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A multi-objective stochastic programming method of electric vehicle charging load based on non-dominated sorting genetic algorithm
A multi-objective stochastic programming method of electric vehicle charging load based on non-dominated sorting genetic algorithm
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机译:基于非支配排序遗传算法的电动汽车充电负荷多目标随机规划方法
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#$%^&*AU2014101609A420170727.pdf#####ABSTRACT OF THE INVENTION The invention discloses a multi-objective stochastic programming approach of EV charging load based on non-dominated sorting genetic algorithm. In combination with the requirements of the best operation of the distribution system and in consideration of the influence of multiple random factors, it establishes a new multi-objective stochastic optimization model of the distribution network based on EV charging load, which utilizes the improved non-dominated sorting genetic algorithm- II (non-dominated sorting genetic algorithm-2, NSGA-2) to solve, takes fully charged EV battery, charging power within limit and distribution network tide constraints as constraint conditions and takes distribution network loss, power node peak load and load fluctuation optimization as sub-goals to achieve multi-objective stochastic programming of EV charging load.
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