SUMMARY

The electrification of transportation could be an effective strategy for reducing CO2 emissions. At the same time, a large-scale introduction of plug-in hybrid electric vehicles (PHEVs) and electric vehicles also constitutes a challenge to power systems: Uncontrolled charging would lead to increased load peaks thus potentially overloading system assets. In this paper we take into account the potential flexibility of these new loads and propose a smart charging scheme based on endogenous Locational Marginal Prices. We also assess the potential of Vehicle To Grid (V2G) for peak-shaving by using vehicles to arbitrage intertemporal energy price differences. The method employed is an Optimal Power Flow (OPF), which considers supply and demand side as well as network infrastructure simultaneously. The OPF thus constitutes an appropriate framework to assess the impact of PHEVs on network operation, prices and the energy supply. Within this OPF framework vehicles place demand bids according to their driving patterns and battery state of charge, which are then aggregated at each network location or node. Under V2G this scheme is extended and supply curves are defined taking into account battery degradation costs and round-trip energy losses. Vehicles are modeled individually and their driving patterns are obtained from an agent-based transport simulation. In case studies with one million PHEVs we show that the proposed smart charging method constitutes an improvemen