基于改进灰狼优化算法的分布式电源优化配置
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摘要
计及源荷侧随机波动性的影响,采用机会约束规划方法,建立综合考虑配电网运行费用、电压稳定性和污染气体排放量的分布式电源随机规划模型。考虑各评价指标的数量级不同,为避免过度优化某一评价指标,采用模糊技术建立综合满意度函数。结合半不变量理论和Cornish-Fisher级数展开计算配电网随机潮流,得到节点电压幅值的概率密度曲线,从概率的角度对系统电压水平进行评估。对一种新颖的灰狼优化算法进行改进,采用Tent映射产生的混沌序列代替随机产生的初始种群,同时提出一种非线性收缩因子。PG&E33节点系统的仿真结果验证该文模型和算法的有效性及合理性。
Stochastic programming model of distributed generations is proposed based on chance constrained programming method in this paper,which considers operating cost of distribution network,voltage stability,pollution gas emissions and stochastic volatility of generation side and demand side. The quantity level of each evaluation index is different. The fuzzy technology is used to establish comprehensive satisfaction function to avoid excessively optimizing a certain evaluation index. Stochastic power flow is calculated with semi-invariant theory and Cornish-Fisher series expansion in distribution network. System voltage level is evaluated by probability density curve of node voltage amplitude. An improved grey wolf optimization algorithm is proposed,which uses a non-linear shrinkage factor and makes chaotic sequence of Tent map instead of initial population. The simulation results of PG&E33 system verify the validity and rationality of the model and algorithm.
Stochastic programming model of distributed generations is proposed based on chance constrained programming method in this paper,which considers operating cost of distribution network,voltage stability,pollution gas emissions and stochastic volatility of generation side and demand side. The quantity level of each evaluation index is different. The fuzzy technology is used to establish comprehensive satisfaction function to avoid excessively optimizing a certain evaluation index. Stochastic power flow is calculated with semi-invariant theory and Cornish-Fisher series expansion in distribution network. System voltage level is evaluated by probability density curve of node voltage amplitude. An improved grey wolf optimization algorithm is proposed,which uses a non-linear shrinkage factor and makes chaotic sequence of Tent map instead of initial population. The simulation results of PG&E33 system verify the validity and rationality of the model and algorithm.
引文
[1] Mostafa N,Rachid C,Mario P. Optimal allocation ofdispersed energy storage systems in active distributionnetworks for energy balance and grid support[J]. IEEETransactions on Power Systems,2014,29(5):2300—2310.
[2] Peyman K,Gharehpetian G B,Abedi M,et al. Longterm scheduling for optimal allocation and sizing of DGunit considering load variations and DG type[J].Electrical Power and Energy Systems,2014,9(54):277—287.
[3]刘波,张焰,杨娜.改进的粒子群优化算法在分布式电源选址和定容中的应用[J].电工技术学报,2008,35(6):103—108.[3] Liu Bo,Zhang Yan,Yang Na. Improved particle swarmswarm optimization method and its application in thesiting and sizing of distributed generation planning[J].Transactions of China Electrotechnical Society,2008,35(6):103—108.
[4]叶德意,何正友,臧天磊.基于自适应变异粒子群算法的分布式电源选址与容量确定[J].电网技术,2011,35(6):155—160.[4] Ye Deyi,He Zhengyou,Zang Tianlei. Siting and Sizingof distributed generation planning based on adaptivemutation particle swarm optimization algorithm[J].Power System Technology,2011,35(6):155—160.
[5]周勇,陈家俊,姜飞,等.基于改进萤火虫算法的分布式电源优化配置[J].现代电力,2014,31(5):54—58.[5] Zhou Yong,Chen Jiajun,Jiang Fei,et al. Research onoptimized distributed generations locating based onmodified firefly algorithm[J]. Modern Electric Power,2014,31(5):54—58.
