多电压等级不平衡主动配电网电压无功自适应多目标协调优化
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摘要
高间歇性DG持续大量接入给传统配电网电压无功控制带来严峻挑战。利用新兴DG与传统设备(如电容器、OLTC等)进行电压无功协调控制显得尤为重要。然而,现有协调控制研究多采用负荷与出力的日前预测,并基于平衡网络模型和单一电压等级假设,导致其控制结果不合理或不可行。为应对上述技术挑战,基于主动配电网双向信息通信并采用自适应动态权重策略,提出一种含中压(三相三线)和低压(三相四线)的多电压等级不平衡主动配电网电压无功自适应协调优化控制策略。通过中压侧传统三角形开关电容器与低压侧新兴分布式光伏逆变器的协调控制,实现网损、电压幅值、不平衡度、电容器动作成本及光伏逆变器出力成本的综合运行优化。为有效求解上述配网最优潮流问题,采用改进直接法潮流和粒子群算法进行联合求解。最后,基于某澳大利亚真实配电网开展24 h多场景仿真,以验证所提电压无功控制的可行性、有效性及优越性。
Increasing penetration of intermittent distributed generations(DGs) raises great challenge to distribution volt/var management. Coordinated volt/var control by emerging DGs and traditional devices(e.g. capacitors, on-load tap changers(OLTCs) etc.) is essential. However, existing coordinated volt/var control studies are mainly based on day-ahead load and generation forecasts, fixed optimization weights, balanced configuration and single-voltage level, leading to unreasonable control solutions. Based on the increasing availability of bi-way information and communication infrastructures, a real-time coordinated volt/var control strategy with adaptive optimization weights for integrated 3-wire MV and 4-wire LV radial distribution networks is proposed. By coordinating the traditional MV delta switched capacitors and the emerging LV distributed PV inverters, operation performance including network losses, voltage balance and magnitude profiles, as well as operation costs of capacitors and PV inverters are simultaneously optimized. To effectively and efficiently solve the proposed distribution optimal power flow problem, an improved direct load flow combined with a modified particle swarm optimization method is employed. Finally, detailed simulations on a real Australian distribution network over 24 hours are performed to prove the feasibility, effectiveness and superiority of the proposed adaptive and coordinated volt/var optimization strategy.
Increasing penetration of intermittent distributed generations(DGs) raises great challenge to distribution volt/var management. Coordinated volt/var control by emerging DGs and traditional devices(e.g. capacitors, on-load tap changers(OLTCs) etc.) is essential. However, existing coordinated volt/var control studies are mainly based on day-ahead load and generation forecasts, fixed optimization weights, balanced configuration and single-voltage level, leading to unreasonable control solutions. Based on the increasing availability of bi-way information and communication infrastructures, a real-time coordinated volt/var control strategy with adaptive optimization weights for integrated 3-wire MV and 4-wire LV radial distribution networks is proposed. By coordinating the traditional MV delta switched capacitors and the emerging LV distributed PV inverters, operation performance including network losses, voltage balance and magnitude profiles, as well as operation costs of capacitors and PV inverters are simultaneously optimized. To effectively and efficiently solve the proposed distribution optimal power flow problem, an improved direct load flow combined with a modified particle swarm optimization method is employed. Finally, detailed simulations on a real Australian distribution network over 24 hours are performed to prove the feasibility, effectiveness and superiority of the proposed adaptive and coordinated volt/var optimization strategy.
引文
[1]中华人民共和国国家发展和改革委员会.可再生能源发展“十三五”规划[R].北京:中华人民共和国国家发展和改革委员会,2016.
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[29]Doma M I.Particle swarm optimization in comparison with classical optimization for GPS network design[J].Journal of Geodetic Science,2013,3(4):250-257.
[30]Arefi A,Haghifam M R.A modified particle swarm optimization for correlated phenomena[J].Applied Soft Computing,2011,11(8):4640-4654.
[31]Fu Y,Zhou X,Su X.A comprehensive three-phase load flow method for integrated MV and LV distribution networks[C]//ISGT-Asia2017.Auckland:IEEE PES,2017.
[32]Teng J H.A direct approach for distribution system load flow solutions[J].IEEE Transactions on Power Delivery,2003,18(3):882-887.
