Minimum charging-cost tracking based optimization algorithm with dynamic programming technique for plug-in hybrid electric vehicles

By 2015, one million PHEVs are estimated to posses U.S. automotive market. Optimized management of PHEVs charging activities is necessary since growing penetration of PHEV fleet would place significant influences on grid, either by providing bulky energy storages or by requiring charging capacities. In this paper, dynamic programming (DP) technique is applied to seek minimum cost of PHEVs charging activities. Battery state-of-charge (SoC) is taken as the state factor and charging current works as the control factor in the objective function. The cost function is established based on realtime electricity price. Charging decisions are made stage by stage due to the uncertainty of real-time price. Day-ahead price data is applied in DP algorithm to optimize the charging map.