Research On Power Fluctuation Control Strategy Of Campus Photovoltaic Power Generation System Based On Energy Storage

Photovoltaic power generation can alleviate the problem of energy shortage,and distributed microgrids can reduce the power consumption in the transmission and distribution process,but as the installed capacity of photovoltaics increases,the impact on the large power grid is increasingly prominent(such as power fluctuations).Therefore,in response to this problem,this paper takes the campus light storage combined power generation system as the research object,and takes the hybrid energy storage system of lithium battery and super capacitor combination to suppress the photovoltaic output power fluctuation as the research center,and proposes two control strategies to suppress the power fluctuation.Make the grid-connected power fluctuation of the optical storage system within the allowable range of the power grid,thereby improving the power quality:(1)The smoothing coefficient changes according to the degree of power fluctuation,considers the state of charge of the energy storage,and allocates the power of the lithium battery and super capacitor according to the energy storage SOC value,so as to achieve the purpose of suppressing the power fluctuation.(2)The second control strategy adopts the wavelet packet decomposition method to suppress:PV output power will fluctuate when connected to the grid,and the power that does not meet the photovoltaic grid-connected fluctuation requirements will be borne by the hybrid energy storage.The wavelet packet decomposition method is selected to decompose it according to Lithium battery features high energy density,low power density,low supercapacitor energy density and high power density.The low-frequency and high-frequency powers are borne by the lithium battery and supercapacitor respectively,while considering the state of charge and capacity optimization of energy storage.Power fluctuations are smooth.(3)Based on the prediction of photovoltaic power,it analyzes the degree of fluctuation of photovoltaic power in the future,and selects a suitable power fluctuation suppression strategy:first,improve the particle swarm optimization(Particle Swarm Optimization,PSO)to optimize the Radial Basis Function(RBF)The algorithm predicts the photovoltaic power,and compares with other algorithms to find the superiority of this algorithm,and the prediction accuracy is higher.Then use the campus photovoltaic power station data to carry out simulation experiments.The results show that both control strategies achieve the power fluctuation suppression goal.The grid-connected power of the first control strategy changes according to the fluctuation of the output power of the photovoltaic power station,which is adaptive,but does not consider the economy of energy storage;the second control strategy uses wavelet packet decomposition to consider the energy storage Economical.Comprehensive analysis considers that the first control strategy is suitable for application when the power fluctuation is small,and the second control strategy is suitable for use when the power fluctuation is large.