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Studies On Control Strategy And Capacity Optimized Configuration Of Hybrid Energy Storage System For Wind Power Smoothing

Posted on:2020-03-06Degree:DoctorType:Dissertation
Country:ChinaCandidate:J WuFull Text:PDF
GTID:1362330602966403Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
The inherent intermittence,fluctuation and uncertainty of wind energy make the output power of wind farm unable to meet the grid-connected fluctuation standard directly,which affects the large-scale development of wind power generation.Considering that energy storage system(ESS)has bidirectional power throughput capability,fast response speed and high controllability,it is a reliable solution to smooth the fluctuation of wind power output and improve the grid-connected capability of wind power by configuring ESS for grid-connected wind farms.This paper deeply analyzes the development status of energy storage in wind power fluctuation related fields,and selects battery-super capacitor HESS as the carrier to suppress wind power fluctuations.Research on wind power fluctuation smooth control,HESS energy management and optimal allocation of storage capacity are carried out in this paper.The main research contents and contributions include:(1)In this paper,a wind power fluctuation decomposition and allocation method with scene adaptive ability is proposed.Firstly,the amplitude-frequency characteristics of wind power are analyzed,and the distribution of wind energy in different frequency bands is determined to guide the design of mitigation strategy;secondly,according to the power fluctuation characteristics of different wind power scenes,adaptive wavelet packet decomposition method is designed to decompose wind power into grid-connected power and HESS power commands in line with grid-connected standards;finally,the power commands of battery and super capacitor are determined by the two-stage power command allocation method which includes the primary allocation based on the charge-discharge characteristics of HESS and the secondary correction based on the fuzzy control of energy storage SOC.The proposed adaptive decomposition and allocation method can achieve the optimal decomposition of wind power and the rational allocation of HESS power commands,which provides a control basis for the subsequent HESS optimization configuration model.(2)The paper proposes a real-time wind power fluctuation smoothing method considering control response delay.Contrary to the adaptive wavelet packet smoothing method which relies on historical data,the real-time smoothing method can cope with the unknown future trend of wind power and take full consideration of the response delay of the control system.Firstly,the response delay of each link of the HESS is quantitatively analyzed,and then the kalman filter algorithm with the fuzzy optimization of the filter parameters which following the variation of wind power is adopted to determine the grid-connected power and HESS power commands.Finally,the rolling on-line distribution of power commands is realized by MPC method based on the SOC of HESS.The proposed control method can meet the requirements of real-time on-line control and is more close to the requirements of wind power fluctuation smoothing in engineering practice.(3)A capacity optimization configuration model of HESS considering battery cycle life is established,and an optimal solution scheme for joint solution of optimal decomposition point of HESS power commands and HESS capacity is proposed.Quantitative model of battery cycle life is established to analyze the impact of battery life attenuation on the comprehensive cost of ESS.In order to solve the capacity optimization configuration model of HESS,which uses wavele packet decomposition to suppress wind power fluctuation,the optimal decomposition point of HESS power commands and the capacity configuration of HESS are solved jointly.On this basis,the capacity optimization configuration models of single battery energy storage and single super capacitor energy storage are established respectively,and compared with the battery-supercapacitor HESS to verify the technical and economic advantages of HESS in smoothing wind power fluctuation.(4)An algorithm for analyzing typical operation curves of ESS is proposed to improve the calculation efficiency and accuracy of the capacity optimization model of ESS.In order to solve the problems of poor calculation accuracy of ESS configuration scheme based on typical daily data and poor calculation efficiency of ESS configuration scheme based on annual operation data,k-means clustering algorithm is used to extract typical data sets from annual operation curve of ESS as input data of the capacity optimization model of ESS,and the clustering number and initial cluster centers of k-mean clustering are determined from annual operation curve of ESS by cloud transformation.The proposed typical curve analysis algorithm can overcome the disadvantage of the traditional k-means clustering that requires pre-specified number of clusters,and can also solve the stability problem caused by the randomness of the initial clustering center.At the same time,the results of the proposed algorithm can be used as the input data of the ESS configuration model to achieve a balance between the calculation accuracy and efficiency of the solution process compared with the typical daily data and the annual operation data.The researches above make progresses on improving the quality of grid-connection wind power,optimizing the effect of HESS energy management,perfecting the capacity optimization model of HESS and improving the accuracy and efficiency of the ESS optimization model solving process,and provides a new perspective for the control and configuration of HESS for wind power smoothing.
Keywords/Search Tags:wind power generation, hybrid energy storage system, wavelet packet decomposition, fuzzy control, kalman filter, battery life, k-means clustering
PDF Full Text Request
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