参考文献/References:
[1]JOHNSON R C, HAPP H H, WRIGHT W J.Large scale hydro-thermal unit commitment-method and results[J].IEEE Transactions on power apparatus and systems,1971,PAS-90(3):1373-1384.
[2]PANG C K,SHEBLE G B,ALBUYEH F.Evaluation of dynamic programming based methods and multiple area representation for thermal unit commitments[J].IEEE Transactions on power apparatus and systems,1981,PAS-100(3):1212-1218.
[3]葛莲.基于混合智能算法的电力系统无功优化研究[D].兰州:兰州交通大学,2012.
[4]吴凡.基于粒子群优化算法的风电-火电机组组合调度研究[D].北京:华北电力大学,2015.
[5]孙璐.基于改进粒子群优化算法的电力系统无功优化[D].广州:华南理工大学,2012.
[6]张毅磊.基于果蝇优化算法的电力系统无功优化研究与应用[D].长沙:湖南大学,2015.
[7]方杰,艾欣,潘伟,等.基于可中断负荷的机组组合优化调度模型[J].现代电力,2014,31(4):47-53.
[8]YAMIN H Y,SHAHIDEHPOUR S M.Unit commitment using a hybrid model between Lagrangian relaxation and genetic algorithm in competitive electricity markets[J].Electric power systems research,2004,68(2):83-92.
[9]ARISTYO M F,PENANGSANG O,AZIS M F,et al.Dynamic unit commitment economic dispatch using multi Swarm-PSO based on user interface[C]//International Conference of Integrated Intellectual Community, 2014:22-27.
[10]宋潇,李叶,刘家军,等.基于改进粒子群文化算法的机组组合联合调度研究[J].电网与清洁能源,2016,32(6):77-84.
[11]胡廷鹤.基于多代理粒子群算法的电力系统无功优化研究[D].广州:广东工业大学,2013.
[12]马磊,杨莲.人工智能算法在电力系统无功优化问题中的应用[J].电脑知识与技术, 2010,6(24):6840-6842.
[13]李伟琨,阙波,王万良,等.基于多目标飞蛾算法的电力系统无功优化研究[J].计算机科学,2017,44(增刊2):503-509.
[14]娄素华, 熊信银. 基于多目标微粒群算法的电力系统无功优化研究[C]//中国高等学校电力系统及其自动化专业第二十三届学术年会论文汇编.合肥:合肥工业大学, 2008:60-64.
[15]汪海涌.基于遗传算法的电力系统无功优化的研究[D].重庆:重庆大学,2005.
[16]CHEN Y Q,LIU K P.Research on dynamic optimal reactive power dispatch based on immune agent system[C]//7th IET International Conference on Advances in Power System Control, Operation and Management,2006: 40-45.
[17]KARTHIKAIKANNAN D, RAVI G.Optimal reactive power dispatch of power system using improved harmony search algorithm[J].International review of electrical engineering,2014,9(3):620-628.
[18]LIU K Y,SHENG W X,LI Y H.Research on reactive power optimization based on immunity genetic algorithm[C]// Proceedings of the 2006 International Conference on Intelligent Computing:-Volume Part I,2006:600-611.
[19]SARKHEYLI A,ZAIN A M, SHARIF S.The role of basic, modified and hybrid shuffled frog leaping algorithm on optimization problems: a review[J].Soft computing,2015,19(7):2011-2038.