Study on Stochastic Optimal Scheduling Strategy for Renewable Microgrid Based on Simplified Particle Swarm Optimization Algorithm
Optimal scheduling of high-percentage renewable energy microgrids is of great significance in promoting the green transition of new power systems.Aiming at the problem of uncertainty and stochasticity of microgrids due to environmental factors such as weather conditions,this paper proposes a stochastic optimal scheduling strategy for renewable microgrids based on a simplified particle swarm optimization algorithm with the goal of minimizing the operating cost of microgrids.Firstly,mathematical models of power devices such as wind turbine,photovoltaic system,fuel cell and microturbine are established and their performances are explained.Secondly,the simplified particle swarm optimization algorithm model and its execution process are designed.Finally,the hourly predicted output power of the four microsource models established above is used to optimize the operating cost of the microgrid,and the optimal fitness solution with a fitness value of 23 and an effective control of the operating cost of the microgrid is obtained.This study provides a more robust solution by considering the load demand and making decisions on the optimal management of renewable energy in microgrids.
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