Optimal integration and location of PHEV aggregators in power distribution systems

In this paper, optimal battery scheduling for Plug-In Hybrid Electric Vehicles (PHEVs) is achieved for load leveling. This proper scheduling can lead to peak shaving and off-peak shaving (valley filling). Due to the uncertain nature of PHEVs, including charging and discharging times and daily movements, stochastic modeling is proposed. Daily movements to and from houses to administrative centers, as well as charging and discharging schedules are chronological-based; therefore, using sequential Monte-Carlo Simulation (MCS) is highly recommended. Furthermore, in order to optimize the scheduling-related fitness functions, Particle Swarm optimization (PSO) algorithm is utilized. Also, this paper focuses on finding the best location of parking lots for these PHEV aggregators. Two indices, voltage unbalance and power loss, for locating the PHEV aggregators are considered. During peak hours, these criteria can be more critical for a three-phase distribution system. Hence, this problem is solved using a multi-objective optimization algorithm based on fuzzification of objectives. The results are compared with those of single-objective algorithms. IEEE 13 node three-phase benchmark system is used for analyzing the proposed method.