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Plug-In Electric Vehicles Automated Charging Control A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Dallinger, David; Kohrs, Robert; Mierau, Michael; Marwitz, Simon; Wesche, Julius Working Paper Plug-in electric vehicles automated charging control Working Paper Sustainability and Innovation, No. S4/2015 Provided in Cooperation with: Fraunhofer Institute for Systems and Innovation Research ISI Suggested Citation: Dallinger, David; Kohrs, Robert; Mierau, Michael; Marwitz, Simon; Wesche, Julius (2015) : Plug-in electric vehicles automated charging control, Working Paper Sustainability and Innovation, No. S4/2015, Fraunhofer-Institut für System- und Innovationsforschung ISI, Karlsruhe, http://nbn-resolving.de/urn:nbn:de:0011-n-3279201 This Version is available at: http://hdl.handle.net/10419/107069 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. www.econstor.eu Working Paper Sustainability and Innovation No. S 04/2015 David Dallinger Robert Kohrs Michael Mierau Simon Marwitz Julius Wesche Plug-in electric vehicles automated charging control Abstract This paper examines how plug-in electric vehicles can be managed to balance the fluctuation of renewable electricity sources. In this context, different control strategies are introduced. To investigate indirect control via electricity tariffs, an electricity market analysis is conducted of a system with a high share of genera- tion from renewable electricity sources. The analysis uses driving data collected from battery electric and plug-in hybrid vehicles in a research project which means that real charging and driving behavior can be considered. The results show that it is difficult to implement smart charging based on economic argu- ments because the incentives from day-ahead electricity markets are relatively small. In addition, a novel, autonomous control approach is discussed for plug- in electric vehicles. While measuring the voltage at the grid connection point, plug-in electric vehicles are able to fully independently generate operation schedules that can avoid load peaks and integrate fluctuating power outputs from distributed renewable generation sources. The results reveal that combining indirect, price-based control to consider the system level with autonomous voltage-based control to consider the situation in distribution grids is a very promising control approach that allows electric vehicles to benefit from sustainable renewable generation and avoids load peaks due to simultaneous charging. Table of Contents Page 1 Introduction .......................................................................................................... 1 1.1 Background .............................................................................................. 1 1.2 The iZEUS Project ................................................................................... 2 1.3 Objective and procedure .......................................................................... 2 2 Charging control methods .................................................................................. 3 2.1 Direct control ............................................................................................ 3 2.2 Indirect control ......................................................................................... 4 2.3 Autonomous distributed control ................................................................ 5 2.4 Discussion ............................................................................................... 6 3 Driving and charging behavior ........................................................................... 7 3.1 iZEUS test fleet ........................................................................................ 8 3.2 Driving data evaluation ............................................................................. 9 3.3 Charging behavior .................................................................................. 11 3.4 Discussion ............................................................................................. 14 4 Simulation of charging control ......................................................................... 15 4.1 Method ................................................................................................... 15 4.1.1 Indirect control ....................................................................................... 16 4.1.2 Autonomous distributed control .............................................................. 17 4.2 Scenario ................................................................................................. 20 4.2.1 Electricity system ................................................................................... 21 4.2.2 Grid simulation ....................................................................................... 22 5 Results ............................................................................................................... 23 5.1 Indirect price-based control – a consumer survey .................................. 23 5.2 Energy system analysis ......................................................................... 25 5.2.1 Smart charging savings .......................................................................... 26 5.2.2 Vehicle-to-grid savings ........................................................................... 27 5.3 Prototype development and demonstration ............................................ 28 5.3.1 Metering Board ...................................................................................... 29 5.3.2 Controller Architecture ........................................................................... 30 5.3.3 Automotive Integration ........................................................................... 30 5.3.4 Demonstration ........................................................................................ 30 5.4 Grid impact analysis ............................................................................... 33 6 Conclusions ....................................................................................................... 35 7 References ......................................................................................................... 37 Plug-in electric vehicles automated charging control 1 1 Introduction This section provides the background to the research objective of studying the role of electric vehicles in a modern electricity system and introduces the re- search project in which large parts of this work were conducted. 1.1 Background Plug-in electric vehicles (PEVs) are a promising option to increase efficiency in the transport sector, if these vehicles are powered with electricity generated by renewable energy sources (RES). In theory, using RES to power vehicles is a win-win situation. PEVs are ideal RES consumers because of their high electricity-to-wheel efficiency compared to fuel cell vehicles or those based on liquefying RES. RES installations benefit from PEV demand that could boost RES expansion. In practice, this interaction is more complex because the most promising RES – photovoltaic and wind energy – are fluctuating sources. The value that needs to be considered when combining renewable generation and PEVs is not the amount of energy available (in kWh) but rather the amount of power available (in kW) . The far-reaching changes fluctuating generation will bring to modern electricity systems are illustrated in Figure 1. Figure 1: Example of the possible residual load situation for 3 weeks in sum- mer, Germany, 2030 The diagram shows the fluctuating generation, the system load and the resulting residual load for an example scenario reflecting a likely situation in Germany in 2030. The residual load fluctuation for these three weeks in sum- 2 Plug-in electric vehicles automated charging control mer is mainly caused by the high installed photovoltaic capacity. Compared to the system load, huge ramp rates can be observed and, for some hours, the generation from fluctuating sources even surpasses the system load demand (negative residual load). PEVs are able to balance the increasing fluctuation of the residual load by pro- viding flexible charging loads and vehicle-to-grid services (V2G). This makes it possible to integrate RES into the energy system. To achieve this win-win situa- tion, it is necessary to develop flexible control strategies that are able to mana- ge the rapid changes in electricity systems with high RES shares. 1.2 The iZEUS Project The
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