This research deals with the energy management problem to minimize the cost of non-renewable energy for a small-scale microgrid with electric vehicles(EV)and electric tractors(ET).The EVs and ETs function as batteries...This research deals with the energy management problem to minimize the cost of non-renewable energy for a small-scale microgrid with electric vehicles(EV)and electric tractors(ET).The EVs and ETs function as batteries in the power system,while they often have to leave it for their mobility and agricultural work.Each State of Charge(SoC),which is the charge rate of the battery from 0 to 1,and the operating time of ETs are optimized under the assumption that the required electrical energy,the arrival and departure time of EVs,and the working time of ETs are given by users,but they include uncertainties.In this paper,we deal with these uncertainties by constraints for robust energy planning and expected optimization based on scenarios,and show that the scheduling of the SoC assuming the worst case and the optimal home-based power consumption planning that considers the cost of each scenario corresponding to each variation can be obtained.Our proposed method is formulated as a mixed-integer linear programming(MILP),and numerical simulations show that the optimal cooperative operation among multiple houses can be obtained and its global optimal or sub-optimal solution can be quickly obtained by using CPLEX.展开更多
文摘This research deals with the energy management problem to minimize the cost of non-renewable energy for a small-scale microgrid with electric vehicles(EV)and electric tractors(ET).The EVs and ETs function as batteries in the power system,while they often have to leave it for their mobility and agricultural work.Each State of Charge(SoC),which is the charge rate of the battery from 0 to 1,and the operating time of ETs are optimized under the assumption that the required electrical energy,the arrival and departure time of EVs,and the working time of ETs are given by users,but they include uncertainties.In this paper,we deal with these uncertainties by constraints for robust energy planning and expected optimization based on scenarios,and show that the scheduling of the SoC assuming the worst case and the optimal home-based power consumption planning that considers the cost of each scenario corresponding to each variation can be obtained.Our proposed method is formulated as a mixed-integer linear programming(MILP),and numerical simulations show that the optimal cooperative operation among multiple houses can be obtained and its global optimal or sub-optimal solution can be quickly obtained by using CPLEX.
