Introduction
Due to the German government’s policies electric vehicles (EV) will significantly gain popularity and market share over the next few years. Great potential for electromobility exists especially in suburban areas, where a full-scale development of so-called electromobility-hotspots is most feasible. The immediate consequence of such transformation may lead to a considerable surge in power consumption and a significantly higher loading of the suburban’s low voltage grid. Any inhomogeneous distribution of EV within the grid will further increase the load locally. In order to increase the number of EV that can be integrated into the electricity grid, it is necessary to further expand the low voltage grid. The method applied to ensure cost effectiveness and a sparing use of resources when it comes to grid expansion, is referred to as the NOVA principle.
Methodology
Within the scope of this article, quasi-dynamic simulations using DigSilent PowerFactory are carried out to analyze the impact of the increasing penetration of EV in reference grids for suburban areas. In addition, the effectivity of the NOVA principle to increase the grid capacity is examined.
The grid planning principle NOVA is derived from German renewable energy law and describes a cost-progressive process for upgrading existing electricity grids. Applying NOVA to a grid extension project means primarily consider possible grid optimization, then technical grid reinforcement and finally as a last measure grid expansion.
Two grids which are synthesized from real networks forming a typical and an extreme reference grid (ERG) for suburban areas serving as a basis for the investigations. The parameter constellation of the ERG is selected so that within 95 % of the existing suburban low voltage grids in Germany the equipment loads and voltage ratios are at least equal or better than in the ERG. Other than that, the extreme grid scenario has one significantly longer grid string, also containing a high number of households which indicates high inhomogeneity in the load distribution.
Within the scope of grid reinforcement adjustable local grid transformers are considered. In addition, line voltage regulators and parallel lines are considered. In the context of the grid expansion, replacement and larger dimensioning of local grid transformers and construction of new power lines are considered. Furthermore, in terms of the technical solutions for voltage control, voltage dependent and load-flow dependent control types are considered.
First Results
In ERG, the transmission capacity is limited by line overloading and under voltage problems. Therefore, parallel lines should be used to increase the thermal limit current as well as lower the voltage drop. In typical reference grids, the most effective option to grow the number of EV is by using a voltage regulation transformer as the undervoltage problem is dominant and limits the transmission capacity.
Automobile is the biggest oil products consuming sector in Japan and to shift from ICE (Internal Combustion Engine) to EV is necessary to meet 80% carbon abatement target. On the other hand, the popularisation of EV will increase electricity demand which leads to the burden of electricity grid and constitute limiting factor to increase the share of renewable energy. However, if the charging patter of EV are done in an optical manner, the huge capacity of EV battery will play as a storage system to absorb the high share of intermittent renewable energy.
In this study, we have employed energy TIMES-based Japan energy technology model with grid features and done two simulations, no optimisation and optimisation, to identify the benefits of EV charging pattern optimisation to meet 80% carbon mitigation target
Without the optimisation of EV charging patter, the share of EV electricity consumption in total electricity consumption is 9.6% in 2050, but in certain time-period, April evening, is 36.4%. As a result, PV curtailment occur in day-time. Electricity price will be 22.0 JPY/kWh in 2050. If we optimise the charging patter of EV, the electricity price will be 17.7JPY/kWh in 2050, which is 20.0% cheaper than no optimisation case.
Optimisation of EV charging patter will make to increase the share of renewable energy cheaper and more affordable cost burden.
This study was based on supraharmonic current and voltage measurements of four different electric vehicles connected to the grid. As a comparison the same measurement was carried out on a full-converter wind turbine. The data have been calculated and analyzed according to the IEC 61000-4-30, IEC 61000-4-7 and IEC 61400-21-1 requirements. One result is that that the wind turbine injected significantly less supraharmonics into the grid compared to the electric vehicles’ charging systems. The frequency of the supraharmonics depends on the switching frequency of the power electronics used in each of the vehicles’ charging systems.
The growing number of battery electric vehicles and plug-in hybrid electric vehicles brings the need of more fast charging stations across cities and highway stops. This charging stations toned to be connected to the electrical grid via existent facilities, can cause constraints such as power availability.
This work brings an approach for the planning and operation of such energy hubs by coping with this challenge by deploying a Battery-based Energy Storage System (BESS). With the BESS integration, it is expected to minimize utilization and overall energy costs, preventing infrastructure upgrades, and enhancing the integration of renewable energy resources.