[6]潘超,孟涛,蔡国伟,等.主动配电网广义电源多目标优化规划[J].电工电能新技术,2016,35(3):41—46.[6] Pan Chao, Meng Tao, Cai Guowei, et al. Multi-objective optimization planning of generalized power inactive distribution network[J]. Advanced Technology ofElectrical Engineering and Energy,2016,35(3):41—46.
[7]夏澍,顾劲岳,葛晓琳,等.风光联合优化配置的多目标机会约束规划方法[J].电力系统保护与控制,2016,44(6):35—40.[7] Xia Shu,Gu Jinyue,Ge Xiaolin,et al. Multiobjectivechance-constrained programming method for windgenerations and photovoltaic allocating[J]. PowerSystem Protection and Control,2016,44(6):35—40.
[8] Mirjalili S, Mirjalili S M, Lewis A. Grey wolfoptimization[J]. Advances in Engineering Software,2014,69:46—61.
[9]潘超,孟涛,蔡国伟,等.广义电源多目标优化配置与运行[J].电网技术,2015,39(12):3505—3512.[9] Pan Chao, Meng Tao, Cai Guowei, et al. Multi-objective optimal configuration and operation ofgeneralized power sources[J]. Power SystemTechnology,2015,39(12):3505—3512.
[10]武晓朦,刘健,毕鹏翔.配电网电压稳定性研究[J].电网技术,2006,30(24):31—35.[10] Wu Xiaomeng,Liu Jian,Bi Pengxiang. Research onvoltage stability of distribution networks[J]. PowerSystem Technology,2006,30(24):31—35.
[11]王锡凡,王秀丽.电力系统随机潮流分析[J].西安交通大学学报,1988,22(2):87—97.[11] Wang Xifan, Wang Xiuli. Probabilistic load flowanalysis in power systems[J]. Journal of Xi’an JiaotongUniversity,1988,22(2):87—97.
[12]郭效军,蔡德福.不同级数展开的半不变量法概率潮流计算比较分析[J].电力自动化设备,2013,33(12):85—110.[12] Guo Xiaojun,Cai Defu. Comparison of probabilisticload nflow calculation based on cumulant method amongdifferent series expansions[J]. Electric Power AutomationEquipment,2013,33(12):85—110.
[13]张浩,张铁男,沈继红,等. Tent混沌粒子群算法及其在结构优化决策中的应用[J].控制与决策,2008,23(8):857—862.[13] Zhang Hao, Zhang Tienan, Shen Jihong, et al.Research on decision-makings of struture optimizationbased on improved Tent PSO[J]. Control and Decision,2008,23(8):857—862.
[14] Aman M M,Jasmon G B,Bakar A H A,et al. A newapproach for optimum simultaneous multi-DGdistributed generation units placement and sizing basedon maximization of system loadability using HPSO(hybrid particle swarm optimization)algorithm[J].Energy,2014,66:202—215.
[15]潘超,孟涛,蔡国伟,等.含分布式电源的主动配电网双层规划模型[J].电测与仪表,2015,52(24):19—34.[15] Pan Chao,Meng Tao,Cai Guowei,et al. Bi-levelprogramming model of distributed generation in activedistribution network[J]. Electrical Measurement&Instrumentation,2015,52(24):19—34.
[2] Peyman K,Gharehpetian G B,Abedi M,et al. Longterm scheduling for optimal allocation and sizing of DGunit considering load variations and DG type[J].Electrical Power and Energy Systems,2014,9(54):277—287.
[3]刘波,张焰,杨娜.改进的粒子群优化算法在分布式电源选址和定容中的应用[J].电工技术学报,2008,35(6):103—108.[3] Liu Bo,Zhang Yan,Yang Na. Improved particle swarmswarm optimization method and its application in thesiting and sizing of distributed generation planning[J].Transactions of China Electrotechnical Society,2008,35(6):103—108.
