Integration of Renewable Energy Generation with EV Charging Strategies to Optimize Grid Load Balancing Rui Freire, Joaquim Delgado, João M. Santos and Aníbal T. de Almeida, Senior Member, IEEE Abstract - In this paper we will discuss three different Electric Vehicle Charging Strategies known as Dumb Charge, Smart Charge and Vehicle To Grid (V2G); as well as their impacts on the Portuguese Electric Transmission Grid for a 100% Electric Vehicle Fleet scenario. The future interaction between V2G and the large-scale penetration Renewable Resources will also be analyzed. I. INTRODUCTION A large portion of the electricity produced today is based on non-renewable resources like Coal, Natural Gas, Oil and Uranium. The fossil resources, as we know, contribute to the amount of carbon dioxide in the atmosphere. Adding to this, we have the transportation sector supported 98% by Internal Combustion Engines (ICE) [1], mostly using oil derived fuels and so responsible for more carbon dioxide emissions. Fortunately renewable sources like hydroelectric, wind, solar, geothermal, biomass and wave power are playing an increasing role in both electric energy production and transportation sectors. After nearly a century of hibernation, the automobile industry is returning to the process of electrification. Motivated by the increasing awareness of oil depletion and climate change, the electric vehicle (EV) sector is currently developing rapidly with new players entering the scene and with the traditional industry actively developing new models. The use of Plug-In charging without any constraint (Dumb Charge) leads to a large number of electric vehicles connected the grid nearly at the same time. This will may cause a peak demand that the grid cannot support. A controlled strategy of charging, the so called smart charge, is therefore needed to permanently adjust the demand to the available power. This procedure will be discussed in the next section. However, with the proliferation of electric vehicles (EV´s) in the market another charging strategy might be considered. Because the most significant renewable sources, like wind and solar, are intermittent, V2G might contribute as a powerful mechanism to integrate this type of production, see Section 3. II. EV´s PENETRATION AND CONSUME Taking account the number of light vehicles of the last years [2], we develop , with Matlab´s Toolbox curve fitting, equation (1) which gives the estimated number of light vehicles for next years. Whereas: N - estimated number of light vehicles x - year ( > 2000) From (1) we obtain a the portuguese fleet that consists of 4.700.000 light vehicles by the end of 2010. Assuming a 10% EV´s penetration in the Portuguese market, which corresponds to 470.000 EV´s, and also assuming an average daily distance traveled of 50 km per vehicle as well as an average consume of 200 Wh/km per vehicle, then we have 200x50x365x470.000 = 1,72 TWh consumed per year. This corresponds to 3,43% of the Portuguese total actual electricity consume per year (aprox. 50 TWh). For other EV´s penetration scenarios you might see the following table. TABLE I EVs PENETRATION AND CONSUMES EVs Penetration Number of EVs Increased Energy EVs Consume per year 10% 470.000 3,43% 1,72 TWh 25% 1.175.000 8,6% 4,29 TWh 50% 2.350.000 17,2% 8,6 TWh 75% 3.525.000 25,7% 13 TWh 100% 4.700.000 34.3% 17,2 TWh Considering that the Portuguese fleet light vehicles will not increase more than 5.000.000 vehicles in the next decades, and considering the improvement in the efficiency of the Electric Power Drive Systems, the maximum increased consume will not be greater than 36,5%. This increase will be gradual and it will expand simultaneously with the future exploration of renewable sources. In fact, for a 25% EV´s penetration, the extra energy needed is lesser than 2009 wind production of 7.44 TWh [3]. Anyway there are concerns, that should be taking into account, when we plug an entire fleet of electric vehicles to the grid. As will see on the fourth chapter, plug in an 100% EV´s fleet (worst case scenario), could lead to high peaks of demand that can be perfectly avoided. 2010 13th International IEEE Annual Conference on Intelligent Transportation Systems Madeira Island, Portugal, September 19-22, 2010 MB5.2 978-1-4244-7659-6/10/$26.00 ©2010 IEEE 392