This approach sizes a stationary energy storage system with lithium-ion technology batteries through a co-optimization of the planning and operation stages, integrated in an electrical installation that will implement fast charging stations. This sizing is a result of an optimization based on the interior point algorithm, where the objective is to minimize the total operating costs of a fast charging station, including the maintenance, operation and installation, while properly modelling the different resources such as the BESS, the charging station and EV charging and PV generation.
In order to have an estimate of necessary power and energy consumption, a simulated frequency of parking of BEVs at the charging stations, based on probabilities, was modelled taking in account the distance that a battery electric vehicle will do in a certain period of time and the probability of being a car with a particular set of characteristics.
Keywords – Battery Energy Storage System; Fast Charging Stations; Battery Electric Vehicle
Public transport and private electric vehicles are most likely the first sectors to enter the electricity grids with high vehicle volumes. Both groups come with challenges and new possibilities for the grid integration. An important issue is how well the electricity demand is predicted in time and location. Battery electric buses allow scheduled charging times but with high power peaks. Based on energy system simulations, we find that stationary battery system and vehicle/charging management are solutions to offer flexibility. The charging behavior of private cars are very hard to predict. Based on mobility behavior energy demands and charging location are estimated. With the ramp-up of electric cars the amount and distribution of charging events is a challenge for the low and medium voltage grid. Our research shows that flexibility is provided with user initiated charging management as well as grid or market controlled charging processes. With intelligent digital solutions and good planning of charging infrastructure a successful grid integration is possible.
Due to various drivers like climate and clean air policies, worldwide, the share of electric vehicles in the total fleet will dramatically increase during the next decades. The combination of growing e-mobility, decarbonisation and power system transformation represents a major challenge for planning of distribution networks (medium and low voltage). The required investments for implementing an adequate charging infrastructure potentially are huge. Simultaneously, they are highly uncertain because planning horizons in network development cover decades. How to avoid stranded investments? And how to avoid that lacking charging infrastructure becomes the bottleneck for new transportation technologies?
The paper presents results of a comprehensive scenario study looking at Germany up to 2050. The scenarios modelled the interdependency of different assumptions for market penetration of EVs, growth of renewables in distribution networks, geographic distribution, mobility and charging patterns. An important parameter during modelling was the possibility to influence charging and other loads in case of network congestion.
The study quantified the demand for network expansion and reinforcement as well as associated investments at a detailed level. The analysis distinguished network categories (rural, sub-urban und urban) and geographic profiles for renewables and mobility.
Key outcomes of the analysis were: charging strategies supporting a dynamic utilisation of the existing network capacity, massively reduce required investments. Such a charging management affects only short periods and negligible amounts of energy. Also, the modal split of transportation has a huge impact. The results showed that transformation of mobility is more than replacing combustion engines by batteries and electric drives – also in a network infrastructure perspective.
The paper / presentation will summarise key recommendations derived for policy makers.
The work has been performed on behalf of and in collaboration with Agora Verkehrswende, Agora Energiewende und Regulatory Assistance Project (RAP).
The acceleration of electric vehicle adoption increases the need of a charging infrastructure. Although most drivers may have the possibility to charge at home during the night, ride hailing vehicles (such as taxis) would need to access to fast charging station during the day in cities. Indeed, their distance driven per day is high and the stopover to charge must be as short as possible to limit its impact on their activity.
However, conventional fast charging stations face several limitations. First the investment cost is high, due to the powerful power converters needed. Moreover, the distribution grid must be upgraded to be able to provide the required power without overloading the MV/LV transformer and/or creating voltage imbalance on the network. Finally, the additional peaks in power demand could have a negative impact on the grid stability and limit renewable power penetration.
This paper presents a novel fast charging infrastructure based on the vehicle-to-vehicle (V2V) energy transfer from a fleet of one-way carsharing electric vehicles (CEV) towards private electric vehicles (PEV) in the need for a fast recharge. This infrastructure has several benefits: first, the transfer is “off-grid” so the V2V system does not need additional connection and reinforcement of the local network. Moreover, it can create an additional profit to the carsharing system when the vehicles are parked at the charging stations.