[4]叶德意,何正友,臧天磊.基于自适应变异粒子群算法的分布式电源选址与容量确定[J].电网技术,2011,35(6):155—160.[4] Ye Deyi,He Zhengyou,Zang Tianlei. Siting and Sizingof distributed generation planning based on adaptivemutation particle swarm optimization algorithm[J].Power System Technology,2011,35(6):155—160.
[5]周勇,陈家俊,姜飞,等.基于改进萤火虫算法的分布式电源优化配置[J].现代电力,2014,31(5):54—58.[5] Zhou Yong,Chen Jiajun,Jiang Fei,et al. Research onoptimized distributed generations locating based onmodified firefly algorithm[J]. Modern Electric Power,2014,31(5):54—58.
[6]潘超,孟涛,蔡国伟,等.主动配电网广义电源多目标优化规划[J].电工电能新技术,2016,35(3):41—46.[6] Pan Chao, Meng Tao, Cai Guowei, et al. Multi-objective optimization planning of generalized power inactive distribution network[J]. Advanced Technology ofElectrical Engineering and Energy,2016,35(3):41—46.
[7]夏澍,顾劲岳,葛晓琳,等.风光联合优化配置的多目标机会约束规划方法[J].电力系统保护与控制,2016,44(6):35—40.[7] Xia Shu,Gu Jinyue,Ge Xiaolin,et al. Multiobjectivechance-constrained programming method for windgenerations and photovoltaic allocating[J]. PowerSystem Protection and Control,2016,44(6):35—40.
[8] Mirjalili S, Mirjalili S M, Lewis A. Grey wolfoptimization[J]. Advances in Engineering Software,2014,69:46—61.
[9]潘超,孟涛,蔡国伟,等.广义电源多目标优化配置与运行[J].电网技术,2015,39(12):3505—3512.[9] Pan Chao, Meng Tao, Cai Guowei, et al. Multi-objective optimal configuration and operation ofgeneralized power sources[J]. Power SystemTechnology,2015,39(12):3505—3512.
[10]武晓朦,刘健,毕鹏翔.配电网电压稳定性研究[J].电网技术,2006,30(24):31—35.[10] Wu Xiaomeng,Liu Jian,Bi Pengxiang. Research onvoltage stability of distribution networks[J]. PowerSystem Technology,2006,30(24):31—35.
[11]王锡凡,王秀丽.电力系统随机潮流分析[J].西安交通大学学报,1988,22(2):87—97.[11] Wang Xifan, Wang Xiuli. Probabilistic load flowanalysis in power systems[J]. Journal of Xi’an JiaotongUniversity,1988,22(2):87—97.
[12]郭效军,蔡德福.不同级数展开的半不变量法概率潮流计算比较分析[J].电力自动化设备,2013,33(12):85—110.[12] Guo Xiaojun,Cai Defu. Comparison of probabilisticload nflow calculation based on cumulant method amongdifferent series expansions[J]. Electric Power AutomationEquipment,2013,33(12):85—110.
[13]张浩,张铁男,沈继红,等. Tent混沌粒子群算法及其在结构优化决策中的应用[J].控制与决策,2008,23(8):857—862.[13] Zhang Hao, Zhang Tienan, Shen Jihong, et al.Research on decision-makings of struture optimizationbased on improved Tent PSO[J]. Control and Decision,2008,23(8):857—862.
[14] Aman M M,Jasmon G B,Bakar A H A,et al. A newapproach for optimum simultaneous multi-DGdistributed generation units placement and sizing basedon maximization of system loadability using HPSO(hybrid particle swarm optimization)algorithm[J].Energy,2014,66:202—215.
[15]潘超,孟涛,蔡国伟,等.含分布式电源的主动配电网双层规划模型[J].电测与仪表,2015,52(24):19—34.[15] Pan Chao,Meng Tao,Cai Guowei,et al. Bi-levelprogramming model of distributed generation in activedistribution network[J]. Electrical Measurement&Instrumentation,2015,52(24):19—34.