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[37]Yan Y,Qian Y,Sharif H,et al.A survey on smart grid communication infrastructures:motivations,requirements and challenges[J].IEEECommunications Surveys&Tutorials,2013,15(1):5-20.
[38]Perth Solar City Annual Report.(2012-12-01).http://www.westernpower.com.au/networkprojects/smart Grid/Perth_Solar_City.ht ml.
[2]Liu M B,Canizares C A,Huang W.Reactive power and voltage control in distribution systems with limited switching operations[J].IEEE Transactions on Power Systems,2009,24(2):889-899.
[3]谭煌,张璐,丛鹏伟,等.计及分布式电源与电容器协调的配电网日前无功计划[J].电网技术,2014,38(9):2590-2597.Tan Huang,Zhang Lu,Cong Pengwei,et al.Day-ahead reactive power scheduling for distribution network considering coordination of distributed generation with capacitors[J].Power System Technology,2014,38(9):2590-2597(in Chinese).
[4]李智欢,段献忠.多目标进化算法求解无功优化问题的对比分析[J].中国电机工程学报,2010,30(10):57-65.Li Zhihuan,Duan Xianzhong.Comparison and analysis of multiobjective evolutionary algorithm for reactive power optimization[J].Proceedings of the CSEE,2010,30(10):57-65(in Chinese).
[5]Spring A,Wirth G,Becker G,et al.Grid influences from reactive power flow of photovoltaic inverters with a power factor specification of one[J].IEEE Transactions on Smart Grid,2014,7(3):1222-1229.
[6]Valverde G,Cutsem T V.Model predictive control of voltages in active distribution networks[J].IEEE Transactions on Smart Grid,2013,4(4):2152-2161.
[7]Turitsyn K,Sulc P,Backhaus S,et al.Options for control of reactive power by distributed photovoltaic generators[J].Proceedings of the IEEE,2010,99(6):1063-1073.
[8]Zhang L,Tang W,Liang J,et al.Coordinated day-ahead reactive power dispatch in distribution network based on real power forecast errors[J].IEEE Transactions on Power Systems,2016,31(3):2472-2480.
[9]刘斌,粟梅,林小峰,等.非隔离型H6桥单相光伏逆变器无功补偿调制及并网电流波形改善控制[J].中国电机工程学报,2016,36(4):1050-1060.Liu Bing,Li Mei,Lin Xiaofeng,et al.Reactive power compensation modulation and waveform-improving control strategy for non-isolated H6-type single-phase photovoltaic grid-connected inverter[J].Proceedings of the CSEE,2016,36(4):1050-1060(in Chinese).
[10]Yang F,Li Z.Improve distribution system energy efficiency with coordinated reactive power control[J].IEEE Transactions on Power Systems,2016,31(4):2518-2525.
[11]Hong Y Y,Luo Y F.Optimal var control considering wind farms using probabilistic load-flow and gray-based genetic algorithms[J].IEEE Transactions on Power Delivery,2009,24(3):1441-1449.
[12]Hong Y Y,Pen K L.Optimal VAR planning considering intermittent wind power using markov model and quantum evolutionary algorithm[J].IEEE Transactions on Power Delivery,2010,25(4):2987-2996.
[13]邢海军,程浩忠,张逸.基于多种主动管理策略的配电网综合无功优化[J].电网技术,2015,39(6):1504-1510.Xing Haijun,Cheng Haozhong,Zhang Yi.Reactive power comprehensive optimization in distribution network based on multiple active management schemes[J].Power System Technology,2015,39(6):1504-1510(in Chinese).
[14]Chen S,Hu W,Chen Z.Comprehensive cost minimization in distribution networks using segmented-time feeder reconfiguration and reactive power control of distributed generators[J].IEEETransactions on Power Systems,2016,31(2):983-993.
[15]Kim Y J,Kirtley J L,Norford L K.Reactive power ancillary service of synchronous DGs in coordination with voltage control devices[J].IEEE Transactions on Smart Grid,2017,8(2):515-527.
[16]Kim Y J,Ahn S J,Hwang P I,et al.Coordinated control of a DG and voltage control devices using a dynamic programming algorithm[J].IEEE Transactions on Power Systems,2013,28(1):42-51.
