基于运行层面相关性场景的含风机配电网多目标无功优化
|
摘要
针对含间歇性分布式电源(distribution generation,DG)配电网的无功优化问题,研究了基于运行层面相关性场景的配电网多目标无功优化模型及决策方法。从运行层面对风速和负荷进行了不确定性建模,构建了运行层面的相关性场景;以静态电压稳定性最好、网损期望最小和电压偏移期望最少为目标函数,建立了含间歇性DG配电网的多目标无功优化模型,并提出了基于优先级的多目标决策方法进行最优非支配解的选取。算例验证了所提方法的有效性,结果表明:基于运行层面的相关性场景构建方法可提高配电网的无功优化性能,基于优先级的多目标决策方法可根据系统实际运行状态动态调整目标偏好,从而保证系统运行稳定、经济及优质供电。
Aiming at reactive power optimization problem of distribution network with intermittent distributed generation(DG), a multi-objective reactive power optimization model of distribution network at operation level based on correlated scenario and a decision-making method is studied. In this paper, uncertainty modeling of wind speed and load is carried out from the runtime layer, and the correlated scenario at operation level is constructed. Based on objective function of the best static voltage stability, the minimum network loss expectation and the minimum voltage deviation expectation, a multi-objective reactive power optimization model of distribution network with intermittent DG is established, and a multi-objective decision-making method based on priority is proposed to select the optimal non-dominated solution. Effectiveness of the proposed method is verified with a numerical example. Results show that the scenario construction method at operation level can improve performance of reactive power optimization of distribution network, and the multi-objective decision-making method based on priority can dynamically adjust target preference according to actual operation state of the system, so as to ensure stable and economic operation, and high-quality power supply.
Aiming at reactive power optimization problem of distribution network with intermittent distributed generation(DG), a multi-objective reactive power optimization model of distribution network at operation level based on correlated scenario and a decision-making method is studied. In this paper, uncertainty modeling of wind speed and load is carried out from the runtime layer, and the correlated scenario at operation level is constructed. Based on objective function of the best static voltage stability, the minimum network loss expectation and the minimum voltage deviation expectation, a multi-objective reactive power optimization model of distribution network with intermittent DG is established, and a multi-objective decision-making method based on priority is proposed to select the optimal non-dominated solution. Effectiveness of the proposed method is verified with a numerical example. Results show that the scenario construction method at operation level can improve performance of reactive power optimization of distribution network, and the multi-objective decision-making method based on priority can dynamically adjust target preference according to actual operation state of the system, so as to ensure stable and economic operation, and high-quality power supply.
引文
[1]陶顺,陈鹏伟,肖湘宁,等.智能配电网不确定性建模与供电特征优化技术综述[J].电工技术学报,2017,32(10):77-91.Tao Shun,Chen Pengwei,Xiao Xiangning,et al.Review on uncertainty modeling and power supply characteristics optimization technology in smart distribution network[J].Transactions of China Electrotechnical Society,2017,32(10):77-91(in Chinese).
[2]陈海焱,段献忠,陈金富.分布式发电对配网静态电压稳定性的影响[J].电网技术,2006,30(19):27-30.Chen Haiyan,Duan Xianzhong,Chen Jinfu.Impacts of distributed generation on steady state voltage stability of distribution system[J].Power System Technology,2006,30(19):27-30(in Chinese).
[3]张谦,廖清芬,唐飞,等.计及分布式电源接入的配电网静态电压稳定性评估方法[J].电力系统自动化,2015,39(15):42-48.Zhang Qian,Liao Qingfen,Tang Fei,et al.Steady state voltage stability assessment method of distribution network considering inter-connection of distributed generators[J].Automation of Electric Power Systems,2015,39(15):42-48(in Chinese).
[4]汪文达,崔雪,马兴,等.考虑多个风电机组接入配电网的多目标无功优化[J].电网技术,2015,39(7):1860-1865.Wang Wenda,Cui Xue,Ma Xing,et al.Multi-objective optimal reactive power flow of distribution network with multiple wind turbines[J].Power System Technology,2015,39(7):1860-1865(in Chinese).
