摘要
带精英策略的非支配排序遗传算法(NSGA-Ⅱ)在多目标优化领域中被广泛应用。针对煤矿发电厂电力监控系统多目标环境经济调度(EED)问题,为了进一步提高NSGA-Ⅱ算法的搜索能力和种群多样性,避免早期收敛于局部最优,提出了一种新型融合算法TL-NSGA-Ⅱ。通过对IEEE30节点测试系统进行电力系统环境经济调度仿真测试以及和对比其他算法可知,TL-NSGA-Ⅱ算法能够得到更优的Pareto解,说明该算法能够更有效地求解多目标环境经济调度问题。
The non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) is widely used in the field of multi-objective optimization.To solve multi-objective environmental economic dispatch(EED) problem,in order to improve the search ability and population diversity of the algorithm and avoid early convergence to local optimum,a new fusion algorithm TL-NSGA-Ⅱ is proposed.The proposed algorithm has been examined and tested on IEEE30 bus test system for solving multi-objective environmental economic dispatch and compared with the other exllent algorithm,it can be seen that the TL-NSGA-Ⅱ algorithm can obtain a better Pareto solution,which shows that the algorithm can effectively solve the multi-objective environmental economic dispatch problem.
作者
郭振科
陈运启
满兴中
GUO Zhenke;CHEN Yunqi;MAN Xingzhong(CHN Energy Wuhai Energy Huangbaici Mining Co.,Ltd.,Wuhai,Inner Mongolia 016000,China;China Coal Technology Engineering Group Chongqing Research Institute,Chongqing 400039,China)
出处
《自动化应用》
2024年第13期38-40,共3页
Automation Application
