehicles (PEVs). In this context the rising share of electrical vehicles could both intensify grid issues but also, if equipped with automation technology, provide the opportunity to counteract network congestions without being dependent on the comparatively expensive grid expansion.

This paper presents an aggregated approach to control a compound of charging stations with respect to network congestions. The main focus of the paper will be on the automated temporal shift of the charging power of pooled charging stations in order to avoid limitation violations of the corresponding network section.



DEVELOPMENT OF ELECTROMABILITY IN THE TRANSPORT SECTOR OF BELARUS - STATUS AND PERSPECTIVES
Submission-ID 034
Natallia Yankevich
National Academy of Sciences of Belarus, Head of the Department, Belarus

From the ecological point of view, the benefits of electric transport using are obvious for large cities, but in general in the country they can be insignificant or absent at all, so the total ecological effect will depend not only on the technical characteristics of electric vehicles, but also of the structure of electric power generation by types of generation (thermal, nuclear, renewable energy sources) and used fuels. At the moment, it is recognized in Belarus that electric vehicles are the optimal type of passenger transport for a city usage that meets all the requirements of environmental and energy security. However, the number of persons wanting to buy them is very little, because today electric vehicles in Belarus are very expensive cars. An electric vehicle in Belarus even without additional payments is 1.5 times more expensive than a car with ICE.

The program for the development of charging infrastructure and electric vehicles in the Republic of Belarus contains two scenarios for electricity consumption by electric vehicles and electric buses in the Republic of Belarus until 2025 - optimistic and pessimistic.

It is assumed that the number of electric vehicles in Belarus by 2025 will be:

- according to optimistic scenario - 32.7 thousand units, incl. 30.82 thousand units of passenger electric cars and 1.88 thousand units of electric buses;

- according to pessimistic scenario - 9.96 thousand units, incl. 9.37 thousand units of passenger electric vehicles and 0.59 thousand units of electric buses.

In this connection the need to develop strategic solutions in the following areas has become more acute for the Belarusian transport sector:



Renewable Energy schemes and benefits for Indian Farmers 2018
Submission-ID 039
MD IRFAN AHMED, Nikita Jain, Pallavi Soni
CAREER POINT UNIVERSITY, KOTA, RAJASTHAN INDIA, India
Renewable energy resources are the fastest growing energy resources in the world. Renewable energy resources exist over wide geographical areas, in contrast to other energy sources, which are concentrated in a limited number of countries. National RE markets are proposed to carry on growing strongly in the coming decade and beyond. In a move that will help reduce dependence on diesel pumps to irrigate crops, the National Democratic Alliance (NDA) government plans to offer incentives to farmers to shift to solar power pumps. The extra electricity is produced by the farmers and that will be bought by state electricity distribution companies (discoms) and will help boost India’s emerging green economy. The government working on a plan targeted at farmers to generate 20 gigawatts (GW) of solar power. It contains setting up small solar projects of 1-2 megawatt (MW) size on fallow land and solarizing water pumps. “Many farmers are installing solar water pumps to irrigate their fields. Government of India will take necessary measures and encourage state governments to put in place a mechanism that their surplus solar power is purchased by the distribution companies or licensees at reasonably remunerative rates,”. The profit will be given on domestic solar equipment makers, the budget eliminated the 5% customs duty on solar tempered glass used for manufacturing cells, panels and modules.


Optimized charging of electrical vehicles based on the Day-Ahead Auction and continuous Intraday market
Submission-ID 047
Jan Meese 1, Evgeny Schnittmann 1, Robert Schmidt 1, Markus Zdrallek 1, Thomas Armoneit 2
1 University of Wuppertal, Germany
2 Stadtwerke Iserlohn GmbH, Germany
The raising share of electrical vehicles does not only lead to new challenges for distribution grids but also opens up new possibilities for a smart trading at short term markets for electricity. Within this paper a car park with several fast charging stations with 22 kW each is simulated to observe the impacts on the distribution grid and the costs for the electricity procurement.

Based on simulated driving profiles of electrical vehicles (EVs) and a perfect foresight approach the flexibility of the charging processes is determined in a way, that no user is restricted in his mobility needs. Regarding the start- and end time of each travel the ratio of parking time and required charging time is formed as an indicator of the available flexibility.

The driving profiles are used in a mixed integer linear program (MILP) to optimize the procurement of the required energy for charging the EVs. To different marketing alternatives are considered: in the first step, the optimization considers only the Day-Ahead Auction. The second step combines the Day-Ahead auction with the continuous Intraday market. This combination, denoted as Intraday Redispatch, leads to a significant reduction of costs due to the higher volatility at the continuous Intraday Market. The other major advantage of the Intraday Redispatch is the possibility to trade energy at the continuous Intraday Market until 30 Minutes before delivery, so deviations of the forecasted arrival times of the EVs can be compensated.

The simulation carried out with 50 electrical vehicles shows the realized cost savings for an optimized charging based on the considered short-term markets and the resulting effects on the distribution grid. The Day-Ahead optimizations reduces the charging costs to 30% of the average costs, with the Intraday Redispatch trading strategy the costs could be lowered to even negative costs.



Smart Charging – A strategy for Charging EVs in Big Cities with Load Shifting and Control
Submission-ID 049
Jonas Persson, Johan Tollin, Christian Gruffman, Ying He
Vattenfall R&D, Sweden
By 2030, the overall goal of the Swedish transport sector is to lower the use of fossil fuels by 70% compared to 2010. The climate impact has made electro-mobility in Sweden to start replacing conventional vehicles on a large scale towards the goal. A very large proportion of the vehicles in Swedish major cities can be expected to be electrified in the coming years, near 100% electrification of passenger cars by 2030 is a feasible option.

However, the electricity supply of Swedish major cities is strained for a number of hours during a year. In Stockholm region, for example, network constraint can arise during high loads of about 100 hours distributed during a year. The network constraint issues may still persist, even after today’s ongoing power boost and network enhancement. With the massive penetration of electric vehicles (EVs), the charging pattern of EVs will pose a number of challenges to the city’s power supply system.

This paper addresses these aspects and looks at strategies of how to deal with the challenges brought by increasing EV penetration rates in urban environments. The paper will present the strategies resulting from a vision project within the E-Mobility programme performed at Vattenfall R&D, Sweden. The project studied possible charging scenarios in the case of a fully electric transport system in Stockholm city by the year 2030; assessed the effect on grid power loading by simultaneous charging activities of large number of EVs without steered charging; and analyzed typical demand of city residential power consumers.

The study points out that uncontrolled charging of large numbers of EVs in big cities would stress the electricity network, and the need of controlled charging is a key aspect in the strategy for smart charging of EVs in big cities. Based on the load demand analysis, the project also designs a strategic controlled charging solution by shifting EV load from high load hours to night and low load hours. The details of the analysis and charging strategies will be described and presented in the full paper.



Analysis of Simultaneity Factors of Electric Vehicles with Probabilistic Distribution Grid Planning
Submission-ID 050
Groß Daniel, Früh Heiner, Krzysztof Rudion
University of Stuttgart Institute of Power Transmission and High Voltage Technology, Germany
The number of electric vehicles has increased over the past years in Germany and a further increase is expected for the next years [1]. Distribution system operators are nowadays facing the challenge that they have to plan their distribution grid for the charging of electric vehicles. According to [2], the current distribution grid planning uses two worst-case conditions, one for high load with low generation and one for low load with high generation. In case of low voltage distribution grids, simultaneity factors are defined for the estimation of the maximum load of a high number of customers [3]. Distribution system operators often use empirical values for the definition of their simultaneity factors for different load types. However, in case of electric vehicles no empirical values are available for the definition of simultaneity factors. Therefore, the driving behavior and its corresponding loading behavior is usually modelled based on mobility data [1], [3]. This paper focuses on the impacts of the charging power of electric vehicles to the simultaneity factors.

In this paper, models of the power consumption of residential customers [4] are combined with models of the driving behavior and its corresponding charging power. Here, the differences of the simultaneity factors and the considered power consumption in distribution grid planning is analyzed for different methods of combination and for alternating charging powers. Additionally, the benefits of a probabilistic approach for distribution grid planning is highlighted. A comparison shows that the probabilistic approach is beneficial compared to a deterministic approach in case of a radial grid structure, where the deterministic approach tends to underestimate the line currents.

REFERENCES

[1] G. Walker, Impact and Chances of Electric Mobility for the German Low Voltage Distribution Grids, Ph.D. dissertation, Institute of Power Transmission and High Voltage Technology, University of Stuttgart, Germany, 2017.

[2] CIGRE WG C6.19, Planning and Optimization Methods for Active Distribution Systems, CIGRE Technical Brochure, 2014, ISBN: 978-2-85873-289-0.

[3] S. Kippelt, C. Wagner, C. Rehtanz, Consideration of Electricity Applications in Distribution Grid Expansion Planning and the Role of Flexibility, International ETG Congress 2017, Bonn, Germany, 2017.

[4] D. Groß, P. Wiest, K. Rudion und A. Probst, Parametrization of Stochastic Load Profile Modeling Approaches for Smart Grid Simulations, in IEEE International Conference on Innovative Smart Grid Technologies (IEEE ISGT Europe 2017), Torino, Italy, 2017



Research Campus Mobility2Grid: From Lab to Reality
Submission-ID 051
Karoline Karohs 1, 2, Dietmar Göhlich 1, 2, Enrico Lauth 1, 2
1 Technische Universität Berlin, Germany
2 Forschungscampus Mobility2Grid, Germany
Increasing numbers of electric vehicles and renewable power generation can be beneficial for curbing carbon emissions. Vehicle2Grid technologies are available for integrating such vehicles into power networks that are fed with volatile renewable energies. Hence, cars, busses, and trucks can serve as both flexible energy storage and source. This paper summarizes results of the Mobility2Grid research project in the fields of grids and vehicles, acceptance and participation, and business models. As the paper focusses on the question of how to get from research results to application, it also features questions of successful cooperation and communication within the project. It is shown that it is technologically possible to apply Vehicle2Grid technologies in real-life scenarios; that user acceptance can be facilitated; and that potentially viable business models exist.


Analysis of different sector coupling paths for CO2 mitigation in the German energy system under consideration of energy supply infrastructures
Submission-ID 066
Felix Kattelmann, Markus Blesl
Institute of Energy Economics and Rational Energy Use, University of Stuttgart, Germany
In the context of the energy transition in Germany, the share of renewable energies in the electricity generation mix has been the main focus so far. However, if the German government’s long-term greenhouse gas reduction targets are taken as a basis, decarbonisation of the heating and transport sectors is crucial. In this context, different sector coupling paths must be evaluated in terms of their suitability to achieve the given climate targets.

This paper focusses on the use of sector coupling in the transport sector. In particular, it investigates the direct electrification of the transport sector. In addition, an analysis of the influence of the required energy supply infrastructures on the use of sector coupling technologies for decarbonisation of the transport sector in Germany is carried out. The aim is to examine not only the influence of infrastructures on the choice of sector coupling technologies, but also the impact of the sector coupling options on infrastructures.

To this end, in the framework of the German Kopernikus project ENavi, the energy system model TIMES is expanded with regard to the conceivable sector coupling technologies. In order to be able to adequately evaluate these technologies, a simplified representation of the required energy supply infrastructures will also be implemented. By varying the infrastructure parameters, scenario-based analyses will then be carried out to determine to what extent the infrastructures influence the selection of sector coupling paths and thus the possible composition of Germany’s future energy system.

