Energy management for plug in hybrid electric vehicles using stochastic optimization

This paper presents Mixed Integer Linear Programming (MILP) for large number of Plug in Hybrid Electric Vehicles (PHEVs) charging and discharging in a grid connected charging park. The main objective of this paper is to find the optimum power flow and to reduce the overall daily charging cost of PHEVs when subject to various constraints such as power balance constraints, Battery charging/discharging constraints and PHEVs arrival/departure State of Charge (SOC) constraints. PHEVs involve battery with different battery ratings, fuel cells as well as photo voltaic (PV) systems. Here the solar power is considered as a valuable energy source for charging of PHEVs. The process of Charging and discharging is to optimize the bidirectional energy flows between the grid and PHEVs Battery. The proposed MILP algorithm to find global optimum solution for minimize the charging cost of PHEVs, Hence the PHEVs charged during the periods with low electricity prices therefore owners pay minimum cost for charging their vehicles. The results showed the proposed algorithm that minimizes the charging cost of PHEVs and optimal power flow for the grid connected PHEVs systems. Moreover, electric vehicle owners could yield more profit by discharging their vehicles as well as having preferred state of charge in the leaving time.