Energy storage capacity optimization of residential buildings considering consumer purchase intention: A mutually beneficial way

Abstract

This paper aims to study the energy storage capacity allocation of residential buildings in a way of mutual benefit between investors and users. The relationship between the interests of investors and users can be established through consumer purchase intention. Firstly, this paper analyzes the running process of the energy storage system and constructs the charging state discrimination model. Secondly, based on the consumer utility theory, the purchase intention of users to such assets is analyzed, and the optimal capacity allocation is modeled by maximizing investors' profits. Finally, considering that the problem is NP-hard, particle swarm optimization algorithm based on inertial weight is applied to solve it. This article creatively and quantitatively depicts consumers' purchase intention, and takes into account the interests of users while carrying out capacity allocation, although from the perspective of maximizing the interests of investors. In the example analysis, after optimization, consumers' electricity bills are reduced by more than 50%, and investors' profits are increased by 1420 dollars per house, indicating: compared with the construction of traditional residential buildings or buildings with only photovoltaic system, the configuration of energy storage system can bring more profits to investors, users can also save a considerable amount of electricity bills, this paper also fits the requirements of carbon reduction.