The main findings indicate that the potential of sector coupling technologies is very much dependent on the choice of greenhouse gas emission reduction targets. In freight traffic in particular, these options only become attractive when ambitious targets are established. With regard to infrastructures, it can be said that a detailed assessment of the infrastructures has a great influence on the energy system. Furthermore, the impact of the use of sector coupling is far from negligible and requires more detailed research.



Charging of Electric Vehicles and its Influence on the Local Voltage
Submission-ID 079
Jonas Wetterström
Vattenfall AB, Sweden
This paper focus on charging of electric vehicles (EVs) and its influence on the local voltage. With the expected growth of infrastructure for charging of electric vehicles this subject is of large interest.

In the paper it will be shown total harmonic distortion (THD), sags, swells, flicker, and supra harmonics of the voltage. This quantities have been measured in combination with the charging current on several electric vehicles from at least two substations. The two examples are from one fast- (symmetric) and several normal-EV charging equipment (asymmetric).

The expected results are that the THD of the voltage is not much influenced from the electric vehicle, but there will be some unbalance in the slow-EV charging case, due to that the charger are one phase loads and they also charge at different times. It has been observed low distortion in the charging current due to the specific EV charger but no changes has been observed in the voltage quality (THD) compared to a substation without EV charging equipment. The voltage quality follows instead the “normal” pattern of other loads in the facility already present before the EV charging is started.

Even though it has not been possible to observe any problem at this facility so far, it is important to continue to do new measurements of EVs in weaker grids.



Comparison of electromobility-impacts on the low-voltage level in different grid regions
Submission-ID 084
Bernd Thormann, Thomas Kienberger
University of Leoben - Chair of Energy Network Technology, Austria
The analysis of electromobility induced grid impacts enables a premature identification of the need for grid expansion. Three various low-voltage grids are considered separately in detail in order to compare the effects of electric vehicles in different regions. For that purpose, inadmissible voltage deviations and thermal line utilizations are determined by using long-term load flow simulations and assessed by means of standardized limits according to EN 50160. Regarding thermal line overloads triggered by peak loads, the analyzed grid regions show similar results. Nevertheless, the potential for implementing a future number of electric vehicles deviates significantly: While the urban grid on the outskirt shows little impact on voltage characteristics, even low e-mobility penetrations cause critical voltage deviations in suburban and rural grids.

Keywords: electromobility induced grid restrictions, low-voltage level, grid regions



Harnesing synergies between electric vehicles and variable renewable power: the impact of smart charging
Submission-ID 090
Arina Anisie, Francisco Boshell, Emanuele Taibi
IRENA - International Renewable Energy Agency, Germany
EVs represent a paradigm shift for both the transport and power sectors, with the potential to aid to the decarbonisation of both sectors by coupling them. Although the transport sector currently has a very low share of renewable energy, it is undergoing a fundamental change, particularly in the passengers road vehicle segment where EVs are an emerging solution. The cost reductions in RE power generation makes electricity an attractive low-cost fuel for the transport sector. A significant scaling up in EVs deployment represents an opportunity for the electricity industry as well.

EVs can act as flexible loads and decentralised storage resources capable of providing additional flexibility to support power system operation. With smart charging, EVs could alternate their charging patterns to flatten peak demand, fill load valleys and support real-time balancing of the grids by adjusting their charging levels. Smart charging therefore is a way of optimizing the charging process according to distribution grids constraints and local renewable energy sources availability and customers’ preferences. Smart charging includes different technical charging options, from the simplest of deferring the EV charging from peak to off-peak periods, to providing close to real time balancing and ancillary services. Such mechanisms range from simply switching on and off the charging through unidirectional control of vehicles (also called V1G) that allows for increase or decrease of the rate of charging, to the technically challenging bidirectional vehicle-to-grid (V2G), which allows the EV to provide services to the grid in the discharge mode. Smart charging techniques differ from system to system: while it tries to capture the synergies with renewable energies, each of renewable energy sources present different availability patterns.

The paper will analyze in depth how smart charging can harness the synergies between EVs and renewable generation, providing insights on what would be the impact of smart charging in power systems (both V1G and V2G technologies). Based on a modeling exercise, the paper will look at two scenarios:



Impact Assessment of Integrating Novel Battery Trolleybuses, PV Units and EV Charging Stations in a DC Trolleybus Network
Submission-ID 095
Mohammed Salih 1, Dirk Baumeister 1, Mahjar Wazifehdust 1, Philippe Steinbusch 1, Markus Zdrallek 1, Stan Mour 2, Petar Deskovic 2, Tobias Küll 2, Conrad Troullier 3
1 Chair of Power System Engineering; University of Wuppertal, Germany
2 SWS Netze Solingen GmbH, Germany
3 Stadtwerke Solingen GmbH, Germany
Solingen is known for the largest operating trolleybus system in Germany, with 50 electrically driven trolleybuses which are equipped with auxiliary combustion engines and 50 additional conventional diesel buses serving the public transport system.

The project "BOB-Solingen" - the abbreviation BOB denotes the German words “Batterie-Oberleitungs-Bus” – is intended to electrify the entire public transport sector by introducing a new kind of trolleybuses, which will be able to travel regardless of the vital overhead line by means of the included battery. BOB is the result of combining the recognized trolleybus technology with the latest battery technology and the intelligent charging infrastructure, creating the next generation of buses which, as a matter of fact, are able to drive on routes with no power supply as well.

Moreover, the project is planned to integrate charging stations for electric vehicles (EV), decentralized renewable power generators such as photovoltaic (PV) systems as well as a stationary power storage system. The stationary storage will consist of used trolleybus batteries to increase their cost efficiency by establishing a second-life utilization concept.

The entire DC system will be transformed into a Smart-Trolleybus-System (STS) allowing an intelligent control and management of the power flow in the overall system. The Chair of Power System Engineering at the University of Wuppertal will develop and implement the essential automation system for the DC grid to use its existing overhead infrastructure as effective as possible within its physical limitations.

In order to realize an intelligent control of the grid, the load flow of the current grid (including the trolleybuses) as well as of the future grid (including BOB) has to be modeled and simulated. By means of the simulation, critical grid situations can be detected. These might occur more frequently in future due to the fact that e.g. the additionally implemented batteries can cause an increased number of peak loads which have to be handled.

This paper intends to simulate and evaluate the power profiles of all operating trolleybuses as well as the planned BOB based on different possible operation circumstances (e.g. stopping or not at traffic lights and bus stops, different stopping durations, traffic influences, variation in temperature and passenger numbers). The power profiles for both the buses and additional actuators within the DC grid, such as PV systems, charging stations and stationary power storage units will be presented and discussed.

The grid state is expected to be strongly fluctuating due to the increased number of loads and feeders, some of which operate bidirectionally. Load flow calculations will be the key to point out the actual grid state in order to enable the essential intelligent grid control. Performance and capability will be presented and evaluated in this paper.



Future System Services Provided from Electric Vehicles
Submission-ID 100
Peter Herbert
Section Manager, Power Technology, Vattenfall R&D, Sweden
Section Manager, Power Technology, Vattenfall R&D, Sweden
In the present situation of expansion of electric vehicles as well as that the current power system has small margins and overall higher demand for electricity, it is important to see how it is possible to include charging of electric cars into power systems that have small margins in power, i.e., bottlenecks.

With the upcoming new load of electric vehicles it is important to use its benefits such as load-shift, possibility to stop charging, or even up-load power to the grid. These capabilities can be used for tasks and deliveries such as; a) emergency power as a global system service, b) primary frequency control as a global system service, c) balancing to avoid regional and local bottlenecks as a regional and local system service, d) voltage control as a local system service, and e) local load-shift in order to use the subscription locally in the most optimal way.

In order to enable these upcoming future system services it is of high importance to drive the development of charging infrastructure as well as its communication infrastructure in this direction.

In the paper it is highlighted urging questions for the development of a smart communication infrastructure for the upcoming infrastructure associated with electric vehicles.

In future scenarios electric cars are expected to take an active part of solving the arising power system issues listed above a) – e). Electric cars need to help the future power system.

It is outlined the importance of standardization for the evolution of the electric infrastructure for electric cars.Also standards that opens up for controlled charging and future implementation of Vehicle to Grid (V2G) where electric cars feed power to the grid and/or Vehicle to Home (V2H) is treated.



Optimal De-Centralized Smart Home-Charging: Potential Study
Submission-ID 113
Mahmoud Shepero, Reza Fachrizal, Joakim Munkhammar
Department of Engineering sciences Uppsala university, Sweden
This paper evaluates the impacts of electric vehi- cles’ (EVs’) smart charging algorithms on reducing the peak of the total load of households. Two smart charging schemes are proposed. The first scheme—postponed charging—is defined as reducing the charging power if the total load exceeds the fuse size, thereby sometimes postponing the charging. The second scheme—capacity-filling charging—is defined as charging the EVs with the difference between the fuse size and the house load, i.e., the available capacity. Both schemes were benchmarked to the uncontrolled charging scheme.

The study was evaluated on 10 different Swedish simulated detached houses without electric heating, and using various combinations of charging powers and fuse limits. The results show that the worst house—the house that needed smart charging the most—needed postponed charging 8 days a year to avoid breaking the fuse. Moreover, postponed charging increased the charging duration, and thus inconvenience to the EV owners, by at most 4 hours. On the other hand, the capacity-filling charging scheme could increase or decrease the charging duration—compared to the uncontrolled charging. An increase is expected if the difference between the fuse size and the house load is smaller than the uncontrolled charging power. The charging duration will be shorter if the difference between the fuse size and the house load is larger than the comparable uncontrolled charging power.

The capacity-filling scheme proved to be more convenient, as it did not increase the charging duration by more than 3 minutes. Moreover, it reduced the charging duration for at least 198 days a year.

The results indicate that charging the EVs by the available capacity—the difference between fuse size and house load—is recommended compared to constraining the charging power.



Urban Network Infrastructure: Sharing of Charging Current and Exploiting Utilization Potential
Submission-ID 127
Kira Rambow-Hoeschele 1, 2, 3, Anna Nagl 2, David K. Harrison 3, Bruce M. Wood 3, Karlheinz Bozem 4, Kevin Braun 2, Peter Hoch 2
1 Robert Bosch GmbH, Marketing and Sales | Automotive Strategy, Germany
2 Aalen University | Competence Center for Innovative Business Models, Germany
3 Glasgow Caledonian University | School for Engineering and Built Environment, United Kingdom
4 bozem | consulting associates | munich, Germany
The Competence Center for Innovative Business Models at Aalen University researches and develops new, economically resilient business models for sustainable electromobility. Ecological possibilities to charge electric vehicles with solar power are investigated. This paper deals with solutions on how to increase the utilization rate of charging stations and how to better use renewable energies for the supply of such. The project is state subsidized by the German Federal Ministry of Education and Research (BMBF) from August 1, 2016, to December 31, 2018, under the references 02K12A150 and 02K12A151. In the context of the research project, business models are developed that generate added value for the stakeholders such as electric vehicle users, grid operators, energy suppliers, and other companies.


