改进的花朵授粉算法在微网优化调度中的应用
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摘要
研究了用于解决微网优化调度问题的群智能算法.针对微网优化调度问题的多目标、多约束条件等特点,对微网优化调度问题建模;提出了改进的花朵授粉算法,并将其应用到微网优化调度问题.在初始化时,采用对立点方法增加种群多样性和优化搜索空间;局部更新时,使用一种新的局部更新算子提高算法收敛速度;此外,为了减少计算量和避免陷入局部最优,定义了是否使用遗传操作的判断条件.仿真结果表明,该算法性能优于原始花朵授粉算法和遗传算法等其他算法.
The swarm intelligence algorithm for solving the problem of optimization dispatch of microgrid was investigated. A model for optimization dispatch of microgrid was established under the consideration of the process characteristics,such as multi-objective and multi-constraints. A modified flower pollination algorithm( MFPA) was proposed and applied to the optimization dispatch of microgrid. During initialization, opposition method was utilized to improve the diversity of the population as well as fully explore the space. During local updating,the newoperation can accelerate the convergence. In addition,the condition for using genetic operations was defined in order to reduce the calculation and avoid the local optimal solution. Simulation results demonstrated that the performance of MFPA was better than those of FPA,GA and several other algorithms.
The swarm intelligence algorithm for solving the problem of optimization dispatch of microgrid was investigated. A model for optimization dispatch of microgrid was established under the consideration of the process characteristics,such as multi-objective and multi-constraints. A modified flower pollination algorithm( MFPA) was proposed and applied to the optimization dispatch of microgrid. During initialization, opposition method was utilized to improve the diversity of the population as well as fully explore the space. During local updating,the newoperation can accelerate the convergence. In addition,the condition for using genetic operations was defined in order to reduce the calculation and avoid the local optimal solution. Simulation results demonstrated that the performance of MFPA was better than those of FPA,GA and several other algorithms.
引文
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[3]Othman M M,El-khattam W,Hegazy Y G,et al.Optimal placement and sizing of voltage controlled distributed generators in unbalanced distribution networks using supervised firefly algorithm[J].International Journal of Electrical Power&Energy Systems,2016,82:105-113.
[4]Tharakeshwar T K,Seetharamu K N,Prasad B D.Multiobjective optimization using bat algorithm for shell and tube heat exchangers[J].Applied Thermal Engineering,2017,110:1029-1038.
[5]Reddy S S,Rathnam C S.Optimal power flow using glowworm swarm optimization[J].International Journal of Electrical Power&Energy Systems,2016,80:128-139.
[6]Yang X S.Flower pollination algorithm for global optimization[C]//International Conference on Unconventional Computation and Natural Computation.Berlin:Springer-Verlag,2012:240-249.
[7]Dubey H M,Pandit M,Panigrahi B K.A biologically inspired modified pollination algorithm for solving economic dispatch problems in modern power systems[J].Cognitive Computation,2015,7(5):1-15.
[8]Abdelaziz A Y,Ali E S,Elazim S M A.Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems[J].Energy,2016,101:506-518.
[9]Rahnamayan S,Tizhoosh H R,Salama M M A.Opposition versus randomness in soft computing techniques[J].Applied Soft Computing,2008,8(2):906-918.
[10]Abedini M,Moradi M H,Hosseinian S M,et al.Optimal management of microgrids including renewable energy scources using GPSO-GM algorithm[J].Renewable Energy,2016,90:430-439.
[11]Malysz P,Sirouspour S,Emadi A.An optimal energy storage control strategy for grid-connected microgrids[J].IEEE Transactions on Smart Grid,2014,5(5):1785-1796.
[12]钱科军,袁越,石晓丹,等.分布式发电的环境效益分析[J].中国电机工程学报,2008,28(29):11-15.(Qian Ke-jun,Yuan Yue,Shi Xiao-dan,et al.Environmental benefits analysis of distributed generation[J].Proceedings of the CSEE,2008,28(29):11-15.)
[13]丁明,张颖媛,茆美琴,等.包含钠硫电池储能的微网系统经济运行优化[J].中国电机工程学报,2011,31(4):7-14.(Ding Ming,Zhang Ying-yuan,Mao Mei-qin,et al.Economic operation optimization for microgrids including Na/S battery storage[J].Proceedings of the CSEE,2011,31(4):7-14.)
[14]陈洁,杨秀,朱兰,等.微网多目标经济调度优化[J].中国电机工程学报,2013,33(19):57-66.(Chen Jie,Yang Xiu,Zhu Lan,et al.Microgrid multi-objective economic dispatch optimization[J].Proceedings of the CSEE,2013,33(19):57-66.)
[15]毛晓明,陈深,吴杰康,等.分时电价机制下含蓄电池微网的优化调度[J].电网技术,2015,39(5):1192-1197.(Mao Xiao-ming,Chen Shen,Wu Jie-kang,et al.Optimal dispatching of microgrid containing battery under time-of-use price mechanism[J].Power System Technology,2015,39(5):1192-1197.)
[16]Holland J.Adaptation in natural and artificial systems[J].The Quarterly Review of Biology,1975,6(2):126-137.
[17]Yang X S.Firefly algorithms for multimodal optimization[C]//Proceeding of the 5th International Symposium on Stochastic Algorithms:Foundations and Applications.Berlin:SpringerVerlag,2009:169-178.
[18]Gandomi A H,Yang X S,Alavi A H,et al.Bat algorithm for constrained optimization tasks[J].Neural Computing and Applications,2013,22(6):1239-1255.