摘要
Due to the growing penetration of renewable energies(REs)in integrated energy system(IES),it is imperative to assess and reduce the negative impacts caused by the uncertain REs.In this paper,an unscented transformation-based mean-standard(UT-MS)deviation model is proposed for the stochastic optimization of cost-risk for IES operation considering wind and solar power correlated.The unscented transformation(UT)sampling method is adopted to characterize the uncertainties of wind and solar power considering the correlated relationship between them.Based on the UT,a mean-standard(MS)deviation model is formulated to depict the trade-off between the cost and risk of stochastic optimization for the IES optimal operation problem.Then the UT-MS model is tackled by a multi-objective group search optimizer with adaptive covariance and Levy flights embedded with a multiple constraints handling technique(MGSO-ACL-CHT)to ensure the feasibility of Peratooptimal solutions.Furthermore,a decision-making method,improved entropy weight(IEW),is developed to select a final operation point from the set of Perato-optimal solutions.In order to verify the feasibility and efficiency of the proposed UT-MS model in dealing with the uncertainties of correlative wind and solar power,simulation studies are conducted on a test IES.Simulation results show that the UT-MS model is capable of handling the uncertainties of correlative wind and solar power within much less samples and less computational burden.Moreover,the MGSOACL-CHT and IEW are also demonstrated to be effective in solving the multi-objective UT-MS model of the IES optimal operation problem.
Due to the growing penetration of renewable energies(REs) in integrated energy system(IES),it is imperative to assess and reduce the negative impacts caused by the uncertain REs.In this paper,an unscented transformation-based mean-standard(UT-MS) deviation model is proposed for the stochastic optimization of cost-risk for IES operation considering wind and solar power correlated.The unscented transformation(UT)sampling method is adopted to characterize the uncertainties of wind and solar power considering the correlated relationship between them.Based on the UT,a mean-standard(MS) deviation model is formulated to depict the trade-off between the cost and risk of stochastic optimization for the IES optimal operation problem.Then the UT-MS model is tackled by a multi-objective group search optimizer with adaptive covariance and Levy flights embedded with a multiple constraints handling technique(MGSO-ACL-CHT) to ensure the feasibility of Peratooptimal solutions.Furthermore,a decision-making method,improved entropy weight(IEW),is developed to select a final operation point from the set of Perato-optimal solutions.In order to verify the feasibility and efficiency of the proposed UT-MS model in dealing with the uncertainties of correlative wind and solar power,simulation studies are conducted on a test IES.Simulation results show that the UT-MS model is capable of handling the uncertainties of correlative wind and solar power within much less samples and less computational burden.Moreover,the MGSOACL-CHT and IEW are also demonstrated to be effective in solving the multi-objective UT-MS model of the IES optimal operation problem.
基金
supported by the State Key Program of National Natural Science Foundation of China(No.51437006)
the Fundamental Research Funds for the Central Universities and the China Postdoctoral Science Foundation(No.2017M622690).
作者简介
Mengshi LI received the M.Sc.(Eng.)(with distinction)and Ph.D.degrees in electrical engineering and electronics from the University of Liverpool,Liverpool,U.K.,in 2005 and 2010,respectively.He is currently an associate professor with the School of Electric Power Engineering,South China University of Technology,Guangzhou,China.His research interests include computational intelligence and their applications in power systems.mengshili@scut.edu.cn;Jiehui ZHENG obtained his B.E.degree in Electrical Engineering from Huazhong University of Science and Technology,Wuhan,China,in 2012,and his Ph.D.degree at the same area in South China University of Technology(SCUT),Guangzhou,China in 2017.He is currently a research assistant in SCUT.His research interests include optimization algorithms,decision making methods and their applications on integrated energy systems.zhengjh@scut.edu.cn;Yanni KOU received the B.E.degree in Electrical Engineering from Huazhong University of Science and Technology,Wuhan,China,in 2014.She obtained the M.S.degree at the same area in South China University of Technology,Guangzhou,China.Her research interests include stochastic optimization,multi-objective optimization and its application on integrated energy systems.epyn.kou@mail.scut.edu.cn;Qinghua WU obtained an M.Sc.(Eng)degree in Electrical Engineering from Huazhong University of Science and Technology,Wuhan,China,in 1981.From 1981 to 1984,he was appointed Lecturer in Electrical Engineering in the University.He obtained a Ph.D.degree in Electrical Engineering from The Queen’s University of Belfast(QUB),Belfast,U.K.in 1987.He worked as a Research Fellow and subsequently a Senior Research Fellow in QUB from 1987 to 1991.He joined the Department of Mathematical Sciences,Loughborough University,Loughborough,U.K.in 1991,as a Lecturer,subsequently he was appointed Senior Lecturer.In September,1995,he joined The University of Liverpool,Liverpool,U.K.to take up his appointment to the Chair of Electrical Engineering in the Department of Electrical Engineering and Electronics.Now he is with the School of Electric Power Engineering,South China University of Technology,Guangzhou,China,as a Distinguished Professor and the Director of Energy Research Institute of the University.Professor Wu has authored and coauthored more than 440 technical publications,including 220 journal papers,20 book chapters and 3 research monographs published by Springer.He is a Fellow of IEEE,Fellow of IET,Chartered Engineer and Fellow of InstMC.His research interests include nonlinear adaptive control,mathematical morphology,evolutionary computation,power quality and power system control and operation.wuqh@scut.edu.cn
