求解电力系统多目标环境经济调度的帕累托最优MFO算法
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摘要
本文提出了一种利用MFO算法解决电力系统环境经济调度的新方法,该算法利用飞蛾扑火原理对设定目标进行螺旋式搜索,并在目标位置进行重复检索。MFO算法对于大规模非线性规划问题具有较强的适应性和有效性。在求解环境经济调度问题中,结合实际发电系统运行过程中应满足的功率平衡约束和容量约束等,以总燃料成本和污染排放最低为目标建立多目标规划数学模型。运用帕累托最优前沿求取帕累托非劣性最优解,得到帕累托最优配置方案,在可行域中搜索出全局最优解。在MATLAB仿真平台对含40台发电机组系统进行仿真计算,结果表明本文提出算法在求解电力系统环境经济调度中具有较高的收敛性和较强的适应性。
This paper proposed a new method to solve economic-environmental dispatch of power system problem by using moth-flame optimization( MFO) algorithm. The algorithm searchs the setting goals for spiral deeply by using moth-flame principle,and repeats to search in the target location. Moth-flame optimization algorithm has strong adaptability and effectiveness for large-scale nonlinear programming problems. In the process of solving the economic-environmental dispatch problem,with the power balance constraints and capacity constraints in the actual process of the electricity generation and operation,fuel costs and emissions of polluting gases are regarded as optimization objectives of the multi-objective programming model. The Pareto-optimal frontier can obtain the non-inferiority optimal solution,then the optimal allocation scheme is obtained and the global optimal scheduling scheme is searched in the feasible region. In the MATLAB simulation platform,the simulation calculation is carried out for 40 generating sets,and the results show that the algorithm proposed in this paper has high convergence and adaptability in solving the environmental economic dispatch of power system.
This paper proposed a new method to solve economic-environmental dispatch of power system problem by using moth-flame optimization( MFO) algorithm. The algorithm searchs the setting goals for spiral deeply by using moth-flame principle,and repeats to search in the target location. Moth-flame optimization algorithm has strong adaptability and effectiveness for large-scale nonlinear programming problems. In the process of solving the economic-environmental dispatch problem,with the power balance constraints and capacity constraints in the actual process of the electricity generation and operation,fuel costs and emissions of polluting gases are regarded as optimization objectives of the multi-objective programming model. The Pareto-optimal frontier can obtain the non-inferiority optimal solution,then the optimal allocation scheme is obtained and the global optimal scheduling scheme is searched in the feasible region. In the MATLAB simulation platform,the simulation calculation is carried out for 40 generating sets,and the results show that the algorithm proposed in this paper has high convergence and adaptability in solving the environmental economic dispatch of power system.
引文
[1]刘静,罗先觉(Liu Jing,Luo Xianjue).采用多目标随机黑洞粒子群优化算法的环境经济发电调度(Environ-mental economic dispatching adopting multi-objective random black-hole particle swarm optimization algorithm)[J].中国电机工程学报(Proceedings of the CSEE),2010,30(34):105-111.
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[9]陈功贵,陈金富(Chen Gonggui,Chen Jinfu).含风电场电力系统环境经济动态调度建模与算法(Environmental/economic dynamic dispatch modeling and method for power systems integrating wind farms)[J].中国电机工程学报(Proceedings of the CSEE),2013,33(10):27-35.
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[12]刘磊,杨仕友(Liu Lei,Yang Shiyou).高维多目标优化设计的改进多重单目标Pareto采样算法研究(An improved multiple single objective Pareto sampling algorithm for many-objective optimizations)[J].电工电能新技术(Advanced Technology of Electrical Engineering and Energy),2013,32(1):89-93.
[13]崔逊学(Cui Xunxue).多目标进化算法及其应用(Applications adopting multi-objective evolutionary algorithm)[M].北京:国防工业出版社(Beijing:National Defence Industry Press),2006.
[14]冯士刚,艾芊(Feng Shigang,Ai Qian).带精英策略的快速非支配排序遗传算法在多目标无功优化中的应用(Application of fast and elitist non-dominated sorting generic algorithm in multi objective reactive power optimization)[J].电工技术学报(Transactions of China Electrotechnical Society),2007,22(12):146-152.
