利用改进非劣分层遗传算法(non-dominated sorting genetic algorithm II,NSGA-II)对互联电网多目标交易优化模型进行求解,得到多样化的帕雷托前沿,为决策提供丰富的信息,进一步与基于基点和熵的多属性决策方法结合,筛选出最优解。算例分析结果表明,该方法得出的解比用基于沙普利值的合作博弈法得出的解更优,能准确提供互联电网交易的优化分配方案,具有一定的实用性。 The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective transaction optimization model for interconnected power grids, and a diversified Pareto front is obtained to provide rich information for decision making. Based on the combination of the basis points and entropy of multi-attribute decision making method, the optimal solution is screened out. The results of the example analysis show that the solution obtained by this method is better than that obtained by using the cooperative game theory based on the Shapley value and can provide the optimal distribution scheme of the interconnected power grid transaction accurately, which has a certain practicality.