本文選題：多目標(biāo)優(yōu)化　切入點(diǎn)：進(jìn)化算法　出處：《計(jì)算機(jī)科學(xué)》2017年S2期 　論文類型：期刊論文

【摘要】：鑒于電力需求的日益增長(zhǎng)與傳統(tǒng)無功優(yōu)化方法的桎梏,如何更加合理有效地解決電力系統(tǒng)的無功優(yōu)化問題逐漸成為了研究的熱點(diǎn)。提出一種多目標(biāo)飛蛾撲火算法來解決電力系統(tǒng)多目標(biāo)無功優(yōu)化的問題,算法引入固定大小的外部?jī)?chǔ)存機(jī)制、自適應(yīng)的網(wǎng)格和篩選機(jī)制來有效存儲(chǔ)和提升無功優(yōu)化問題的帕累托最優(yōu)解集,算法采用CEC2009標(biāo)準(zhǔn)多目標(biāo)測(cè)試函數(shù)來進(jìn)行仿真實(shí)驗(yàn),并與兩種經(jīng)典算法進(jìn)行性能的對(duì)比分析。此外,在電力系統(tǒng)IEEE 30節(jié)點(diǎn)上將該算法與MOPSO,NGSGA-Ⅱ算法的求解結(jié)果進(jìn)行比較分析的結(jié)果表明,多目標(biāo)飛蛾算法具有良好的性能,并在解決電力系統(tǒng)多目標(biāo)無功優(yōu)化問題上具有良好的潛力。
[Abstract]:In view of the increasing demand for electricity and the shackles of traditional reactive power optimization methods, How to solve the problem of reactive power optimization in power system more reasonably and effectively has gradually become a hot topic. A multi-objective moth-fighting algorithm is proposed to solve the problem of multi-objective reactive power optimization in power system. The algorithm introduces fixed size external storage mechanism, adaptive mesh and filter mechanism to effectively store and enhance the Pareto optimal solution set of reactive power optimization problem. The algorithm uses CEC2009 standard multi-objective test function to carry out simulation experiments. The performance of the algorithm is compared with that of two classical algorithms. In addition, the results of comparison between the algorithm and the MOPSONNGSGA- 鈪，

本文編號(hào)：1576817