Pathways to Electromobility: Upgraded Charging Infrastructure Through Renewable Energies
Submission-ID 131
Kira Rambow-Hoeschele 1, 2, 3, Anna Nagl 2, David K. Harrison 3, Bruce M. Wood 3, Karlheinz Bozem 4, Kevin Braun 2, Peter Hoch 2
1 Robert Bosch GmbH | Marketing and Sales | Automotive Strategy, Germany
2 Aalen University | Competence Center for Innovative Business Models, Germany
3 Glasgow Caledonian University | School for Engineering and Built Environment, United Kingdom
4 bozem | consulting associates | munich, Germany
Within the context of the state-supported, cooperative project “low-carbon city”, Aalen University researches solutions to increase the utilization rate of charging stations and to improve the use of renewable energies for power supply. The project is state subsidized by the German Federal Ministry of Education and Research (BMBF) from August 1, 2016, to December 31, 2018, under the references 02K12A150 and 02K12A151. In this research project, business models are developed that generate added value for the stakeholders such as electric vehicle users, grid operators, energy suppliers, and other companies. This paper particularly focuses on the advancement of semi-public charging infrastructure.


Charging Profile „HomeZone“: Customer Retention Measures and Charging Infrastructure Optimization
Submission-ID 132
Kira Rambow-Hoeschele 1, 2, 3, Anna Nagl 2, David K. Harrison 3, Bruce M. Wood 3, Karlheinz Bozem 4, Kevin Braun 2, Peter Hoch 2
1 Robert Bosch GmbH | Marketing and Sales | Automotive Strategy, Germany
2 Aalen University | Competence Center for Innovative Business Models, Germany
3 Glasgow Caledonian University | School for Engineering and Built Environment, United Kingdom
4 bozem | consulting associates | munich, Germany
The Competence Center for Innovative Business Models at Aalen University researches solutions to supply charging stations for electromobility with renewable energies and increase their capacity. Economically resilient business models for sustainable electromobility are developed. The overall goal is to generate added value for all stakeholders involved, including electric vehicle users, grid operators, energy suppliers, and other companies. The cooperative project “low-carbon city” is state subsidized by the German Federal Ministry of Education and Research (BMBF) from August 1, 2016, to December 31, 2018, under the references 02K12A150 and 02K12A151. From the industry perspective, Überlandzentrale Wörth/I.-Altheim Netz AG supports the research project as regional distribution system operator. Bozem | consulting associates | munich provides business expertise concerning renewable energy and competitive strategy.


Analyses and evaluation of power quality aspects in a low-voltage network with regard to a high penetration of decentralized generation and charging infrastructure
Submission-ID 147
Jochen Zumpe, Johanna Eppler
Fichtner GmbH & Co. KG, Germany
The term "Power Quality" refers to the ideal aspects of voltage quality such as a constant frequency, a perfect sinusoidal shape, a constant rms-value and the ideal symmetry of the three phases. The power electronics integrated in various consumers distort and interfere with them. This paper examines a public low-voltage network including households and electric vehicles as consumers. In addition, some photovoltaic systems feed into the grid. The scenario for the year 2030 illustrates the influence of increased penetration of electric vehicles and photovoltaic systems on power quality in a low-voltage grid. The distortion of the current is particularly high in some transformer outgoing circuits with regard to DIN EN 50160.


Technical and Economic Considerations on Autonomous, Connected, Electric, and Shared Vehicles
Submission-ID 152
Nick G. Rambow 1, 2, Kira Rambow-Hoeschele 3, 4
1 Robert Bosch GmbH | Corporate Strategy Development, Germany
2 ESB Business School | Reutlingen University, Germany
3 Robert Bosch GmbH | Marketing and Sales | Automotive Strategy, Germany
4 Glasgow Caledonian University | School of Engineering and Built Environment, United Kingdom
Autonomous driving, connectivity features, electric powertrains, and car sharing are four important fields on which the automotive industry is currently working. The technological developments in those areas have the potential to change the industry in a way it has never changed before. Those changes will not only have a large economic effect but will also affect vehicle designs in the future. Not only will it be of importance to implement high cyber security standards in order to protect private and sensitive data but also to prepare power system and internet infrastructure in order for future cars to succeed.


The Connected Vehicle and Its Impact on the Development of Electromobility
Submission-ID 154
Nick G. Rambow 1, 2, Kira Rambow-Hoeschele 3, 4
1 Robert Bosch GmbH | Corporate Strategy Development, Germany
2 ESB Business School | Reutlingen University, Germany
3 Robert Bosch GmbH | Marketing and Sales | Automotive Strategy, Germany
4 Glasgow Caledonian University | School of Engineering and Built Environment, United Kingdom
In the automotive industry, several disruptive technological developments are currently going on. One of them is the transformation of the car into a third living space due to a variety of connectivity features that is being developed and added to cars. Those features also foster the attractiveness of electric cars and play an important role in the development stage as an intelligent integration of them needs to be ensured.


Ethical Considerations on Future Vehicle Design
Submission-ID 157
Nick G. Rambow 1, 2, Kira Rambow-Hoeschele 3, 4
1 Robert Bosch GmbH | Corporate Strategy Development, Germany
2 ESB Business School | Reutlingen University, Germany
3 Robert Bosch GmbH | Marketing and Sales | Automotive Strategy, Germany
4 Glasgow Caledonian University | School of Engineering and Built Environment, United Kingdom
The automotive industry is currently facing a variety of challenges that could transform the industry in a way it has never changed before. One main driver of this transformation is connectivity, enabling cars to communicate with devices to offer new features to the customers. Many of which depend on personal data of passengers. This creates threats and opportunities at the same time. As data privacy is a very sensitive topic in today’s world, it is necessary to discuss certain frameworks that ensure that customers are protected and that ethical standards are being implemented. Although many people show interest in these features, a lot of concerns regarding privacy are threatening people. To gain trust among society and to ensure that those features will be of benefit for humans, it is necessary that thoughts about security, privacy, and ethics are made before those features are introduced to customers.


Exploring the Business Case of a Risk-Averse Electric Vehicle Aggregator in the Nordic Market
Submission-ID 158
Jacob Dalton, Lars Herre, Lennart Söder
KTH Royal Institute of Technology, Sweden
The Nordic power system is facing the challenge of the ongoing decrease of synchronous generation along with increased penetration of inverter based renewable generation leading to reduced system inertia. Meanwhile, the electrification of the transport sector will result in a significant amount of additional electrical loads. However, the electrification of private transport is a technology of growing interest that can provide flexibility to the power system if adequately utilized. Electric vehicles (EV) can be considered as temporary energy storage with availability, energy and capacity constraints.

In this paper, we use first hand data of a real EV fleet of Tesla vehicles and their historical driving patterns to develop a two-stage stochastic optimization problem. This model maximizes the profit of a risk-averse EV aggregator that aims to place optimal bids on the day ahead in both energy and Frequency Containment Reserve (FCR) markets. Only uni-directional charging is examined, while we take into account uncertainty from prices and vehicle utilization. Case studies are carried out modelling individual vehicle driving behavior in different Nordic price areas in both winter and summer.

We identify a strong alignment of EV availability and periods of high FCR prices. Results show that consumption is shifted largely towards early hours of the morning. When compared to a reference "cost of charging case", up to 50% of the cost of charging can be covered in Norway, while the entire cost is met in Sweden.



Methods for efficient charging infrastructure placement
Submission-ID 161
Kathrin Goldammer, Oliver Arnhold, Norman Pieniak, Katrin Hübner, Jörn Hartmann
Reiner Lemoine Institut, Berlin, Germany, Germany
Without comprehensive spatial coverage and demand-appropriate distribution of charging points, potential users of electric vehicles have little incentive to make the jump from conventional to battery-electric motor vehicles.

Whether charging infrastructure expansion is effective will be determined by future demand, the quality of the coordination between stakeholders and exploitation of potential synergies between public, semi-public and private charging infrastructure.

Today, charging infrastructure planning must include all interested parties, many of whom had not been considered until recently. These include municipalities, public works departments, distribution system operators, transit authorities, car-sharing companies, charging infrastructure operators, supermarket chains, and landlords.

Because any one stakeholder can now play multiple roles, the traditional channels and directions of communication in the energy industry will change.

Charging infrastructure must meet conflicting criteria. Decision-makers need a tool or suite of tools that helps them to balance these competing criteria. Any such tool must make electromobility development potential apparent, deliver reliable estimates of future demand and assist in coordinating planning, implementation and operation of charging infrastructure.

So far, most planning tools do not include the full spectrum of charging powers available between 2.7 kW and 350 kW, have not considered mid- and long-term time horizons for infrastructure development, and do not have the ability to directly include all the stakeholders in the planning process. Further, they typically do not integrate real-time data from monitoring of existing charging stations, a requirement for any demand-oriented infrastructure planning.

Successful integration and use of charging points also require coordination with on-site implementers, as well as consideration of specific site conditions and information about independent activity in semi-public and private spaces not traditionally gathered by governments and planners.

We introduce a set of quantitative and qualitative methods for producing robust planning guidance based on our experience in the German state of Brandenburg.



Electric Vehicle User Behavior and Demand Response - A strive for Energy Autonomy
Submission-ID 167
Nithin Isaac
Nithin Isaac, South Africa
Electric vehicles are being promoted world-wide by governments to reduce dependence on oil and to mitigate greenhouse gas emissions. In addition to barriers of entry such as the costs of the new technology, convenience, and availability of electrical energy, consumer behaviour is also a concern in developing countries such as South Africa. The Council for Scientific and Industrial Research (CSIR) has estabished a program aimed at promoting energy autonomy within the campus. The program focuses on the use of excess energy generated through renewable sources as well as initiating demand response activities to charge electric vehicles. The campus currently owns 10 electric vehicles, both hybrid and battery, which can be used by staff on the campus as a means of striving towards energy autonomy. With increasing utilisaiton, and the development of fast-charging systems, it is envisioned that more people will be keen to use these vehicles. However, the development of the electric vehicle market is also tied to consumer awareness of the benefits of these vehicles, hence, understanding consumer behaviour with regards to electric vehicles can help encourage its adoption. The integration of the electric vehicles to the envisioned micro-grid will help the campus become self-sustaining in terms of its energy use. This paper concentrates on understanding consumer behaviour in the electric vehicle space in order to maximise adoption of the technology and to promote energy autonomy.


Evaluation of Modular Infrastructure Concepts for Large-Scaled Electric Bus Depots
Submission-ID 174
Laura Haffner 1, Markus Dietmannsberger 2, Detlef Schulz 1, Marc Schumann 1
1 Helmut Schmidt University, Germany
2 Hamburger Hochbahn AG, Germany

The city of Hamburg, Germany committed to buy exclusively emission free buses by 2020. Thus, public transportation companies as Hamburger Hochbahn AG (HOCHBAHN) must build a charging infrastructure for large electric bus fleets. Currently HOCHBAHN is planning an urban charging depot for 240 electric buses (EBs). This pilot project is the first large-scale infrastructure project for EB fleets in Germany. New electrical infrastructures for bus depots must comply with local grid capabilities. Furthermore, they have to fulfill highly individual boundary conditions and operational requirements. In the close future, most public transportation companies will face the challenge of developing electric infrastructures for EB fleets. This paper identifies the key components of electric infrastructures for bus depots based on the introduced concept. It outlines decision objectives, that describe the characteristics of a concept, and confronts them among themselves. The authors apply a sensitivity analysis to evaluate how dimensioning of components affects bus charging times and operation. The developed algorithm in this work uses real data and demonstrates that components can be downsized by 8\%. Furthermore, the method is extended to evaluate needed capacity for varying module sizes of concepts.



