摘要
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 optimization model for multi-objective transaction of interconnected power grid is solved by non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) algorithm and the solutions over diversified Pareto front are obtained which can offer wealth of information for the decision-making; further combining the Pareto front with multiple attributes decision-making (MADM), the optimal solution is screened out. Results of calculation example show that the optimal solution attained by the proposed method is better that that obtained by Shapley value-based cooperative game method. The attained solution can provide optimized allocation scheme for electric power transaction of integrated power grid precisely.
出处
《电网技术》
EI
CSCD
北大核心
2011年第8期30-34,共5页
Power System Technology
关键词
多目标优化
互联电网
多属性决策
演化算法
帕雷托解集
multi-objective optimization
interconnected power grid
multiple attributes decision making
genetic algorithm
Pareto solution set