Distributed Wind Power and Photovoltaic Energy Storage Capacity Configuration Method under Big Data

Abstract

In the past, the large-scale battery energy storage system was used for volume configuration, and its scheme was fitted by non-parameter estimation and curve fitting. Only one analysis scenario was used, leading to unsatisfactory capacity configuration results under different weather conditions. In order to solve this problem, a distributed configuration method of wind power and photovoltaic energy storage capacity under big data was proposed. The topological structure of distributed wind power and photovoltaic energy storage is analyzed, and the energy state of the energy storage device is adjusted to operate under different scenarios. The objective function is calculated to determine the weight value of fluctuation quantity, design the overall layout plan of energy storage across time scales, use the big data analysis method to solve the objective functions, and design the energy storage capacity configuration process. According to the experimental results, the capacity configuration results of this method in fog, heavy rain, and thunderstorm are consistent with the expected configuration results and have a good configuration effect.