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Maximum entropy based probabilistic load flow calculation for power system integrated with wind power generation 被引量:8

Maximum entropy based probabilistic load flow calculation for power system integrated with wind power generation
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摘要 Distributed generation including wind turbine(WT) and photovoltaic panel increases very fast in recent years around the world, challenging the conventional way of probabilistic load flow(PLF) calculation. Reliable and efficient PLF method is required to take this chage into account.This paper studies the maximum entropy probabilistic density function reconstruction method based on cumulant arithmetic of linearized load flow formulation,and then develops a maximum entropy based PLF(MEPLF) calculation algorithm for power system integrated with wind power generation(WPG). Compared with traditional Gram–Charlier expansion based PLF(GC-PLF)calculation method, the proposed ME-PLF calculation algorithm can obtain more reliable and accurate probabilistic density functions(PDFs) of bus voltages and branch flows in various WT parameter scenarios. It can solve thelimitation of GC-PLF calculation method that mistakenly gains negative values in tail regions of PDFs. Linear dependence between active and reactive power injections of WPG can also be effectively considered by the modified cumulant calculation framework. Accuracy and efficiency of the proposed approach are validated with some test systems. Uncertainties yielded by the wind speed variations, WT locations, power factor fluctuations are considered. Distributed generation including wind turbine(WT) and photovoltaic panel increases very fast in recent years around the world, challenging the conventional way of probabilistic load flow(PLF) calculation. Reliable and efficient PLF method is required to take this chage into account.This paper studies the maximum entropy probabilistic density function reconstruction method based on cumulant arithmetic of linearized load flow formulation,and then develops a maximum entropy based PLF(MEPLF) calculation algorithm for power system integrated with wind power generation(WPG). Compared with traditional Gram–Charlier expansion based PLF(GC-PLF)calculation method, the proposed ME-PLF calculation algorithm can obtain more reliable and accurate probabilistic density functions(PDFs) of bus voltages and branch flows in various WT parameter scenarios. It can solve thelimitation of GC-PLF calculation method that mistakenly gains negative values in tail regions of PDFs. Linear dependence between active and reactive power injections of WPG can also be effectively considered by the modified cumulant calculation framework. Accuracy and efficiency of the proposed approach are validated with some test systems. Uncertainties yielded by the wind speed variations, WT locations, power factor fluctuations are considered.
出处 《Journal of Modern Power Systems and Clean Energy》 SCIE EI 2018年第5期1042-1054,共13页 现代电力系统与清洁能源学报(英文)
基金 supported by National Natural Science Foundation of China(No.51625702,No.51377117,No.51677124) National High-tech R&D Program of China(863Program)(No.2015AA050403)
关键词 Maximum ENTROPY PROBABILISTIC load flow PROBABILITY density function WIND power generation MONTE Carlo simulation Maximum entropy Probabilistic load flow Probability density function Wind power generation Monte Carlo simulation
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  • 1胡泽春,王锡凡,张显,王秀丽.考虑线路故障的随机潮流[J].中国电机工程学报,2005,25(24):26-33. 被引量:78
  • 2Usaola J. Probabilistic load flow with correlated windpower injections[J]. Electric Power Systems Research,2010,80(5): 528-536.
  • 3Aboreshaid S,Billinton R. Probabilistic evaluation ofvoltage stability[J] . IEEE Transactions on PowerSystems, 1999, 14(1): 342-347.
  • 4Borkowska B . Probabilistic load flow[J] . IEEETransactions on Power App. Syst,1974,93(3): 752-759.
  • 5Chun-Lien S. Probabilistic load-flow computation usingpoint estimate method[J]. IEEE Transactions on PowerSystems, 2005,20(4): 1843-1851.
  • 6Caramia P, Carpinelli G,Varilone P. Point estimateschemes for probabilistic three-phase load flow[J]. Electric Power Systems Research, 2010,80(2):168-175.
  • 7Yu H? Chung CY,WongKP,et al Probabilistic loadflow evaluation with hybrid Latin hypercube sampling andcholesky decomposition [J]. IEEE Transactions on PowerSystems, 2009, 24(2): 661-667.
  • 8Pei Z,Lee S T. Probabilistic load flow computation usingthe method of combined cumulants and Gram-Charlierexpansion[J]. IEEE Transactions on Power Systems,2004,19(1): 676-682.
  • 9Usaola J. Probabilistic load flow in systems with windgeneration[J]. Generation, Transmission & Distribution,IET, 2009,3(12): 1031-1041.
  • 10Tian WD,Sutanto D, Lee Y B, et al Cumulant basedprobabilistic power system simulation using Laguerrepolynomials[J]. IEEE Transactions on Energy conversion?1989, 4(4): 567-574.

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