INVADE flexibility centralized algorithm to manage electric vehicles under DSO requests in public charging stations with limited information
Submission-ID 175
Pol Olivella-Rosell 1, Pau Lloret-Gallego 1, Stig Ødegaard Ottesen 4, Sigurd Bjarghov 5, Roberto Villafafila-Robles 1, Michel Bayings 2, Patrick Rademakers 3
1 Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, ETS d'Enginyeria Industrial de Barcelona, Universitat Politècnica de Catalunya, Spain
2 GreenFlux Assets B.V., Netherlands
3 Elaad, Arnhem, Netherlands
4 eSmart Systems AS, Halden, Norway
5 Department of Electric Power Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
The current amount of electric vehicles (EVs) in the Dutch distribution systems is raising doubts about their feasible massive penetration in the forthcoming years. Different initiatives are designing innovative solutions to reduce the need of grid reinforcements and grid tariff price increase. One of these initiatives is the INVADE H2020 project (www.h2020invade.eu). It aims to develop a centralized platform managed by a flexibility operator (FO) which interacts with distribution system operators, balance responsible parties and EV charging stations. The FO is responsible of a subpart of the aggregator activities e.g. pooling small flexibilities of customers or network users through the centralized platform in order to make use of their flexibility in the grid management or participating in energy markets.

The INVADE project has pilots in The Netherlands. This paper will describe the large scale offices and parking lots case for semi private/public situations and the large scale public case with charge points in the public domain. Both sub-pilots have in common the lack of available information regarding the charging process as users and EVs are completely unknown. This makes the definition and formulation of the optimization problem more challenging and more dependent on the forecasting tools.

In such a situation, the DSO can face congestions due to simultaneous EV charges causing grid congestions or voltage limit violation in weak or remote areas. Therefore, the DSO could be interested in offering economic discounts to EV drivers if they reduce or even delay their charging processes when there is grid scarcity. Additionally, EV charging could be re-scheduled in some cases where time flexible customers want to utilize fluctuating prices in order to save charging costs.

The nature of the problem is that some information is not known with certainty at the moment decisions are made, and further, that information will be revealed successively. To handle this situation, usage of a rolling horizon principle has been selected, which implies that the process of receiving fresh data, updating predictions, making decisions and sending these to the local systems is repeated for each time-slot

The paper is structured as follows: The section 2 presents the Dutch case studies, section 3 presents the optimization problem mathematical formulation, section 4 shows the inputs and outputs obtained and the section 5 includes the paper conclusions.



Hot-spot Scenarios of Electrical-Vehicles on the Low Voltage Grid including Statistics and Effect of decentralized Battery Storage
Submission-ID 182
Joel Wenske 1, Benjamin Matthiss 1, Jann Binder 1, Thomas Speidel 2, Volkmar Klausser 3, Michael Klesse 3
1 Zentrum fuer Sonnenenergie- und Wasserstoff-Forschung Baden-Württemberg, Germany
2 ads-tec GmbH, Germany
3 Stadtwerke Nürtingen, Germany
Suburban citizens are the ‘first movers’ in battery electrical vehicles (BEV). Thus, suburban areas and low voltage grids will be the first to become hot spots when integrating battery electrical vehicles (BEV) in the grid. This paper analyzes the impact of different BEV penetration levels on the voltage drop in several strings of a suburban network, the statistics of charging events and the influence of battery storage at each charging station on the remaining network load.

For BEV-penetration levels of 5%, 10% and 21% and for charging stations (CS) of 11 and 22 kW the additional transformer loads and voltage drops for this suburban network are calculated.

The worst-case assumption of simultaneous charging of all BEVs in a string of 60 households (HH) is used as a starting point. In this case more than 5% penetration of BEVS will always lead to excessive voltage drop, if charging stations are not clustered close to the feeder of the string.

However, including the statistics of arrival time (with a maximum at 18.00 h) and the duration of individual charging events (as they depend on the statistics of daily driving distance; 70% of cars have driven less than 50 km per day in Germany), the maximum number of simultaneously charging vehicles is reduced significantly with a high confidence. For the example of 60 HH and 21% BEV penetration (which leads to 17 BEVs in the string), the number of simultaneously charging vehicles is decreased from 17 to 6 BEVS with a confidence of 99.7%.

In a final step, the impact of decentralized storage placed at each charging station is considered. With 5 kWh of local battery storage, which is assumed to cover the initial recharging effort, and considering the distribution of driving distances in Germany, only 34% of all BEVs need further recharging from the grid. For the above example of 17 BEVs in a string, a 5 kWh storage leads to a maximum of 3 simultaneously charging vehicles with more than 99.7% confidence. 10 kWh and 15 kWh of battery storage at each charging station leads to a maximum of 2 and 1 vehicle(s) with more than 99.7% confidence, respectively.

Using the same approach, 100% penetration with BEVs s and 15 kWh battery storage at each private charging station, of the 79 vehicles in the above string ouf the network, not more than 3 vehicles will be seen to charge from the grid simultaneously with a confidence of 99,7%.

Thus, it is very important to take the statistics of charging events and average usage of cars into account, to limit network-extension effort to a reasonable amount, while still providing a high service level for the customers.



Future Impact of Electromobility on the Energy Supply Grid of Technische Universität Braunschweig
Submission-ID 183
Michael Kurrat
Technische Universität Braunschweig, Germany
By the year 2050, the TU Braunschweig wants to achieve a climate-friendly building stock with a very low energy requirement and a mostly coverage from renewable energies. To achieve this goal, it is necessary to improve energy efficiency as well as to expand renewable energies based on solar energy and biomass. Due to the imminent change in the mobility sector towards electromobility, the integration of high-performance consumers represents another challenge for the distribution grid. In order to be prepared for the upcoming grid effects, strategic planning at the distribution grid level is already indispensable from today's standpoint.

TU Braunschweig’s buildings are distributed in various areas within the city. In total, the campus comprises four separate areas that can be viewed independently of each other. In addition to the central campus, there is a campus area located at east as well as at north. Each campus power grid includes medium voltage and low voltage level.

Simulations of the campus grid were carried out using DIgSILENT PowerFactory. A separate model is created for each campus grid. Load flow calculations can be carried out within a selected observation period.

In the first step a qualitative mapping of the grid structure including the specific parameters of cable and transformer is made using the existing planning documents from the building management department of the university. In the second step, the electrical load and generation profiles are implemented in the simulation model. The university has a comprehensive system of electrical meters distributed throughout the campus.

In order to make a forecast for the respective observation period, assumptions regarding the development of electromobility, renewable energy integration and energy efficiency improvements must be made for the simulation model.

With regard to the electromobility sector, studies were used to determine the demand. The results were compared with the parking situation as well as the grid operating resource limits. For PV integration, an analysis of all roof surfaces with consideration of the structurally loading of the roofs as well as the monument protection of individual buildings was carried out. Based on the expected improvements depending energy efficiency, the Federal Government's targets for 2020 (10 %) and 2050 (25 %) will be used as reference values.

In further investigations of the paper, the development of an energy supply concept is to be addressed in order to achieve the goals set by the Federal Government. For the observation periods 2020, 2030 and 2050, the influence of electromobility through different levels of penetration is evaluated. The effects on the university's distribution grids are investigated using the simulation model. Furthermore, the integration potential of electrical energy storage systems in combination with a charging management system is analyzed and presented.



Automatic chargeable vehicles in the prosumer’s ecosystem
Submission-ID 200
Robert Eriksson 1, Stefan Pettersson 2, Urban Kristiansson 2, Johan Wedlin 2
1 Volvo Cars, Sweden
2 RISE Viktoria, Sweden
Since more than 40 years, electrification has been on the car manufacturers’ observation list. Research, development, production and sales of electrified vehicles proves that electrified vehicles are the alternative for future mobility. Improvements in battery technologies have finally matured and viable products with electric propulsion are now on a broad scale entering key markets. However, it doesn’t stop here, moving into electric mobility means so much more as it opens up a world of new opportunities with foreseen changes in user behaviour enabling new offers to users of future electrified mobility. Just seeing the change as a different fuel is just not enough. For example, there is a need to control charging during peak power hours to save money for the customers. Furthermore, some customers also want to use their remotely produced electricity when charging their vehicle, preferable by using new convenient inductive charging.

How will the electro-mobility solutions for next generation customers of vehicles look like? Volvo Cars and RISE Viktoria are undertaking a pre-study with the main task to address additional research needs covering a situation where vehicles are finding charge spots, optimizes automatic charge control and enabling for prosumers to utilize own produced electricity as fuel.

This paper will explore some of the needs and possibilities opened up when transferring to next generation electromobility taking power production, and remote distribution of energy into consideration.



Smart Integration of Photovoltaics, Vehicle Charging, and Battery Storage in a Household
Submission-ID 205
Christofer Sundström 1, Maximilian Kronawitter 2, Lorenz Viernstein 2
1 Vehicular systems, Linköping University, Sweden
2 Technische Universität München, Germany
The installed power of photovoltaics (PV) increases rapidly, as well as electric vehicles (EV). Most of the EV charging will occur at home, and there is a possibility to shift the charging in time to minimize the electricity cost. The reasons are for example to maximize the self-consumption of the produced electricity, and to charge the EV when the electricity price is at the lowest rate, since the electricity price is set by hourly rates one day in advance in northern Europe. To maximize the self-consumption of the generated PV power, battery storage systems (BSS) are common in Germany, but not as common in Sweden. Simulations and optimizations show that installation of PV systems significantly cuts the electricity costs for the households. Optimizing the time when to charge the EV decreases the yearly electricity cost by about 5% in Sweden, which is a good contribution since the investment of such system is small. Installing a BSS saves only about 3%, and is therefore not profitable due to the high investment. In Germany the difference between selling and buying electricity is significant, and therefore the electricity bill savings are about 1500SEK/year (6%) by installing a 5kWh BSS. Considering the investment cost, this is not yet profitable, but only a relatively small change in the market conditions will make the BSS profitable in Germany.


The ELECTRIFIC Market Maturity Model: Assessing the Market for Electric Mobility Grid Integration Systems
Submission-ID 208
Sonja Klingert 1, Maria Perez-Ortega 2
1 University of Mannheim, Germany
2 GFI, Belgium
One of the key elements for the success of the adoption of a new solution or service by customers is to analyse the target market in detail. Knowing the customer needs and the way an offer can release their pains will help defining the most promising marketing strategy to approach them. But performing a market analysis is a very complex task, especially if the market is not ready yet. This is the case of the EU-funded ELECTRIFIC project, aiming at providing innovative solutions for a seamless integration of eMobility into the electric grid. In order to facilitate the analysis of the potential market of the ELECTRIFIC solutions in different countries, a methodology called Maturity Models was applied and adapted to the characteristics of a general “EV grid integration market”. This paper introduces this methodology, explains preliminary experiences within the project and provides examples of application.


Increased Utilization of residential PV-Storage Systems through locally charged Battery Electric Vehicles
Submission-ID 222
Dennis Huschenhoefer 1, Johannes Mieser 1, Jann Binder 1, Thomas Speidel 2
1 Zentrum fuer Sonnenenergie und Wasserstoff-Forschung Baden-Wuerttemberg, Germany
2 ads-tec GmbH, Germany
An essential factor to improve the carbon footprint of Battery Electric Vehicles (BEV) is charging the battery from renewable energy sources. Hence, charging from a residential roof-mounted PV Plant is a very suitable proposition. Charging during evening hours will require a local stationary battery.

