Research On Optimal Allocation Of Energy Storage System For Power System Integrated With Large-scale Wind Power

The problems of energy have always been the focus of world.With the gradual depletion of fossil energy and the keeping deterioration of global ecological environment,the transformation of energy structure is imperative.Renewable energy has an immense potential for utilization with the advantages of abundant reserves,clean and environmental friendly.Wind energy is a new energy with the more mature technology and develops rapidly.However,due to the characteristics of wind resource,wind power shows strong volatility and uncertainty,the capacity of large-scale wind power utilization is insufficient.The rapid development of wind power in China is restricted.And it will cause serious influence on power quality and the stable operation of the power system with large-scale wind power integration.The quick responsiveness ability of energy storage system is one of the effective ways to improve the problem.The application of large-scale energy storage system provides a new way to improve the large scale wind power integration.Energy storage equipment is expensive due to the limitation of the technical conditions.In order to make full use of energy storage system,it has practical value to investigate optimal allocation of energy storage system for power system integrated with large-scale wind power.Works of this thesis are as follows:(1)Based on the analysis of volatility and uncertainty of wind power,a short-term wind power prediction based on Wavelet Packet Decomposition(WPD)and Relevance Vector Machine(RVM)is proposed.The validity of the method is verified by data testing.And it lays the foundation for the follow-up study.In view of the optimal allocation of energy storage system for power system integrated with large-scale wind power,this thesis started from two aspects: smoothing the fluctuation and improving the uncertainly of wind power(2)Research on optimal allocation of energy storage system for smoothing the fluctuation of wind power,a sliding average filter is used to determine the expected output power of wind and energy storage system.The Variational Mode Decomposition(VMD)is used to decompose the expected power of energy storage system into subsequences of low to high frequencies,and use battery and supercapacitor to stabilize low-frequency fluctuation and high-frequency fluctuation respectively.On this basis,a hybrid energy storage optimization allocation model considering the investment cost of energy storage system and the cost of wind loss and wind power fluctuation lack is established.The Particle Swarm Optimization(PSO)algorithm is used to solve the model,and this model can simultaneously optimize the demarcation point and the hybrid energy storage system capacity.(3)Research on optimal allocation of energy storage system by considering the uncertainty of wind power.In order to improve the fitting accuracy of wind power forecast error,an improved generalized error distribution model is adopted to fit the error probability density distribution.An optimal allocation model of energy storage system considering conventional unit cost,energy storage system cost and risk cost is established.Based on the Chance Constrained Goal Programming(CCGP),the inequality constraints with uncertain variables are transformed into the form of CCGP,and the CCGP model of energy storage optimization allocation is established.The Artificial Bee Colony(ABC)algorithm is applied to solve the model,the accuracy of the error probability density distribution model and the validity of model are verified by the analysis.