[17]王永杰,吴文传,张伯明,等.有功无功协调的主动配电网鲁棒电压控制[J].电力系统自动化,2016,40(9):29-34.Wang Yongjie,Wu Wenchuan,Zhang Boming,et al.Active and reactive power coordinated robust optimization for active distribution networks[J].Automation of Electric Power Systems,2016,40(9):29-34(in Chinese).
[18]Zheng W,Wu W,Zhang B,et al.Robust reactive power optimization and voltage control method for active distribution networks via dual time-scale coordination[J].IET Generation Transmission&Distribution,2017,11(6):1461-1471.
[19]Su X,Masoum M A S,Wolfs P J.Optimal PV inverter reactive power control and real power curtailment to improve performance of unbalanced four-wire LV distribution networks[J].IEEE Transactions on Sustainable Energy,2014,5(3):967-977.
[20]Su X,Masoum M A S,Wolfs P J.PSO and improved BSFS based sequential comprehensive placement and real-time multi-objective control of delta-connected switched capacitors in unbalanced radial MV distribution networks[J].IEEE Transactions on Power Systems,2015,PP(99):1-11.
[21]Kersting,William H.Distribution system modeling and analysis[M].New York,USA:CRC Press,2002.
[22]Pillay P,Manyage M.Definitions of voltage unbalance[J].Power Engineering Review IEEE,2001,21(5):49-51.
[23]Marler R T,Arora J S.The weighted sum method for multi-objective optimization:new insights[J].Structural&Multidisciplinary Optimization,2010,41(6):853-862.
[24]Parsopoulos K E,Vrahatis M N.On the computation of all global minimizers through particle swarm optimization[J].IEEETransactions on Evolutionary Computation,2004,8(3):211-224.
[25]Faria P,Soares J,Vale Z,et al.Modified particle swarm optimization applied to integrated demand response and DG resources scheduling[J].IEEE Transactions on Smart Grid,2013,4(1):606-616.
[26]Clerc M,Kennedy J.The particle swarm-explosion,stability,and convergence in a multidimensional complex space[M].New Jersey,USA:IEEE Press,2002.
[27]Del Valle Y,Harley R G,Venayagamoorthy G K.Comparison of enhanced-pso and classical optimization methods:a case study for statcom placement[C]//International Conference on Intelligent System Applications To Power Systems.Hersonissos,Greece:IEEE,2009:1-7.
[28]Valle Y D,Venayagamoorthy G K,Mohagheghi S,et al.Particle swarm optimization:basic concepts,variants and applications in power systems[J].IEEE Transactions on Evolutionary Computation,2008,12(2):171-195.
[29]Doma M I.Particle swarm optimization in comparison with classical optimization for GPS network design[J].Journal of Geodetic Science,2013,3(4):250-257.
[30]Arefi A,Haghifam M R.A modified particle swarm optimization for correlated phenomena[J].Applied Soft Computing,2011,11(8):4640-4654.
[31]Fu Y,Zhou X,Su X.A comprehensive three-phase load flow method for integrated MV and LV distribution networks[C]//ISGT-Asia2017.Auckland:IEEE PES,2017.
[32]Teng J H.A direct approach for distribution system load flow solutions[J].IEEE Transactions on Power Delivery,2003,18(3):882-887.
[33]Industrial controllers.National instruments TM website[EB/OL].[2017-12-14].http://www.ni.com/industrial-controller.
[34]Intel Hardware.Software and technologies for industrial automation,intel?webiste.[2017-12-14].https://www-ssl.intel.com/content/www/us/en/industrial-automation/productsand-solutions/hardware-sof tware-technologies.html.
[35]Process Control and Industrial Automation.Analog devices TMwebsite.[2017-12-14].http://www.analog.com/en/applications/markets/process-control-andindustrial-automation.html.
[36]Gungor V C,Sahin D,Kocak T,et al.A survey on smart grid potential applications and communication requirements[J].IEEE Transactions on Industrial Informatics,2013,9(1):28-42.
[37]Yan Y,Qian Y,Sharif H,et al.A survey on smart grid communication infrastructures:motivations,requirements and challenges[J].IEEECommunications Surveys&Tutorials,2013,15(1):5-20.
[38]Perth Solar City Annual Report.(2012-12-01).http://www.westernpower.com.au/networkprojects/smart Grid/Perth_Solar_City.ht ml.