Battery storage systems are installed in Germany in more than 50% of all new residential PV installation. For residential electricity consumption of 10 to 12 kWh per day, a battery of 4-6 kWh leads to an optimum in terms of profitability (250-280 equivalent full cycles per year). Increasing the battery capacity will lead to lower specific cost per kWh of the battery and higher efficiency of the overall system, but will not lead to sufficient gain in self-consumption in order to pay for the additional invest (a 10 kWh battery leads to approx.180 cycles per year). The battery utilization can be proved, if the battery provides additional services for the network or for the customer.

Large batteries in domestic applications are not fully discharged during evening hours in summer. Hence charging a BEV during evening hours can take advantage of the surplus of stored electricity for large batteries. The conference paper will provide plots of battery utilization (in terms of equivalent full cycles per year) as it depend on PV size, local demand, daily driving distance and charging patterns (during day or evening; slow or fast charging). For the aforementioned scenario (10 to 12 kWh electricity consumption of the household; plus 10 kWh per day for charging of BEV during evening hours) a battery of 10 to 12 kWh will be cycled approx. 280 times per year and is therefore utilized well.

The final analysis of opportunities (saving through own consumption) leads to an indication of the allowed cost for the battery to provide a positive business case. This paper builds on previous publication of ZSW on PV storage systems, self-consumption, level of autarky and allowed battery cost for a positive business case. Those studies have been a result of simulations taking time series of measured yearly solar radiation and consumption as input data. Those results compared well with field test data.



A Behavioral Perspective on Smarter EV Use
Submission-ID 224
Celina Kacperski 1, Florian Kutzner 1, Jérémy Wautelet 2
1 University of Mannheim, Germany
2 GFI, Belgium
The present paper offers an effective approach to integration of behavioral science insights into a navigation recommender system software. The goal is to provide EV drivers with an intelligent navigation system that allows the choice between different routing recommendations. We investigate which incentives are most successful at encouraging users to make decisions that promote a stable grid and the use of renewable energies. We present the current and planned user interface of the ELECTRIFIC ADAS - an advanced driver assistance system developed within the framework of the Horizon 2020 project "ELECTRIFIC" and a selection of behavioral steering techniques - such as financial and symbolic incentives, or default settings – that will be employed within the context of the ADAS system.


Assessment of new flexibility instruments for electric vehicles to increase network utilisation
Submission-ID 235
Michael Doering, Christian Nabe, Michael D
Ecofys Germany GmbH, Germany
Distribution system operators face the challenge of a high penetration of electric vehicles – new flexible demand units with high connection capacity (fast charging stations). Recent studies[1] have shown an increase of network congestions due to load and the need for significant network extension in the low-voltage system, if the load behaviour of flexible demand units is not coordinated with the available network capacity. In parallel, further digitalisation offers distribution system operators new opportunities to apply advanced metering (e. g. smart meters) and control equipment (e. g. wallbox for electric vehicle). However, to address these challenges and opportunities by the distribution system operators, new flexibility instruments for distribution system operators are needed.

Our study, performed by Ecofys and E.ON, specified key elements of economic and technical framework conditions to integrate electric vehicles and flexible demand units ‘grid friendly’. We focus on the regulation in Germany and use quantitative data from German distribution systems (E.ON), but our conclusions provide general principles for generic distribution systems. The identified instruments had the two main target functions: Use flexible load to increase the network utilisation (decrease cost per grid user) and avoid inefficient network extension. Therefore Ecofys, a Navigant company, identified specific problems and opportunities through an expanded use of flexibility and thus to answer the questions which regulatory flexibility instruments are needed in distribution networks.

For this purpose, we conduct an extensive analysis of recent studies, develop three flexibility models for an appropriate flexibility instrument and evaluate these using previously defined criteria. The instruments are based on two basic principles, that the distribution system operator is able to influence demand units in the low voltage systems via (1) providing a quota / schedule of maximum available capacity or (2) direct control (flexibility procurement). For each model we specified and described

Finally, we assessed the instruments for typical distribution network classes, based on a quantitative analysis of the population of demand units in the German distribution system. The results and conclusions highlight key elements of future regulation which can effectively and efficiently unlock the potentials of new demand units for flexibility in the distribution system.


[1] Ef.Ruhr (2017): Verteilnetzstudie für das Land Baden-Württemberg, available at https://um.baden-wuerttemberg.de/fileadmin/redaktion/m-um/intern/Dateien/Dokumente/5_Energie/Versorgungssicherheit/170413_Verteilnetzstudie_BW.pdf



Autonomous Voltage and Frequency Control by Smart Inverters of Photovoltaic Generation and Electric Vehicle
Submission-ID 236
Shotaro Kamo 1, Yutaka Ota 1, Tatsuhito Nakajima 1, Kenichi Kawabe 2, Akihiko Yokoyama 3
1 Tokyo City University, Japan
2 Tokyo Institute of Technology, Japan
3 The University of Tokyo, Japan
Active distribution management is required for integrating massive renewable energy sources and new electrical devices such as the electric vehicle into the distribution power system. We are focusing flexible control capability of smart inverters of the photovoltaic (PV) generations and the electric vehicles (EV) interconnecting with the distribution system. In this paper, an autonomous distributed control for maintaining voltage in the DSO level and contributing supply and demand balancing in the TSO level is proposed. The interferences are concerned in case of the autonomous control with higher response between voltage and frequency control functions, the PV and EV inverters installed into same location, and the multiple inverters installed into different location on the distribution feeder. So, the HIL(Hardware In the Loop) consisted by real-time power system simulator and two smart inverter systems is conducted in the laboratory, and proposed autonomous control schemes are validated.

We proposed Watt & Volt / Var control in which EV and PV are cooperated for maintaining voltage in the distribution feeder in the solar integration workshop 2017. In this paper, by Freq / Watt control contributing to the frequency regulation in the TSO level is also installed to in the EV inverter. A smart inverter that suppresses voltage fluctuation and frequency fluctuation by autonomous distributed control is to be successfully realized by the proposed control.

Voltage and power flow profile of a distribution feeder in which massive PVs and EVs are interconnected and global frequency deviation based on the supply and demand calculation are emulated in a real-time simulator at the same time. HIL test is carried out by use of the real-time simulator and two smart inverters of the PV and the EV. On the real-time simulator, Opal-RT, the typical distribution feeder in Japan was modified at 6600V level. The feeder length is set at 5km. 720 houses are interconnected to the feeder. In this paper, it is assumed that PVs and EVs are interconnected to all houses, and all the interconnection inverters have control capability. A thermal power generation, an electric power demand, power output of the PVs based on actual measurement are modified for supply and demand imbalance calculation. Calculated frequency deviation is applied to the modified voltage source of the distribution substation at the top of the distribution feeder. Two different type inverter system, TriphaseNV: PM15 and MITSUBISHI ELECTRIC: Smart V2H, are used as actual smart inverters installing proposed control strategies.

Effectiveness of autonomous distributed control by PVs and EVs on the distribution feeder was confirmed through the HIL tests. And, there ware no interference and unstable phenomena caused by multiple smart inverter control. It is said that smart inverters of PVs and EVs is very effective as control devices for TSO and DSO.



Smart Substations for the electrification of road transport infrastructure
Submission-ID 242
Bernhard Ernst
Fraunhofer IEE, Germany
Introduction

In order to reduce the amount of CO2, more and more transitions from classical mobility towards electric mobility are on the way. Besides the transition from internal combustion engine cars toward electrical powered cars, a huge amount of CO2 can be saved by replacing heavy good vehicles powered by Diesel with electric ones. This is in particular interesting, since more and more goods have to be transported on roads due to full capacity of rail-bound transports. This makes it inevitable to electrify highways in order to power the vehicles via overhead wires. The substations (rectifiers) which connects the DC overhead wires with the surrounding distribution AC networks could be used in a smart way to stabilize the power injection and hence the voltage on the overhead wires, as well as providing reactive power for the distribution network in order to compensate for their own influence and additionally provide system services. A project currently carried out at Fraunhofer IEE investigates on the potential of smart substations. Results will be shown at the workshop.

Use Cases and Simulation

Four worst case scenarios will be investigated (combinations of high and low consumption and generation). In these scenarios, the electrified highway will be weakly, mean and strongly used by the vehicles. Also one scenario will be performed without any influence from the electric vehicles. Each scenario will be simulated one time with and one time without a smart substation. The aim of the smart substations will be to control the voltage on both sides of the station to hold a certain value. We will also investigate if it is possible to generate ancillary services which can provide the DSO to the TSO (e.g. reactive power at PCC, voltage control …) using these substations. Also minimizing network losses and losses on the overhead wires is one focus in the simulations.

Expected Results and Outlook

We expect that the electrification of highways will have a significant influence on the supplying distribution grids. The influence will be strongly dependent on the dimension of the substations and the amount of vehicles using the highway (it also depends on the capacity and dimensioning of the vehicles themselves and their storage). Using conventional static substations can result in voltage problems for the distribution grids and also on the overhead wires. The latter can be omitted placing the substations such way, that full load scenarios from the vehicles are covered..

On the DC side smart substations can control the voltage at the upper limit of the designed voltage band. At the same power this leads towards a lower current and therefore a lower voltage drop on the overhead wires resulting in a lower number of substations needed. A cost benefit analysis of regular and smart substations will show the best solution from economical point of view.



Optimized grid function of charging infrastructure
Submission-ID 243
Bernhard Ernst
Fraunhofer IEE, Germany
Abstract

Fraunhofer IEE is planning a new project for the macroeconomic optimization of the charging infrastructure and the distribution grid for fast developing e-mobility. Negotiations with potential partners to compose a consortium of distribution grid operators, car manufacturers and research organizations are already in a mature stage. The results should be achieved through an integrated analysis of the complete value chain of electric vehicle charging infrastructure. The aim is to enable the various stakeholders to offer the best solution in terms of overall economic efficiency, which optimally serves the needs and interests of vehicle users, vehicle and charging infrastructure manufacturers as well as grid operators and energy suppliers. During a planned project term of about four years frequent workshops with all stakeholders are planned. The consortium should use this format to gather as many information as possible and gain knowledge that is not in the focus of the project partners by nature.

The main result of the project is the description of optimal technology mix with regard to charging technology, ICT infrastructure, grid expansion and needs-based charging infrastructure development through holistic charging and grid operating strategies.

The aim of this paper and presentation is to introduce this new project and encourage stakeholder to participate in the planned workshops and give their input to the project.



What E-mobility has in common with a mobile- phone and what “gridfriendly” charging means.
Submission-ID 244
Yetvart Artenoglu
GridSense (InnoSense Ltd), Switzerland
Intro:

The energy sector is changing drastically. Driven by the reduction of CO2-emissions is the production and supply of electrical energy shifting from central plants to a large amount of decentral, renewable and small ones. The fossil vehicle is replaced by electric or hybrid engines. Heat is less and less generated on the basis of oil/gas and more by electric heat pumps. In short, the demand for electrical energy and power will increase in short to medium term, despite increasing the efficiency of appliances. The distribution of electricity has previously been unidirectional, from large power plants down to the end-customer via the distribution grid and is today already bi-directional and very decentral. The private household is transforming from a pure energy consumer to a so called "prosumer" (producer / consumer), as they want to harvest or feed-in their own “green electricity”.

A large amount of electric vehicles will be introduced to the market in the near future. E-mobility will be affordable to the broad market. Many e-mobility associations are agreeing that despite the actual high demand for fast-charging points, most of the charging will be happening either at the private home or at the workplace (fleets), means on the level of the distribution grid.

