Fuzzy Load Modeling of Plug-in Electric Vehicles for Optimal Storage and DG Planning in Active Distribution Network

Abstract

Plug-in electric vehicle (PEV) charge challenges can be addressed by including their effects on the planning of distribution network components. The planning problem becomes more combinatorial when the uncertainty of PEVs is considered as well. In this paper, storage and distributed generation (DG) planning is considered as an option to deal with the problems arising from PEV uncertainty. The optimal location, capacity, and power rating of the stationary batteries, as well as the location and capacity of dispatchable DGs, are determined to minimize the cost objective function under technical constraints. Short-term scheduling and long-term planning, as optimization problems, are solved using Tabu Search and simulated annealing algorithms, respectively. Simulation results show that when connecting PEVs to the distribution network, both of the stationary battery and DG units are needed from technical and economic points of view. Moreover, the optimal penetration of stationary storage units increases if the uncertainty of PEVs is considered.