A Combined Dispatch Model of Power Load Satisfaction and Comfort Based on Genetic Algorithm

• Published in: 2024 9th International Conference on Intelligent Computing and Signal Processing (ICSP) pp. 1703 - 1708
• Main Authors: Zhang, Fan, He, Shan, Lin, Xiaoming, Zhao, Yuming, Tang, Jianlin, Li, Yan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 19.04.2024
• Subjects: Analytical models; Atmospheric modeling; demand response; Distribution networks; Electricity; Filling; genetic algorithm; Genetic algorithms; Load modeling; peak cutting and valley filling; satisfaction of electricity consumption; Signal processing algorithms; Simulation; Tariffs; time-of-use tariff
• DOI: 10.1109/ICSP62122.2024.10743545

In recent years, the demand for electricity of the whole society has been increasing rapidly, and the power suppliers have been unable to meet the power consumption demand of all users. In order to effectively balance the relationship between the power suppliers and users, and ensure the satisfaction of suppliers and the experience of users, a load optimization model is proposed. Based on Time-of-use tariff, the model comprehensively considers the income satisfaction of the power supplier, the satisfaction of the consumer's electricity expenditure and the satisfaction of electricity consumption, and takes Time-of-use tariff and elastic load as decision variables. Finally, the multi-objective function of residential user price response under Time-of-use tariff mechanism is constructed, and the genetic algorithm is used to optimize the model under various constraints. The experimental results show that the load optimization algorithm can effectively reduce the load curve of residential electricity, and can carry out peak cutting and valley filling on the premise of ensuring the satisfaction of users and power supplier.