Thesis:

E-Mobility and Wallboxes up to 22KW are increasing the electrical power requirements in a house and as well in the distribution grids, next to the high rate of simultaneity-effect. These vehicles are typically connected at least 8 hours at home (sleep) and / or 8 hours at the office (work), and therefore have a high potential for flexibility in their load-management. This flexiblity can be learned, preditect and used for peakshaving or shifting. Either via DR-models, power based tarifs or even dynamic grid tarifs depending on the chosen energy management method. If there is no charging-concept, then will the car be charged based on customer requirements, mostly like a mobile-phone (user centric charging). Home = plug in

Additional electrical-car charging and PV-generators will bring Power- and Voltage-violation in the distribution grid, if there is no active energy management. The distribution grid will reach its limits and has to be re-inforced with high amount of costs, which has to be paid by the society. A pure reinforcement without smart technologies will not work, according to many distribution system operators nor is it the economically best option in many cases.

New flexibility concepts for companies like Distribution System Operators, Utilities, Mobility-Service-Providers, etc. are requested for a hassle free implementation of e-mobility and the management of Energy Flows in the house as well at the distribution grid level.

Conclusion:

“Solving the issues of renewable energy integration at the place of its origin – in the private household and the distribution grid.



Maximizing charging power for electric vehicles by optimal utilization of residential photovoltaic battery energy storage systems
Submission-ID 247
Henning Steffens, Raphael Hollinger
Fraunhofer Institute for Solar Energy Systems, Germany
The local production of solar energy by PV systems for self-supply with electrical energy is both economically and ecologically interesting and has been common for many years, especially in single-family houses. A growing proportion of these single-family houses with a PV system are using a locally installed battery to further reduce the electricity consumption from the public electricity grid. Electrical vehicles (EV) are another option to reduce PV surplus, especially if there is an intelligent charging strategy implemented. These new smart charging services are getting more and more attention both from users and automotive manufacturers, due to the fact that they provide new economically promising options and enhanced use comfort as well. This paper contributes to the identification of new charging services while ensuring the main motivation of potential electric vehicle buyers: striving towards self-sufficiency and sector coupling by using a residential PV battery energy storage system.

Within the proposed paper, we will present an in-depth analysis of the energy and power flows of residential PV battery systems in combination with EV and local charging infrastructure. The analysis will focus on the potential to increase speed of charging in times of limited power availability from the public grid. Hence, the following four use cases are analysed for this purpose:

  1. Independent operation of the photovoltaic system, the battery energy storage system and the charging point of the EV, while operating within system limitations
  2. Optimization of the self-consumption share by scheduled charging of the EV
  3. Actively reserving capacity in the PV battery system (only charged by PV surplus) to guarantee EV charging from PV battery
  4. Predictive, deliberate charging of the PV battery system from the public grid to ensure sufficient capacity (also in winter) to provide EV charging powers above grid limits realised by combined charging from the grid and the PV battery system

Therefore load flows in residential photovoltaic battery energy storage systems will be simulated for a multitude of individual residential buildings using minute resolved data of photovoltaic power plants, residential load profiles, charging and driving profiles of electric vehicles. Following this, a sensitivity analysis will be performed for the presented charging services. Due to the big seasonal differences in the service level of these use cases this paper finishes with a detailed seasonal analysis of the charging services.



Grid to Vehicle and Vehicle to Grid Systems for the Large-Scale Penetration of Renewable Generation
Submission-ID 253
Joaquim Delgado, Pedro Moura, Anibal de Almeida
?Institute of Systems and Robotics - ?University of Coimbra, Portugal
The electric power system is quickly changing due to the growing penetration of intermittent and non-dispatchable renewable energy sources. Simultaneously, the demand should ideally be able to be adapted to the renewable generation availability, directly with demand response or indirectly using energy storage technologies.

Simultaneously, the transport sector with electric vehicles (EVs) is increasingly an important consumer of electricity. However, as fleets increase, and when EVs are immobilized and connected to the grid they can be used as controllable loads, charging in periods with higher renewable generation or lower prices, using the Grid to Vehicle (G2V) system. With adequate technology, in addition to absorbing power from the grid, vehicles can also use some of their storage capacity to inject energy into the grid, in order to ensure the balance between the generation and demand, using the Vehicle to Grid (V2G) system.

According to some authors, this operation would require a complex centralized management system that would command the dispatch per group of loads. Others argue that an effective policy of real-time pricing would be enough to motivate the charging and grid injection in the desirable periods. Other authors also advocate a mechanism with each load presenting the capacity to detect an increase in the voltage or slight frequency deviation in the local grid, using it as signal in the decision of charging or grid injection

However, with current electrochemical technologies, cells degrade according to age, discharge depth and number of charge/discharge cycles. Therefore, with V2G the number of charge/discharge cycles is accelerated and the degradation of cells has to be known accurately so that owners can be remunerated in order to feel encouraged to participate in V2G.

The implementation of inductive recharge systems introduces a great simplification in the operation of recharging the EVs, eliminating the cabling and the human intervention. The EV when not in use in the transport only needs to be immobilized on a point of transfer of energy and to allow (or not) the G2V or V2G operation, by pre-programmed indication of its owner, considering the percentage of available battery capacity, the minimum DoD, the operating period, the required SoC at the end of the period, etc. All these features are now easily implemented in smartphone APP, digital identification technology and wireless systems.

The full paper intends to discuss the technologies and methodologies for the implementation of Grid to Vehicle and Vehicle to Grid systems, as well as their potential benefits for the grid in a scenario with large-scale penetration of renewable generation.



Optimal G2V Scheduling of Electric Vehicle Aggregator in Responsive Reserve and Regulation Markets Considering TOU Pricing
Submission-ID 264
Suman Sharma, PRERNA JAIN, ROHIT BHAKAR
Department of EE, MNIT, Jaipur, India

Optimal G2V Scheduling of Electric Vehicle Aggregator in Responsive Reserve and Regulation Markets Considering TOU Pricing

Sharma Suman* , Prerna Jain, and Rohit Bhakar

* Department of Electrical Engineering, MNIT Jaipur, India. 2015ree9012@mnit.ac.in

Department of Electrical Engineering, MNIT Jaipur, India

Abstract: Various entities in electricity market can formulate self-scheduling problem to minimize the costs or maximize the profits. The System Operator (SO) perspective is to minimize the operating cost with shaved peaks and filled valleys. Profit maximization with Charging cost minimization is major concern of Electric Vehicle Aggregator (EVA) in scheduling problem. Coordinated dynamic charging strategy aids EVA to allocate power effectively considering techno-economic constraints. Charging rate modulation according to base load profile of SO and TOU prices as well, significantly enhance EV adoption under sustainable smart grid environment. Optimal Scheduling of EVA involves energy management and available capacity of EVs for participation in multiple markets. Proposed model increases flexibility for load shifting according to price-based demand response framework to increase economic efficiency and reducing the charging peak load simultaneously with satisfaction of EV owners.

Objectives and context

This paper proposes an Optimal TOU pricing based G2V scheduling Strategy of EVA for reserve and regulation markets considering their trade-offs. Profit assessment through multiple markets participation with simultaneous perception of customers and SO, is the challenge towards EVA. G2V scheduling is economically viable only when revenues earned by AS provision outweighs purchase costs for charging energy. In charging mode (G2V), EVA earns revenue for being on stand-by when providing down regulation. EVs utilize additional energy for transportation purposes and thus EVA does not entail additional revenue of energy sale. EVA increases the adoption of EVs by incentivizing EV owners through reduced charging cost (lower than residential electricity prices). TOU price signals are sent downstream to EV owners and charging requirement signals from EV owners dispatched upstream to the EVA. EVA procures DR at the least-cost without sacrificing benefit of consumers and SO. The EVA performs impact analysis of varying dispatch in response to variation in market prices of energy and AS. High value of price differential (difference of maximum price and minimum price) has the capability to compensate for the additional losses if any.

Stage I

Scheduling

Joint optimization of charging cost and revenues

Stage II

Dispatch

Optimal allocation of regulation and reserves

Fig. 1 Typical Architecture of Two-Stage Coordinated Dynamic Charge (Unidirectional G2V) Scheduling and Dispatch of EVA using TOU Pricing



Scenario-driven Analysis of Intelligent Charging Strategies Caused by the Market Ramp-up of Electric Vehicles
Submission-ID 267
Detert Bracht 1, Tim Montag 1, Marcel Kurth 2
1 P3 group, Germany
2 RWTH Aachen, Germany
The accelerating market ramp-up of electromobility in the sector of road-bound passenger and freight transport leads to an increase in the installation of charging infrastructure connected to the distribution grids. The additional power and energy demand of electromobility affects the power flow through operating equipment. In case of high load caused by electromobility, local grid congestion can occur. If no suitable countermeasures are taken, this might induce a need for grid reinforcement. To reduce the need for grid reinforcement, using intelligent charging strategies combined with other smart grid communication systems might be a feasible solution. In this paper, a methodology to forecast the market ramp-up of electric vehicles is introduced as well as intelligent charging strategies and a method to quantify grid reinforcement measures. Based on the market ramp-up scenario, the ability of intelligent charging strategies to prevent the need for grid reinforcement is examined. Depending on the structure of the examined grid area, the costs for a grid reinforcement are significantly reduced by applying the intelligent charging strategies proposed in this paper.


Implementation and Verification of V2G Control Schemes on Multiple Electric Vehicles
Submission-ID 288
Hidekuni Toda 1, Yutaka Ota 1, Tatsuhito Nakajima 1, Ken-ichi Kawabe 2, Akihiko Yokoyama 3
1 Tokyo City University, Japan
2 Tokyo Institute of Technology, Japan
3 The University of Tokyo, Japan
In Japan, the regulation market is scheduled to be launched in 2020, distributed generations and energy storages could participate to the market. Massive pure plug-in electric vehicles (PEV) would be on the road, the potential of the V2G is also dramatically increasing toward 2020.

We have developed some V2G control schemes through the HIL(Hardware In the Loop) tests using experimental batteries and stand-alone bi-directional inverters on control response, communication delay in the case of remote control, and power system frequency dynamics.

In this paper, the proposed V2G control schemes is implemented to the actual PEV and the V2G capable charging system as a first V2G system in Japan. Accuracy of the grid frequency and voltage measurements, response of the system, and communication capability, and so on, are verified on two different type PEV system. Effectiveness of the PEV-FFR(Fast Frequency Response) featuring quick response of the PEV and inverter system, PEV-LFC(Load Frequency Control) coordinating large-scale thermal generations, and combination control of the FFR and LFC dispatched to the multiple PEVs are evaluated. PEV-SIR(Synthetic Inertia Response), in which very quick system response in the frequency detection, control initiation, and physical responses is required, is also evaluated by the HIL test.

Overview of the HIL is as follows. The frequency fluctuations under massive PVs and PEVs integration are emulated by the power system real-time simulator (OPAL-RT Technology, OP5600). The power system model is based on a prefecture level with a population of about 9 million people. The power capacity of the PV is 20% of the total electricity demand at peak time, and the number of PEVs is 480,000, these values are target in 2030.

One PEV is Nissan LEAF(30[kWh]), the other is Nissan e-NV200(24[kWh]). These cars are connected to two different bi-directional power conditioners (Nichicon Corporation, NECST-TD1 & Mitsubishi Electric Corporation, SMART V2H System). It is possible to control charging / discharging of 3 [kW] by Nichicon’s one and 6 [kW] by Mitsubishi Electric’s one.

