Optimal Scenario Generation Algorithm for Multi-objective Optimization Operation of Active Distribution Network

详细信息    查看官网全文

• 英文论文题名：Optimal Scenario Generation Algorithm for Multi-objective Optimization Operation of Active Distribution Network
• 论文作者：Lizhen Wu ; Libo Jiang ; Xiaohong Hao
• 英文论文作者：Lizhen Wu ; Libo Jiang ; Xiaohong Hao ; College of Electrical and Information Engineering ; Lanzhou University of Technology
• 年：2017
• 作者机构：College of Electrical and Information Engineering,Lanzhou University of Technology;
• 英文论文关键词：Active distribution network ; Scenario generation ; Wasserstein distance ; K-means cluster ; Tabu search artificial bee colony algorithm
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：TM73
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：6
• 文件大小：161k
• 原文格式：D
• 会议级别：全国

摘要

Considering the uncertain and stochastic of intermittent distributed generations(DGS) in active distribution network(ADN), a scenario method using Wasserstein distance metric and K-means cluster scenes reduction technology to generate optimal scene is proposed in this paper. So the stochastic problem is transformed into a deterministic problem. The multi-scenario tree models of wind-photovoltaic-load are built. A multi-objective optimization mathematical model of active distribution network containing intermittent DGS is established, which includes objectives that are the annual profits, the total active power losses and the voltage deviations of the bus, and considering active management characteristic. The tabu search artificial bee colony algorithm is used to solve the optimization problems. The simulation results show that the optimal scenes based on the Wasserstein distance indicators and K-means cluster technique reflect the random feature of distributed generation active power output more accurately. Finally, the simulation analysis of IEEE33-bus distribution test system is carried out to verify the effectiveness and feasibility of the proposed method.
Considering the uncertain and stochastic of intermittent distributed generations(DGS) in active distribution network(ADN), a scenario method using Wasserstein distance metric and K-means cluster scenes reduction technology to generate optimal scene is proposed in this paper. So the stochastic problem is transformed into a deterministic problem. The multi-scenario tree models of wind-photovoltaic-load are built. A multi-objective optimization mathematical model of active distribution network containing intermittent DGS is established, which includes objectives that are the annual profits, the total active power losses and the voltage deviations of the bus, and considering active management characteristic. The tabu search artificial bee colony algorithm is used to solve the optimization problems. The simulation results show that the optimal scenes based on the Wasserstein distance indicators and K-means cluster technique reflect the random feature of distributed generation active power output more accurately. Finally, the simulation analysis of IEEE33-bus distribution test system is carried out to verify the effectiveness and feasibility of the proposed method.

引文

[1]Y.You,D.Liu,W.Yu,et al,Technology and its trends of active distribution network,Automation of Electric power Systems,Vol.36,No.18,10-16,2012.
    [2]X.Zhang,H.Z.Cheng,F.Chen,et al,Multi-objective distributed generation planning considering active management,Journal of Shanghai Jiaotong University,Vol.48,No.9,1231-1238,2014.
    [3]X.Wei.,X.Y.Qiu,X.Y.Li,et al,Multi-objective reactive power optimization in power system with farm,Power system protection and control,Vol.38,No.17,107-111,2010.
    [4]A.K.Fard,T.Niknam,Optimal stochastic capacitor placement problem from the reliability and cost views using firefly algorithm,IET Measurement and Technology,Vol.8,No.5,260-269,2014.
    [5]C.Wang,Y.Gao.Probability statistics based reactive power optimization of distribution network containing intermittent distributed generations,Power System Technology,Vol.38,No.4,1032-1037,2014.
    [6]D.Guzmán,M.Ahmed,A.Motaleb,et al.On the capacity factor of distributed wind generation in droop-regulated microgrids,IEEE Transactions on power systems,Vol.28,No.2,1738-1746,2013.
    [7]L.V.Abreu,M.E.Khodayar,M.Shahidehpour,et al,Risk-constrained coordination of cascaded hydro units with variable wind power generation,IEEE Transactions on Sustainable Energy,Vol.3,No.3,359-368,2012.
    [8]J.H.Li,H.Wei,and D.Mo,Asymptotically optimal scenario analysis and wait-and-see model for optimal power flow with wind power,Proceedings of the CSEE,Vol.32,No.22,15-24,2012.
    [9]Y.Y.Zou,Y.Li,Synergetic dispatch models of a Wind/PV/Hydro virtual power plant based on representative scenario set,Power System Technology,Vol.39,No.7,1855-1859,2015.