Using public data from the city of Paris, from the previous carsharing service Autolib© and from the French distribution service operator, the contribution of this paper is the following:
With the focus of governments on clean air and protection of the environment, using Electric Vehicles (EVs) is an effective candidate and solution for most cities to reduced their air pollution. The market penetration of a large number of EVs requires improving the existing power management systems and developing new methods to manage the EVs charging system. Increasing the number of EV users leads to enhanced charging stations and, consequently, a high demand for charging power. A high power demand causes stress and fluctuations in the power grid. Hence, an effective Demand
Side Management (DSM) method is required. This paper is regarding the project ELBE - Electrify Buildings for EVs that aims to install up to 7400 new charging points in the City of Hamburg. An interface based on the communication system between and Distribution Grid Operators (DSO) and ChargePoint Operators (CPO) to use for the DSM has been developed, which always guarantees a 3.2kW charging power for the EVs. The developed communication system and also the conformance test of the communication links between DSO, CPO, charging station and EV corresponding to different test scenarios, are presented in this paper.
With the growing number of EVs and EVs types in the market, charge point operators require tools to achieve and ensure operational excellence, and to ensure the reliability and robustness of the charging network. Based on real data, this paper presents a probabilistic method for the assessment of the operational performance of charging assets needed for a scalable and robust operation. This allows charge point operators (CPOs) to monitor the performance of their assets and identify the most probable root cause for issues.
Public electric vehicle (EV) charging infrastructure is a relatively new asset in infrastructure development and management. However, the demand for electric vehicle charginginfrastructure is expected to show accelerated growth in the near future, as mass-production and sales of electric vehicles are ramping up, driven by environmental concerns and sustainable policies. Like fuel stations and automated teller machines (ATMs), electric vehicle charging stations differ from traditional infrastructure, e.g. roads, bridges, buildings, etc., in that not only they include an interactive user interface (HMI) but also are connected to a monitoring and management system, a so called back-end. This management system or CSMS (charging station management system) provides the end-user with functionalities such as authorization, operation monitoring and invoicing. However, what really sets charging infrastructure apart, is the level of control and observability required for a successful transaction. Any charging transaction includes multiple stakeholder that need to exchange real-time information through different means and/or protocols. This is illustrated in Figure 1. Perhaps the most similar set of assets to EV chargingstations are fuel stations. Both provide energy to power a vehicle, at a price set by the operator for which the driver can pay in multiple ways. However, an ICE (internal combustion engine) car does not need to communicate on a real-time basis with the fuel station. Whereas dispensing gasoline is the same for each vehicle (put the nozzle in and pump the fuel in), this is a more delicate process for electric vehicle charging. This is due to how the energy is stored in an electric vehicle, in a battery. Charging a battery is a process that requires careful management of current delivered to each individual cell, to ensure all cells are fully charged whilst none are being overcharged with a current that exceeds its limits (which could result in cell death, and possibly premature battery failure). This results in a complexity due to the different builds/manufacturers of battery packs as each battery pack will have its own characteristics on how to charge it safely without destroying cells. In IEC61851-1 and ISO 15118 the process of charging is further detailed and indeed shows that the vehicle is the determining factor in setting the maximum power to be delivered to the vehicle at any time during the charging process. We can thus conclude that each vehicle model (or at least, each battery pack model) has its own characteristics to how it needs to be charged which has a different impact on each charging station and connected grid. Thus, the reliability of any charging solution, measured by the successful charging transactions, will depend on the correct functioning of all the interlinked parts. We can further extend this overview by defining all individual components that are required to provide power to the end-user. From the initial mating of end-user’ vehicle with charging station up to the invoicing of the end-user for the received energy. It is crucial to understand the total performance of all these interlinked parts.
The electrification of transport in Europe is in the ramp-up stages of a market transformation
that has the potential to significantly cut emissions in both the transportation and energy sectors,
while generating wider benefits for society. The research underpinning this study finds that the
greatest value from integrating electric vehicles (EVs) into the power grid can be generated by
charging them when and where it is most beneficial for the power system, while ensuring
consumers’ mobility needs are met at an affordable cost. An emerging body of research on electric
vehicle grid integration focuses on modeling the cost of integration under various scenarios, but few
studies look at the existing promising practices that are based on policy tools in use today. The
authors of this study conducted a qualitative review of policies for EV grid integration in the EU
and U.S. markets. We found that, in order to unlock the environmental and economic opportunities
associated with market uptake, three policy strategies are most effective: cost-reflective pricing,
intelligent technology, and integrated infrastructure planning. The study also explores the
implications of these practices for policymakers and regulators in the EU.