The frequency command value calculated by the real-time power system simulator is transmitted to the power amplifier (California Instruments, MX15, rated: 15 kVA). Then, the power amplifier outputs instantaneous voltages corresponding to the frequency deviations. The PEV controller (dSPACE, Micro Auto Box II) measures the frequency deviations and determines a charge / discharge power command to the PEV. Then the PEVs output the V2G power to the power amplifier via the PEV power conditioners. By feeding back V2G power measurements to the real-time simulator, the frequency fluctuations in the next step can be calculated in the real-time simulator. The FFR, LFC, and SIR control schemes are verified on the PEV and charger system.



Optimal e-mobility integration in hotels
Submission-ID 289
Jan von Appen 1, Jan Ringelstein 1, Christoph Nölle 1, Siwanand Misara 2
1 Fraunhofer IEE, Germany
2 Betterspace GmbH, Germany
E-mobility and digitalization pose new challenges for the tourism. While many hotels see e-mobility as an opportunity to expand their services, several obstacles have to be addressed. A minimum-cost charging infrastructure has to be set up in such a way that guests can enjoy the full e-mobility experience and grid-supporting charging processes are enabled. In particular, local energy management systems have to balance trade-offs between higher charging power for fast recharging and the avoidance of load peaks that come at high peak charges. Such a system must also allow for an easy guest communication and integrated billing with guests via existing ICT hotel infrastructure.

In this paper, we present an analysis how hotels can address these challenges by adopting optimized energy management strategies for electric vehicle (EV) charging. A model predictive control approach is presented that is uses a hotel load forecast and a mobility forecast. A mixed integer linear program is developed and implemented to derive optimal charging and discharging schedules for EVs. The approach models in detail current EV charging constraints, e.g. minimum charging power requirements. Load forecasts are derived using a seasonal ARIMA model. Mobility forecasts are based on data collected in an ongoing field test with 12 hotels.

The presented case studies discuss several price incentives, e.g. market-oriented prices, and evaluate benefits from vehicle to grid operation for load management in the hotel and flexibility provision for the grid. Potential trade-offs for hotels and grid operators are analyzed and indications what EV penetration levels will result in additional grid reinforcements are provided for different hotel types.



EV charging in workplace parking, observations and energy management
Submission-ID 291
Markku Peräniitty, Jiri Räsänen
Parking Energy Ltd, Finland
Parking Energy is deploying EV charging to large office buildings, public parking garages and apartment buildings, installing a cabling system which covers all or most of the parking area. The result has been accerelated acceptance of EVs in these locations, with estimates of 50% plug-in car share in 5 years. Parking Energy has collected experiences and data from these larger installations. The challenges in large buildings can be complicated, ranging from economics to availability of power. To be able deliver EV charging services in real estate market, the EV charging system in a building needs to be considered together with the building electrical system. At its simplest form, it can mean controlling the EV charging by real time metering of electrical supply of the building, extending to a smart building where large loads are considered.

One of the key questions in real estate is the economical effects to property owner, the tenants and the car drivers. The costs include the infrstructure such as cabling, the charging equipment, and energy and power costs, and possible upgrades to electrical supply. We looked at employee parking data collected from office sites and public garages mostly used for workplace parking, and looked at economical aspects as a whole. The costs are calculated both in base case where EV charging is used without any load management and with peak shaving with load management, including long term investment costs such as upgrades of electrical infrastructure. Further, we look at cost savings related to EVs, such as replacing ICE fuel costs with plug-in car electricity, and how it the economics work for all parties, including real estate owner, tenants, and EV charging service provider.

The important conclusion from the analysis is that when EV charging is made possible to all parking spaces in a cost-efficient way, plug-in cars become more popular, and the economics work, while at the same time reducing emissions.



Grid Integration Studies for eMobility Scenarios with Comparison of Probabilistic Charging Models to Simultaneity Factors
Submission-ID 293
Jan Ulffers 1, Alexander Scheidler 1, Christian Töbermann 1, Martin Braun 1, 2
1 Fraunhofer Institute for Energy Economics and Energy System Technology (IEE), Germany
2 Department of Energy Management and Power System Operation, University of Kassel, Germany
One major challenge of the mobility transition to Battery Electric Vehicles (BEVs) is the integration of charging infrastructure into distribution grids. The resulting increase in power demand can lead to overloadings and voltage band violations. A common method to estimate the simultaneous power demand of BEVs is the usage of simultaneity factors. This is a reasonable approach for a large number of vehicles. However it is questionable, how precise the results are for small numbers of vehicles - e.g. in low-voltage grid feeders.

In this paper we present a method for conducting grid integration studies in real integrated low- and medium-voltage grid models in the context of eMobility. A special focus is the comparison of a probabilistic distribution approach for BEV charging in low-voltage grids vs. the usage of simultaneity factors. The probabilistic method uses a pool of BEV charging profiles and places them randomly in an LV grid to derive worst-case situations. Necessary grid reinforcement and expansion as well as their cost are then estimated with an automated approach based on a heuristic optimization algorithm. Additionally we compare different charging scenarios like residential charging, public fast charging and dedicated grids for charging stations.

The results show, that the application of simultaneity factors can cause large deviations in regard to violations, as well as necessary grid reinforcement and expansion compared to the probabilistic approach. Especially local weak spots in LV feeders often cannot be identified when using common simultaneity factors for all BEVs in a low-voltage grid. This leads to a possible underestimation of reinforcement and expansion cost. Furthermore the cost of integrating charging infrastructure into the grid varies widely between the different scenarios considered.



A two-step coordinated EV charging method integrating distribution network constraints
Submission-ID 295
Olivier Beaude, Alban Jeandin, Julien Pennec
EDF (R&D), France
At the scale of Distribution Network (DN), scheduling the charging of Electric Vehicles (EV) must integrate local DN constraints and metrics, e.g. line capacity, voltage bounds. Given that the size of the considered setting is relatively small - typically with tens of EV, this leads to methodological and technical issues that are really different compared to high-scale problems, e.g. when using EV flexibility on electricity markets. In particular, at this small scale, forecasting errors made on input parameters of models to schedule EV load in a predictive setting (e.g. when EV is back home, for night charging) can be significant. Addressing this difficulty, the proposed approach consists in the two following steps, performed in order: 1) [Predictive optimization] before real-time, based on available forecasts, an iterative algorithm using game-theoretic principles is applied. It consists in sequentially solving individual EV problems, in which each individual house and DN constraints are approximated with simplified models (e.g. simple power limits depending on charging location instead of load-flow based methods for voltage constraint), that can be integrated in a Mixed-Integer Linear Programming problem. The coordination is ensured through the iterative update (at each iteration of algorithm) of a "coordination signal" calculated by an "aggregator" based on current decisions of individual EV. This algorithm eventually provides each EV with a charging profile offering a compromise between individual constraints and DN ones; 2) [Real-time regulation] in real-time, taking its optimal load profile (output of Step 1)) as a reference, each EV then applies heuristic rules to modify its effective charging decisions depending on two key elements: a) the realization of the main parameters of the models, that can be significantly different from their forecasted values; b) more accurate models for house and DN behaviour / constraints that can be integrated in these heuristic rules, while not possible in step 1) to get tractable optimization problems. These regulation rules also include a coordination logic between different EV, when individual regulation is not possible. Based on the real setting of Pecan Street database, "rule of thumbs" are proposed and tested for the calibration of this two-step approach. It provides a good approximation of real constraints of DN to be integrated into the algorithm of Step 1), depending on the scale of the problem (number of EV) and forecasting capability. The tradeoff between individual EV users' metrics (charging cost, contract power) and DN ones (Peak to Average Ratio, considered as a proxy for power losses, or the need of DN reinforcement) is measured, in comparison with reference charging scenarios: Plug-and-Charge, iterative Water-Filling. The proposed decentralized scheme is also compared to its centralized alternative: in addition with data-privacy, computational advantages are observed.


Real-Time Coordinated Charging for Plug-in Electric Vehicles to Mitigate Asset Overloading in Radial Distribution Networks: A Comparison of Implementations
Submission-ID 296
César García Veloso 1, Kalle Rauma 2, Julián Fernández 3, Christian Rehtanz 2
1 KTH Royal Institute of Technology UPC Polytechnic University of Catalonia, Sweden
2 TU Dortmund University, Germany
3 University of Victoria, Canada
Abstract:

The global proliferation of plug-in electric vehicles (PEV) poses a major a major challenge for operators of current and future distribution systems. If uncoordinated, the charging process of such a growing electrical fleet can lead to overloading of the main network’s assets, distribution transformers and head feeders, which may result in their overheating, deterioration, triggering of associated protections and their eventual risk of failure, compromising the stability and reliability of low voltage distribution networks. In order to mitigate the thermal impacts of uncontrolled domestic AC charging and to increase the housing capacity of PEVs in radial low voltage distribution systems, the present study compares the effectiveness and the performance of a centralized charging control algorithm based on three alternative optimization formulations that seek to minimize the total impact upon the car owners. A lineal, sequential quadratic and heuristic formulations of the optimization are suggested and compared in terms of the impact of the charging strategy on the end-user and the performance of the algorithm. The effectiveness of the proposed system is tested on a realistic simulation environment considering a residential low voltage grid facing a complete set of night charging episodes for incremental PEV penetrations levels. The network topology consists of 20 individual households fed by power underground cables and distributed among three main feeders where a maximum of 20 vehicles, modeled after the two commercially available and mass-produced cars, have been randomly assigned to the existing dwellings. Preliminary results reveal how a successful management of the network’s thermal constrains are obtained resulting in a minimal impact over the participating users under all three implementations. Considering the impact on the end-users the heuristic and linear formulations seem to result in lower values compared to those of the quadratic formulation.

Key Words:

Plug-in electric vehicles, Radial low voltage networks, Real-time control, Centralized thermal management, Active distribution networks, User impact minimization.

Clarfication:

The studied network only registers a minor overloading episode affecting its distribution transformer and thus solely some minimal differences between the three implementations can be seen. Further results will be obtained and will include, the comparison of the performance of the solution for each formulation in terms of computation time and optimality of the solution. Furthermore, more dramatic scenarios such us increasing the thermal limitations of the network or the existing base load will be explored in order to observe significant network violations and so clearer distinctions between the methodologies can be exposed.



Distributed Collaborative Algorithm for Energy and Load Management in Buildings
Submission-ID 303
Heikki Suonsivu, Sampo Kellomäki, Johannes Helander
Parking Energy Ltd, Finland
Urbanization makes it more likely that EVs are going to reside in large parking areas of apartment and office buildings. It has been shown that even limited amount of power can be used to charge EVs in apartment buildings and offices, as typical driving distances are limited and the parking times are often long, such as overnight or working day.

Traditional protocols and methods of load management do not scale for such building environment. A scalable method of doing energy management in EV charging is needed. We present a distributed collaborative algorithm which can implement energy and load management in presence of a large number of energy consumers and produces, as well as energy storage. The algorithm is based on collective situational awareness, including distribution of concerns amongst the components of the system, and is able to cope with an unreliable networking environment. We further present a domain specific mesh networking algorithm that allows the charging algorithm to perform better and/or under more demanding conditions than using previous standard meshing schemes.

The algorithm is based on each charging station exchanging information and trading resources such as capacity allocations between each other, typically over wireless network, avoiding single point of failure. We use radio broadcast domain to reduce transmission. For example, we first try to get a resource from local area, before resorting to a search further away. Locality allows very low latency, which allows charging stations to quickly react to increased power requirements. The algorithm is robust as it makes pessimistic assumptions until communications with peers confirms an action to be within available capacity.

