Research On Optimal Strategy Of Output Power Command For Wind Power Based On Multi-element Composite Energy Storage

Since China entered the “Thirteenth Five-Year Plan”,the energy structure has been continuously optimized and the installed capacity of wind power has been increasing year by year.Clean renewable new energy,including wind power,has been highly valued at home and abroad.Wind energy is one of the most abundant reserves which can be recycled,and environmentally friendly.However,the randomness and intermittent nature of wind power generation have become the major bottlenecks restricting the installation of wind turbines.The composite energy storage system composed of various energy storage media integrates the characteristics of a composite energy storage medium.With high energy density and high power density,it can effectively smooth wind power fluctuations,improve wind power absorption capacity,and optimize power output.In this paper,the requirements of wind power grid connection are used as the scale of wind power output.From the perspective of multiple time scales of wind power,the output power fluctuation and randomness of wind turbines are analyzed,and the necessity of optimizing power output is clarified.Based on the characteristics of multiple time scales of wind power,a multivariate composite energy storage system was proposed,which consisted of compressed air energy storage,super capacitors,and lithium-ion batteries.The characteristics of the three types of energy storage methods were compared and the feasibility of establishing a multivariate composite energy storage system was verified and the basis for the selection of energy storage devices was provided.It is necessary to provide more accurate prediction of wind speed in order to organize and manage the volatility of wind power in advance and coordinate the allocation of energy storage instructions.Short-term prediction of wind speed is performed,based on on-site wind speed sampling data of a wind farm.the influence of meteorological factors on wind speed prediction is analyzed based on the least squares support vector machine regression prediction model and particle swarm optimization algorithm.The LSSVM parameters affecting the accuracy of the prediction model are analyzed.The PSO algorithm is used tooptimize the parameters of the LSSVM.The prediction model is established to verify by simulation experiment.The average error rate of the wind speed predicted by the PSO optimal model is reduced and improves prediction accuracy.In order to smooth the fluctuation of wind power,optimize the power output,and use the improved EMD method to construct the control command of the multi-element composite energy storage system.The characteristics of the intrinsic mode function of the nonlinear signal can be adaptively extracted by the empirical mode decomposition(EMD),and focusing on the difficulty of determining the screening criteria existing in the EMD decomposition process,the improved EMD decomposition algorithm is used to decompose the output power of the wind power,and the power output instructions of the multiple-composite energy storage are formed through recombination of modal components.The simulation experiment result showed that through the optimized strategy of multivariate composite energy storage system,the optimized output of wind power output was completed,the composite energy storage instruction was effectively allocated,and the energy storage system achieved smooth output and the output power quality of wind power has been improved.