Network security-aware charging of electric vehicles

Large-scale integration of electric vehicles (EV) and wind power could have significantly negative impacts on power systems security. So, it is becoming an increasingly important issue to develop an effective network security-aware charging strategy of EVs. This paper proposes a multi-objective formulation for the optimal charging schedule of EVs while considering N − 1 security constraints. An EV aggregator representing a cluster of controllable EVs is modeled for determining the optimal charging schedule based on a trilevel hierarchy. On the top level, the grid control center determines the EV charging strategy from the proposed formulation, where bus voltage fluctuations, network power losses, and EV charging adjustments are considered as multi-objective functions. To reduce the computational burden, Lagrangian Relaxation (LR) is introduced to handle time coupled constraints and Benders Decomposition is introduced to handle contingencies. Case studies have been conducted on the New England 39-bus system, and the results verify the necessity of considering N − 1 security constraints and the effectiveness of the proposed formulation and solution approach.