The algorithm can work stand-alone, but its behaviour can be optimized by a cloud service which will pull in data from various sources, such as grid, weather services, and electricity markets. The cloud service can participate frequency markets through aggregators to allow large numbers of EVs to be used as part of smart grid, with minimum communication resources.

The algorithm was originally designed to be able handle very limited electrical infrastructure, such as block heater outlets present in Scandinavian countries, which often have power limits at 1kW or even less per parking space. However, the cloud-assisted capability to fine tune the power use and accommodate other loads in the building is valuable when developing EV charging services worldwide, as many existing buildings have very limited amount of power available, and the trend of introducing peak power based pricing will make peak shaving a commercial necessity. The system implements fairness as well as protecting the electrical system in addition to being smart grid and smart building capable.



Optimal Control in a Smart Grid Aggregator: Connecting PV, EV, Energy Storage, and Heating Systems to Solve the Power Problem.
Submission-ID 305
Jonathan Ridenour 1, Joachim Lindborg 2
1 Data Scientist, Ngenic AB, Sweden
2 Project Manager, Sustainable Innovation, Sweden
Optimal Control in a Smart Grid Aggregator: Connecting PV, EV, Energy Storage, and Heating Systems to Solve the Power Problem.

Abstract

The main challenge for many Distribution System Operators (DSOs) when it comes to the integration of Electric Vehicle (EV) charging on their grids is not a problem of energy but rather of power. Critical peak power (CPP), already a difficulty during winter months, is exacerbated by the increasing presence of EV charging stations as the use of electric mobility becomes widespread. As a result, DSOs are showing an increased demand for peak-shaving and peak-shifting technologies.

The project "Coordinating Power Control" ("Växlande Effektreglering" in Swedish, referred to as "VäxEl" in this paper), which began in January of 2017, is based on the increased interest of rural households for solar panels, home batteries, EVs and other "smart home" equipment. The ambition of the VäxEl project is to create a cost-effective optimization of a distribution grid by addressing various technical, regulatory, and psychological challenges.

By bringing together a community of market actors, including smart grid service providers, governmental regulatory bodies, research departments, and a local grid owner (DSO), VäxEl seeks to uncover and propose solutions to such challenges. In May of 2018, the International Smart Grid Action Network (ISGAN), a cooperation within the International Energy Agency (IEA), presented the VäxEl project with its prestigious Award of Excellence for world-leading activities in the area of smart grids for power flexibility.

Through partial funding provided by the Swedish Energy Agency and by assisting homeowners in applying for the economic assistance available to purchasers of EVs, home batteries, and solar arrays, VäxEl has been able to martial a formidable amount of power flexibility, including the installation of 500 connected water-based heating systems, 60 sites with rooftop solar panels (providing 200 kW of production), 36 kW of Electric vehicle charging, and 70 kWh of home energy storage (providing 60 kW of instant power flexibility).

This paper presents some of the progress made within the VäxEl project, primarily focusing on two key aspects: the modeling and design of an optimization algorithm for integrating the resources within the project for the purpose of reducing CPP, and the reduction in CPP achieved during February of 2018 by connected heating systems within the Upplands Energi electric grid.



The power grid is the backbone for e-mobility
Submission-ID 314
Salome Gonzalez Vazquez, Florian Regnery
Network Technology/Network Operation Forum in the VDE (VDE|FNN), Germany
The German power grid is a highly reliable infrastructure that will serve as the backbone for the integration of e-mobility. By 2020, as reported by the National Platform for Electric Mobility, 1 million electric vehicles will be on German roads and the charging infrastructure will be expanded to 70,000 public and 7,100 fast charging points. This will mean adding a significant load to the system that could lead to increased congestion in the networks. A well planned integration can avoid additional grid expansions as well as allow for a higher penetration of renewables through flexibility services. If the integration of e-mobility is thoroughly planned from the start, it can generate added value for all parties in the grid and contribute to the energy transition.

E-mobility creates new and mobile volatile loads and feeds that will place an additional load on the grid and could require a large investment in network expansion. This makes e-mobility an important driver for forward-looking development of the grid in addition to the energy transition and the implementation of the European Single Market. Like other network users, e-mobility should also contribute to the provision of system services such as balancing power, frequency maintenance and reactive power supply. Smart charging is one of the key capabilities of e-mobility to provide flexibility, for example, by using electric vehicles as temporal energy storage that can feed energy back into the energy system when required.

The integration of e-mobility will occur mostly at low-voltage level. To avoid their overload, charging stations with capacities of 350 kW and over should be connected to the medium or higher voltage grids. If connection is only possible to the low-voltage grid, this type of charging stations should be combined with energy storage. In addition, three-phase charging system are preferred to avoid voltage imbalances in the network at every level. Market incentives or support programs should be based on three-phase charging.

A planning corridor is necessary for the ramp-up of e-mobility. An increasing number of electric vehicles translate into a greater likelihood of simultaneous charging that could cause bottlenecks in the network. Market-driven charging processes can lead to mass effects and create peaks of demand. As found by the meta-study commissioned by VDE|FNN and BDEW, grid-focused charging control is more efficient than market-led charging. Market signals must therefore be coupled with network-relevant parameters to find the most cost-efficient solution.

This paper summarizes current network conditions in Germany, explains the effects on the power grids and outlines the necessary next steps to facilitate e-mobility integration. Key findings from the meta-study commissioned by VDE|FNN and BDEW also provide a description of the critical factors for the integration of e-mobility and offer suggestions for future research.



Electric Vehicles as a Variation Management Strategy – Representing Individual Driving Patterns in Energy System Modeling
Submission-ID 318
Maria Taljegard, Viktor Johansson, Lisa Göransson, Mikael Odenberger, Filip Johnsson
Chalmers University of Technology, Sweden
This study investigates an optimised charging of passenger electric vehicles (EV), including vehicle-to-grid, as a complement or substitute to other variation management strategies (VMS), e.g., stationary batteries, demand-side management in households, hydrogen storage and cycling of thermal power plants. A cost-minimisation model of the electricity system that is designed to analyse transformation of the electricity system to meet CO2 emission target has been applied. Further, this study takes initial steps to implement GPS measurements of individual car’s movement in the model in order to better represent the spread in the individual driving patterns and thereby reduce the risk of overestimating the EV battery storage potential. The study is carried out for four regions that have large differences in hydro, wind and solar resources (Sweden, Spain, Hungary and Ireland). This study shows that individual driving profiles are very important when modeling EVs in electricity system models, since each driving profile are charged and discharged back to grid very differently. The results also shows that EV batteries can replace stationary batteries in order to handle the day-night time solar variations in Spain. In Ireland with good wind conditions and no hydro power, hydrogen long-term storage becomes important in the scenario without EVs to handle wind variations and minimize total system cost. In the scenario with V2G and a battery size of 30 kWh, part of the EV fleet could provide enough storage for several days in order to handle wind variations, while at the same time full filling their individual driving demands (see Figure 1). A sensitivity analysis has been done for each individual driving profile to also investigate (i) the importance of charging infrastructure outside the home location in order to handle solar and wind variations with EV batteries, and (ii) the cost for cycling EV batteries.


Grid Load Relief by Smart Charging of Electric Vehicles
Submission-ID 323
Thorsten Schlösser 1, Eckehard E. Tröster 1, T. Kurpat 2
1 Energynautics GmbH, Germany
2 RWTH Aachen, Germany
This paper analyzes a possibility to reduce the grid impact of electric vehicles (EV) by curtailing the charging power in case of necessity. The focus lies on the development of a decentralized charging algorithm with minimum communication needs. The only communication needed is uni-directional communication to broadcast the current transformer status. The goal is to evaluate if the local voltage at the charging station is a sufficient indicator to keep the grid within its operation boundaries instead of supplying every charging station with the minimum voltage of the corresponding power line, which would result in high communication needs. To reduce the impact of the local voltage an urgency-factor is included as a further input parameter. It determines how close the vehicles are to the departure time and increases the charging power in case of insufficient charge. The proposed charging is based on a fuzzy controller. It converts the described input parameters into a change of charging power via a predefined control matrix. In the first step, the input values are transferred into fuzzy-areas and thereafter interpreted by the inference engine. In a final step, the results of the inference engine are transformed into a change of charging power by the point of gravity method. Additionally to the fuzzy controller it is assumed that the vehicles are able to support the grid voltage by changing the powerfactor between 0.9 underexcited and 0.9 overexcited alongside a cos(f)(U)- curve. Deterministic models for the active load of households, heat pump and photovoltaic systems were introduced in a previous paper. The existing model is advanced by including reactive power dependencies, car classes and more realistic charging behavior of EV-owners. The functionality of the charging algorithm is tested under difficult grid conditions. A low voltage grid with long power lines and a relatively small transformer in an urban environment is chosen. At first it is shown that the grid can be kept stable even at maximum EV-penetration without causing limitations for the vehicle owners. In a second evaluation the grid is further burdened with heat pumps close to the point of the minimum voltage level even before including EV’s. In this case the charging algorithm is not able to keep the voltage above the voltage threshold because only local voltage measurements are considered. Bi-directional communications could solve the problem but grid expansion should be the preferred method at this point because average EV-charging power is below 23% of its nominal value. Lastly the impact of additional photovoltaic (PV) systems in the grid is evaluated. It can be concluded that photovoltaic systems are not able to prevent grid expansion caused by increasing load from heat pumps and electric vehicles, due to the volatility of the technology.


Probabilistic Modelling of Charging Profiles in Low Voltage Networks
Submission-ID 324
Thorsten Schlößer 1, Eckehard Tröster 1
1 Energynautics GmbH, Germany
2 RWTH Aachen, Germany
This paper analyzes possibilities to create deterministic driving profiles from mobility survey data provided by the German government. Main objectives are to determine (a) the periods when the car is at home and (b) the driving distance and thus the amount of energy necessary to fully recharge the car. For this, the main challenge is to split the data into trips ”departing from” and trips ”returning to” home. This is achieved via the Monte-Carlo-Method under the key assumption that cars are at home early in the morning. The resulting journeys are grouped into daily driving profiles and then travel times and annual distance driven are validated by comparison with the original data. Furthermore, to evaluate the grid impact, a simultaneity factor is introduced assuming that the cars are charged immediately after each journey. The factor describes the percentage of electric vehicles charging at any given time. The maximum simultaneity is found late evening with a steady decrease into the night. An increase in charging power leads to a decrease in simultaneity. However when considering small grids the results become less predictable. Safety margins to keep necessary confidence intervals have to be included. Besides electric vehicle charging, other factors which influence residential low voltage grids are household loads, photovoltaic systems and heat pumps. An already existing model of the University of Loughborough is expanded to consider interdependencies between factors affecting grid loads, such as correlations between driving profiles and household loads. The relative timedependent impact of each technology is shown and the importance of probabilistic modeling in small grids is evaluated. Large safety margins or load shifting through intelligent charging algorithms is needed to keep small grids inside operation boundaries.


Opportunities of the New Energy Vehicles Fueling Station (NEFUSTA) project
Submission-ID 337
,
TBA


Opportunities of the New Energy Vehicles Fueling Station (NEFUSTA) project xx
Submission-ID 344
Florian Verhaak, Novy Francis
DNV GL Netherlands B.V., Netherlands
TBA