Assessment of the Impact of Electric Vehicles on Iberian Day-ahead Electricity Market P. Olivella-Rosell, G. Bosch-Llufriu, R. Villafafila-Robles, D. Heredero-Peris Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya BarcelonaTech, EUE Tècnica Industrial de Barcelona, C. Comte d’Urgell, 187 - 08036 Barcelona, Spain pol.olivella@ citcea.upc.edu Mario Kovačević Faculty of Electrical Engineering University of Osijek, Croatia mario.kovaa@gmail.com Niels Leemput Electrical energy & computer architectures (ESAT/ELECTA) KU Leuven, Leuven, Belgium niels.leemput@esat.kuleuven.be Abstract— Electric vehicles (EVs) could become a controllable grid load by using demand side management techniques, but this requires an information and communications technology (ICT) infrastructure and aggregator agents, to coordinate the EV charging process. To determine the opportunity cost of aggregators, it is necessary to analyze the extra charges in the electricity market, due to the EV charging demand. The EV energy consumption is modeled following agent-based techniques, and the data used corresponds to the Iberian day-ahead market and Spanish mobility needs in 2012. The simulation results show that EVs would significantly influence the electricity price on the day-ahead market, depending on the EV charging behavior. Keywords— Electric vehicles, day-ahead market, demand side management, EV demand I. INTRODUCTION The transportation sector is responsible for around a quarter of EU greenhouse gas emissions, and amount of emissions from transportation have increased with 36% between 1990 and 2007 [1]. Demand for transportation fuels will continue to increase along with carbon dioxide emissions, unless there is a shift in the transportation sector. Most of the EU member states are now establishing clear deployment goals for increasing and stimulating a larger penetration of EVs which include plug-in hybrid electric vehicles (PHEVs), battery electric vehicles (BEVs), and fuel-cell electric vehicles (FCEVs). Wide use of EVs will have an impact on electricity loads and could accelerate the overstretching of the power system, if steps are not taken to prevent this. Big amounts of EVs would add a considerable amount of additional load on the power system if the charging of EVs is uncontrolled, as the start of the uncontrolled charging process at home would coincide with the residential evening peak load. With controlled charging, this influence can be decreased by shifting the charging to times when the consumption is low [2] – [5]. Some papers showed that a penetration of 30% EVs is possible without any significant impact on distribution networks, if some form of coordinated charging is implemented [6]. Charging of EVs is more flexible than traditional loads, because the majority of EVs is driving a relatively low distance and is standing still for a significantly long time, typically overnight [6]. To utilize this flexibility, appropriate algorithms for charging control and management can and must be designed [8]-[10]. This control will be performed by EVs aggregators which will offer new financial contracts specific for aggregated EVs loads. Smart grid technologies and demand side management (DSM) have been proposed as a technical solution to make demand more flexible and able to adapt to power generation and increase system efficiency, stability and reliability. DSM has been regarded as one of the most effective and efficient ways to solve problems associated with renewable energy integration into power system [11]. Shifting of load in certain optimal ways can contribute to various goals such as peak shaving and valley filling [7]. Responsive loads are one part of a DSM approach, which can offer different incentives and benefits to consumers in response to their flexibility, i.e. demand response (DR) [12]. DR is a cost effective technique and can be achieved by either price based or incentive based programs [8]. The power grid has limited storage capabilities, so electricity generation and transmission must be continuously managed to match fluctuating demand [13]. Conventionally, this balance is maintained by power plants that remain on stand-by, ready to respond at desirable moment. DR programs can change consumption behavior by shifting loads to off-peak periods and participate in balancing of demand and supply [14]. Albadi and El-Saadany presented an overview of new flexible resources and defined DR programs and how electricity consumers can participate in those programs [13]. Others provided an overview of the evolution of the DR program and analysis of current opportunities [15]. Cappers et al. summarized the contribution of DR resources in the U.S., with the focus on performance of incentive-based DR programs in organized markets [16]. Kim and Shcherbakova examined central structural and behavioral obstacles to success of DR programs and defined some potential solutions which could greatly improve the functionality and success in the future [17]. Ma and Alcadi 978-1-4799-6075-0/14/$31.00 ©2014 IEEE