Home energy management optimization method considering potential risk cost

Abstract With the popularization of smart power consumption technology, users can optimize the use of electrical equipment through a home energy management system (HEMS), thereby reducing electricity costs while maintaining a degree of comfort. In this study, we established an HEMS with distributed power and an electrical vehicle, describing a multi-objective optimization model with risk cost and risk index constraints, which have not been considered in previous work. The problem can be solved with improved genetic methods. First, this study establishes a mathematical model for the typical electrical equipment of specific smart home users. On this basis, with the user’s electricity consumption cost and risk index being considered, we propose a multi-objective optimization model of the user’s overall satisfaction and the corresponding constraints of the various devices in the home. This model is regarded as a two-stage optimization considering both electricity cost and power fluctuation. Finally, we verify the effectiveness of the model and the optimization algorithm through example simulations