[5]杨德昌,廖文龙,孙雪,等.基于满意度阈值判定的主动配电网无功优化[J].电网技术,2017,41(9):3003-3010.Yang Dechang,Liao Wenlong,Sun Xue,et al.Reactive power optimization of active distribution network based on judgment of the satisfaction threshold[J].Power System Technology,2017,41(9):3003-3010(in Chinese).
[6]王淳,高元海.基于概率统计的含间歇性分布式发电的配电网无功优化[J].电网技术,2014,38(4):1032-1037.Wang Chun,Gao Yuanhai.Probability statistics based reactive power optimization of distribution network containing intermittent distributed generations[J].Power System Technology,2014,38(4):1032-1037(in Chinese).
[7]Zhang S,Cheng H,Zhang L,et al.Probabilistic evaluation of available load supply capability for distribution system[J].IEEE Transactions on Power Systems,2013,28(3):3215-3225.
[8]Shu Z,Jirutitijaroen P.Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources[J].IEEE Transactions on Power Systems,2011,26(4):2066-2073.
[9]Li Y,Li W,Yan W,et al.Probabilistic optimal power flow considering correlations of wind speeds following different distributions[J].IEEE Transactions on Power Systems,2014,29(4):1847-1854.
[10]Narayan K S,Kumar A.Impact of wind correlation and load correlation on probabilistic load flow of radial distribution systems[C]//IEEE International Conference on Signal Processing,Informatics,Communication and Energy Systems.IEEE,2015:1-5.
[11]张世达,孙永辉,赵景涛,等.基于随机响应面法的主动配电网无功优化[J].电力系统自动化,2017,41(13):30-38.Zhang Shida,Sun Yonghui,Zhao Jingtao,et al.Optimal reactive power flow in active distribution network based on stochastic response surface method[J].Automation of Electric Power Systems,2017,41(13):30-38(in Chinese).
[12]王玲玲,王昕,郑益慧,等.计及多个风电机组出力相关性的配电网无功优化[J].电网技术,2017,41(11):3463-3469.Wang Lingling,Wang Xin,Zheng Yihui,et al.Reactive power optimization of distribution network considering output correlation of multiple wind turbines[J].Power System Technology,2017,41(11):3463-3469(in Chinese).
[13]王永杰,吴文传,张伯明.考虑负荷量测和光伏不确定性的主动配电网鲁棒电压控制[J].电力系统自动化,2015,39(9):138-144.Wang Yongjie,Wu Wenchuan,Zhang Boming.Robust voltage control model for active distribution network considering load and photovoltaic uncertainties[J].Automation of Electric Power Systems,2015,39(9):138-144(in Chinese).
[14]冯士刚,艾芊.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[J].电工技术学报,2007,22(12):146-151.Feng Shigang,Ai Qian.Application of fast and elitist non-dominated sorting genetic algorithm in multi-objective reactive power optimization[J].Transactions of China Electrotechnical Society,2007,22(12):146-151(in Chinese).
[15]Soroudi A,Caire R,Hadjsaid N,et al.Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning[J].IET Generation Transmission&Distribution,2011,5(5):1173-1182.
[16]罗毅,多靖赟.基于量子免疫克隆算法的多目标无功优化[J].电力自动化设备,2013,33(9):31-35.Luo Yi,Duo Jingyun.Multi-objective reactive power optimization based on quantum immune colonial algorithm[J].Electric Power Automation Equipment,2013,33(9):31-35(in Chinese).
[17]王松岩,于继来.风速与风电功率的联合条件概率预测方法[J].中国电机工程学报,2011,31(7):7-15.Wang Songyan,Yu Jilai.Joint conditions probability forecast method for wind speed and wind power[J].Proceedings of the CSEE,2011,31(7):7-15(in Chinese).