[15]Güven9 U,S9nmez Y,Duman S,et al.Combined economic and emission dispatch solution using gravitational search algorithm[J].Scientia Iranica,2012,19(6):1754-1762.
[2]江岳文,陈冲,温步瀛(Jiang Yuewen,Chen Chong,Wen Buying).基于随机模拟粒子群算法的含风电场电力系统经济调度(Economic dispatch based on particle swarm optimization of stochastic simulation in wind power integrated system)[J].电工电能新技术(Advanced Technology of Electrical Engineering and Energy),2007,26(3):37-41.
[3]伍大清,刘立,郑建国,等(Wu Daqing,Liu Li,Zheng Jianguo,et al.).基于环境经济调度问题的空间自适应划分多目标优化(Environmental economic power dispatch based on multi-objective evolution algorithm with adaptive space partition)[J].控制与决策(Control and Decision),2015,30(11):1974-1980.
[4]Kuntal Bhattacharjee,Aniruddha Bhattacharya,Sunita Halder nee Dey.Backtracking search optimization based economic environmental power dispatch problems[J].International Journal of Electrical Power&Energy Systems,2015,73:830-842.
[5]Hota P K,Barisal A K,Chakrabarti R.Economic emission load dispatch through fuzzy based bacterial foraging algorithm[J].International Journal of Electrical Power&Energy Systems,2010,32:794-803.
[6]Bhattacharya A,Chattopadhyay P K.Application of bio-geography based optimization for solving multi-objective economic emission load dispatch problems[J].Electric Power Components and Systems,2010,38(3):340-365.
[7]Abdelaziz A Y,Ali E S,Abd Elazim S M.Combined economic and emission dispatch solution using flower pollination algorithm[J].International Journal of Electrical Power&Energy Systems,2016,80:264-274.
[8]谭忠富,鞠立伟,陈致宏,等(Tan Zhongfu,Ju Liwei,Chen Zhihong,et al.).基于粗糙集理论与CLSDE算法的环境经济调度优化模型(An environmental economic dispatch optimization model based on rough set theory and chaotic local search strategy differential evolution algorithm)[J].电网技术(Power System Technology),2014,38(5):1339-1345.
[9]陈功贵,陈金富(Chen Gonggui,Chen Jinfu).含风电场电力系统环境经济动态调度建模与算法(Environmental/economic dynamic dispatch modeling and method for power systems integrating wind farms)[J].中国电机工程学报(Proceedings of the CSEE),2013,33(10):27-35.
[10]Mirjalili S.Moth-flame optimization algorithm:A novel nature-inspired heuristic paradigm[J].Knowledge Based Systems,2015,89:228-249.
[11]Chen Po Hung,Chang Hong Chan.Large-scale economic dispatch by genetic algorithm[J].IEEE Transactions on Power Systems,1995,10(4):1919-1926.
[12]刘磊,杨仕友(Liu Lei,Yang Shiyou).高维多目标优化设计的改进多重单目标Pareto采样算法研究(An improved multiple single objective Pareto sampling algorithm for many-objective optimizations)[J].电工电能新技术(Advanced Technology of Electrical Engineering and Energy),2013,32(1):89-93.
[13]崔逊学(Cui Xunxue).多目标进化算法及其应用(Applications adopting multi-objective evolutionary algorithm)[M].北京:国防工业出版社(Beijing:National Defence Industry Press),2006.
[14]冯士刚,艾芊(Feng Shigang,Ai Qian).带精英策略的快速非支配排序遗传算法在多目标无功优化中的应用(Application of fast and elitist non-dominated sorting generic algorithm in multi objective reactive power optimization)[J].电工技术学报(Transactions of China Electrotechnical Society),2007,22(12):146-152.
[15]Güven9 U,S9nmez Y,Duman S,et al.Combined economic and emission dispatch solution using gravitational search algorithm[J].Scientia Iranica,2012,19(6):1754-1762.