Multi-Objective Optimization Scheduling of Household Energy Based on Goose Algorithm

The incorporation of photovoltaic energy storage systems has introduced new avenues for enhancing household energy supply, thereby enabling a greater integration of re-newable energy sources within residential power consumption. This article proposes a multi-objective optimization scheduling model for household energy management that employs the goose algorithm. The primary objective of this model is to optimize and minimize both household electricity costs and carbon emissions while ensuring user satisfaction. The model comprises two crucial components. Firstly, an optimization scheme for the photovoltaic energy storage system that efficiently manages its charging and discharging operations to achieve a reduction in economic costs. Secondly, an optimization scheme for scheduling household appliance usage periods that strategically allocates appliance operation to meet multiple objectives. Through empirical analysis, the optimized scheduling of the photovoltaic energy storage system demonstrates a potential 6.17% reduction in economic expenditures, while the optimization of appliance usage periods showcases an 11.28% decrease in economic costs and a 0.85% reduction in carbon emissions costs.