[18]丁华杰,宋永华,胡泽春,等.基于风电场功率特性的日前风电预测误差概率分布研究[J].中国电机工程学报,2013,33(34):136-144.Ding Huajie,Song Yonghua,Hu Zechun,et al.Probability density function of day-ahead wind power forecast errors based on power curves of wind farms[J].Proceedings of the CSEE,2013,33(34):136-144(in Chinese).
[19]赵希人,李大为,李国斌,等.电力系统负荷预报误差的概率密度函数建模[J].自动化学报,1993,19(5):562-568.Zhao Xiren,Li Dawei,Li Guobin,et al.Probability density function modeling for power system load forecasting errors[J].Acta Automatica Sinica,1993,19(5):562-568(in Chinese).
[20]张沈习,李珂,程浩忠,等.考虑相关性的间歇性分布式电源选址定容规划[J].电力系统自动化,2015,39(8):53-58,140.Zhang Shenxi,Li Ke,Cheng Haozhong,et al.Optimal siting and sizing of intermittent distributed generator considering correlations[J].Automation of Electric Power Systems,2015,39(8):53-58,140(in Chinese).
[21]Liu Z,Wen F,Ledwich G.Optimal siting and sizing of distributed generators in distribution systems considering uncertainties[J].IEEE Transactions on Power Delivery,2011,26(4):2541-2551.
[22]Deb K,Pratap A,Agarwal S,et al.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[23]Baran M E,Wu F F.Optimal capacitor placement on radial distribution systems[J].IEEE Transactions on Power Delivery,1989,4(1):725-734.
[2]陈海焱,段献忠,陈金富.分布式发电对配网静态电压稳定性的影响[J].电网技术,2006,30(19):27-30.Chen Haiyan,Duan Xianzhong,Chen Jinfu.Impacts of distributed generation on steady state voltage stability of distribution system[J].Power System Technology,2006,30(19):27-30(in Chinese).
[3]张谦,廖清芬,唐飞,等.计及分布式电源接入的配电网静态电压稳定性评估方法[J].电力系统自动化,2015,39(15):42-48.Zhang Qian,Liao Qingfen,Tang Fei,et al.Steady state voltage stability assessment method of distribution network considering inter-connection of distributed generators[J].Automation of Electric Power Systems,2015,39(15):42-48(in Chinese).
[4]汪文达,崔雪,马兴,等.考虑多个风电机组接入配电网的多目标无功优化[J].电网技术,2015,39(7):1860-1865.Wang Wenda,Cui Xue,Ma Xing,et al.Multi-objective optimal reactive power flow of distribution network with multiple wind turbines[J].Power System Technology,2015,39(7):1860-1865(in Chinese).
[5]杨德昌,廖文龙,孙雪,等.基于满意度阈值判定的主动配电网无功优化[J].电网技术,2017,41(9):3003-3010.Yang Dechang,Liao Wenlong,Sun Xue,et al.Reactive power optimization of active distribution network based on judgment of the satisfaction threshold[J].Power System Technology,2017,41(9):3003-3010(in Chinese).
[6]王淳,高元海.基于概率统计的含间歇性分布式发电的配电网无功优化[J].电网技术,2014,38(4):1032-1037.Wang Chun,Gao Yuanhai.Probability statistics based reactive power optimization of distribution network containing intermittent distributed generations[J].Power System Technology,2014,38(4):1032-1037(in Chinese).
[7]Zhang S,Cheng H,Zhang L,et al.Probabilistic evaluation of available load supply capability for distribution system[J].IEEE Transactions on Power Systems,2013,28(3):3215-3225.
[8]Shu Z,Jirutitijaroen P.Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources[J].IEEE Transactions on Power Systems,2011,26(4):2066-2073.
[9]Li Y,Li W,Yan W,et al.Probabilistic optimal power flow considering correlations of wind speeds following different distributions[J].IEEE Transactions on Power Systems,2014,29(4):1847-1854.
