Research on Fine-Tuning Methods for Residential Load Based on Electricity Consumption Behavior Profiles

The refined regulation of residential electricity load is a key measure for achieving demand-side management. To enhance the targeted nature of residential load regulation, a refined residential load regulation method based on electricity consumption behavior profiling is proposed. Firstly, the user electricity consumption behavior profiling scheme is elaborated. Three features, namely load rate, peak-valley difference rate, and peak average power, are extracted from the user adjustable load curve to depict the characteristics of user electricity consumption behavior. Secondly, an improved particle swarm optimization algorithm is constructed to solve the refined residential load regulation scheme under multi-objective conditions. The electricity consumption behavior features are input into the improved particle swarm optimization algorithm, and the optimal solution set for user electricity consumption periods is output, achieving refined residential load regulation. Experimental results show that after refined residential load regulation, the peak values of two electricity consumption periods are significantly reduced, presenting two continuous concentrated electricity consumption time periods, effectively reducing the user′s electricity load.