排序方式: 共有2条查询结果,搜索用时 0 毫秒
1
1.
Man-Im Anongpun Ongsakul Weerakorn Singh J. G. Madhu M. Nimal 《Electrical Engineering (Archiv fur Elektrotechnik)》2019,101(3):699-718
Electrical Engineering - A multi-objective optimal power flow (OPF) solution using an enhanced NSPSO, incorporating chaotic mutation and stochastic weight trade-off features, is proposed here. The... 相似文献
2.
In this paper, a stochastic weight trade-off chaotic non-dominated sorting particle swarm optimization (SWTC_NSPSO) is proposed for solving multi-objective economic dispatch considering wind power penetration. Multi-objective functions including generator fuel cost and system risk are considered. The SWTC_NSPSO algorithm improves the solution search capability by balancing between global best exploration and local best utilization through the stochastic weight trade-off technique combining dynamistic coefficients trade-off methods. The proposed algorithm cooperates with the freak, lethargy factors, and chaotic mutation to enhance diversity and search capability. Non-dominated sorting and crowding distance techniques efficiently provide the optimal Pareto front. The fuzzy function is used to select the local compromise best solution. Using a two stage approach, the global best compromise solution is selected from a large number of local best compromise trial solutions. Simulation results on the modified IEEE 30-bus test system indicate that SWTC_NSPSO can provide a lower and wider Pareto front than non-dominated sorting genetic algorithm II (NSGAII), non-dominated sorting particle swarm optimization (NSPSO), non-dominated sorting chaotic particle swarm optimization (NS_CPSO), and a stochastic weight trade-off non-dominated sorting particle swarm optimization (SWT_NSPSO) in a less computation effort, leading to a lower generator fuel cost and a higher system reliability trade-off solution. 相似文献
1