[10]Narayan K S,Kumar A.Impact of wind correlation and load correlation on probabilistic load flow of radial distribution systems[C]//IEEE International Conference on Signal Processing,Informatics,Communication and Energy Systems.IEEE,2015:1-5.
[11]张世达,孙永辉,赵景涛,等.基于随机响应面法的主动配电网无功优化[J].电力系统自动化,2017,41(13):30-38.Zhang Shida,Sun Yonghui,Zhao Jingtao,et al.Optimal reactive power flow in active distribution network based on stochastic response surface method[J].Automation of Electric Power Systems,2017,41(13):30-38(in Chinese).
[12]王玲玲,王昕,郑益慧,等.计及多个风电机组出力相关性的配电网无功优化[J].电网技术,2017,41(11):3463-3469.Wang Lingling,Wang Xin,Zheng Yihui,et al.Reactive power optimization of distribution network considering output correlation of multiple wind turbines[J].Power System Technology,2017,41(11):3463-3469(in Chinese).
[13]王永杰,吴文传,张伯明.考虑负荷量测和光伏不确定性的主动配电网鲁棒电压控制[J].电力系统自动化,2015,39(9):138-144.Wang Yongjie,Wu Wenchuan,Zhang Boming.Robust voltage control model for active distribution network considering load and photovoltaic uncertainties[J].Automation of Electric Power Systems,2015,39(9):138-144(in Chinese).
[14]冯士刚,艾芊.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[J].电工技术学报,2007,22(12):146-151.Feng Shigang,Ai Qian.Application of fast and elitist non-dominated sorting genetic algorithm in multi-objective reactive power optimization[J].Transactions of China Electrotechnical Society,2007,22(12):146-151(in Chinese).
[15]Soroudi A,Caire R,Hadjsaid N,et al.Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning[J].IET Generation Transmission&Distribution,2011,5(5):1173-1182.
[16]罗毅,多靖赟.基于量子免疫克隆算法的多目标无功优化[J].电力自动化设备,2013,33(9):31-35.Luo Yi,Duo Jingyun.Multi-objective reactive power optimization based on quantum immune colonial algorithm[J].Electric Power Automation Equipment,2013,33(9):31-35(in Chinese).
[17]王松岩,于继来.风速与风电功率的联合条件概率预测方法[J].中国电机工程学报,2011,31(7):7-15.Wang Songyan,Yu Jilai.Joint conditions probability forecast method for wind speed and wind power[J].Proceedings of the CSEE,2011,31(7):7-15(in Chinese).
[18]丁华杰,宋永华,胡泽春,等.基于风电场功率特性的日前风电预测误差概率分布研究[J].中国电机工程学报,2013,33(34):136-144.Ding Huajie,Song Yonghua,Hu Zechun,et al.Probability density function of day-ahead wind power forecast errors based on power curves of wind farms[J].Proceedings of the CSEE,2013,33(34):136-144(in Chinese).
[19]赵希人,李大为,李国斌,等.电力系统负荷预报误差的概率密度函数建模[J].自动化学报,1993,19(5):562-568.Zhao Xiren,Li Dawei,Li Guobin,et al.Probability density function modeling for power system load forecasting errors[J].Acta Automatica Sinica,1993,19(5):562-568(in Chinese).
[20]张沈习,李珂,程浩忠,等.考虑相关性的间歇性分布式电源选址定容规划[J].电力系统自动化,2015,39(8):53-58,140.Zhang Shenxi,Li Ke,Cheng Haozhong,et al.Optimal siting and sizing of intermittent distributed generator considering correlations[J].Automation of Electric Power Systems,2015,39(8):53-58,140(in Chinese).
[21]Liu Z,Wen F,Ledwich G.Optimal siting and sizing of distributed generators in distribution systems considering uncertainties[J].IEEE Transactions on Power Delivery,2011,26(4):2541-2551.
[22]Deb K,Pratap A,Agarwal S,et al.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[23]Baran M E,Wu F F.Optimal capacitor placement on radial distribution systems[J].IEEE Transactions on Power Delivery,1989,4(1):725-734.