Capacity Optimization of Off-Grid Wind-Solar-Diesel-Battery System Based on Improved Whale Optimization Algorithm

Abstract

In the early stage of microgrid construction, reasonable allocation of power equipment capacity based on regional resource characteristics can not only effectively solve the power supply reliability problem caused by wind and solar uncertainty, but also improve the system's economy and environmental protection. This design constructs a off-grid wind-solar-diesel-storage microgrid, establishes a multiobjective optimization model comprehensively considering costs of energy, carbon emissions, and the loss probability of power supply. The energy control strategy of the battery priority tracking load was adopted and the operating conditions of each part were analyzed under 8 working conditions based on net load and battery SOC status. After testing a series of intelligent optimization algorithms, the whale optimization algorithm was improved through adaptive t-distribution, dynamic selection strategy, and differential change strategy. By verifying and analyzing the data from a hospital complex in Montagu, California, USA, it is evident that the established model and control strategy can effectively meet the load demand and achieve the optimal equipment capacity ratio. The Improved Whale Optimization Algorithm (IWOA) demonstrates higher solution accuracy and faster convergence speed in optimization calculations.