E-Mobility Integration Symposium 2018
Mitigation of the impacts of EV inclusion into electricity markets through Demand Aggregators
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.
Impact of increasing E-mobility on a distribution grid at the medium voltage level
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”  and weather data from the Austrian Zentralanstalt für Meteorologie und Geodynamik (ZAMG) .
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.
- Amt der Steiermärkischen Landesregierung, „Solardachkataster Steiermark“, http://www.gis.steiermark.at/cms/beitrag/11864478/73081691/
- ZAMG, Einstrahlungsmessdaten und Temperaturmesswerte des Jahres 2014 für Kapfenberg
Electric Vehicle CPMS and Secondary Substation Management
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
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
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
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
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.
Optimized charging of electrical vehicles based on the Day-Ahead Auction and continuous Intraday market
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.
Research Campus Mobility2Grid: From Lab to Reality
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
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.
Comparison of electromobility-impacts on the low-voltage level in different grid regions
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
Impact Assessment of Integrating Novel Battery Trolleybuses, PV Units and EV Charging Stations in a DC Trolleybus Network
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
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
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
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
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
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
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
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
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
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
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
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.
Evaluation of Modular Infrastructure Concepts for Large-Scaled Electric Bus Depots
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.
Hot-spot Scenarios of Electrical-Vehicles on the Low Voltage Grid including Statistics and Effect of decentralized Battery Storage
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.
Smart Integration of Photovoltaics, Vehicle Charging, and Battery Storage in a Household
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
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
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
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.
Autonomous Voltage and Frequency Control by Smart Inverters of Photovoltaic Generation and Electric Vehicle
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.
Scenario-driven Analysis of Intelligent Charging Strategies Caused by the Market Ramp-up of Electric Vehicles
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
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.
Grid Integration Studies for eMobility Scenarios with Comparison of Probabilistic Charging Models to Simultaneity Factors
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.
Optimal Control in a Smart Grid Aggregator: Connecting PV, EV, Energy Storage, and Heating Systems to Solve the Power Problem.
Optimal Control in a Smart Grid Aggregator: Connecting PV, EV, Energy Storage, and Heating Systems to Solve the Power Problem.
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
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.
Grid Load Relief by Smart Charging of Electric Vehicles
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
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.