Research on Optimal Scheduling of Wind and Solar Energy Storage Microgrid Based on Data Set

Abstract

The application of big data speeds up the construction and development of China's power grid and makes the work of the power grid more efficient than without it. We gathered historical data sets to establish self-learning, self-optimization, and self-adjustment strategies of the microgrids wind power and solar energy storage. We propose a design to realize an optimized system that combines wind and solar power generation with energy storage. Experimental results show that the combination of ultracapacitors and batteries can store energy with different grid parameters based on combined historical data for optimization. It improves the accurate capacity optimization of the energy storage system, meets the demand of output power capacity, and realizes the safety and economy of the whole power grid.