Optimization scheduling of integrated energy service system in community: A bi-layer optimization model considering multi-energy demand response and user satisfaction

Multi-energy complementation and coupling are considered effective methods for solving the increasingly prominent supply and demand relationship and improving energy efficiency. Therefore, considering user satisfaction and multi-energy demand are the most efficient ways to improve multi-energy complementation and coupling. Herein, a bi-layer optimization model of community-integrated energy service system that considers the multi-energy demand response and user satisfaction is proposed based on user preferences. There are two types of people in the community, namely retirees and office workers, and their energy consumption characteristics are analyzed. Users consider multi-energy demand response, optimize energy consumption behavior, and aim at costs and comfort degree. In addition, the service provider optimizes the outputs of coupling components and considers the full consumption of wind and photovoltaic power to increase profit. The improved PSO algorithm and CPLEX solver are adopted to achieve bi-layer optimization. The results show that the costs of retirees and office workers are reduced by 7.32% and 5.69%, respectively. Furthermore, the profit of the service provider is increased by 12.01% when the proportion of retirees is relatively larger and renewable energy is fully consumed. The conclusions also provide suggestions for energy supply methods and site selection strategies to service providers.(c) 2022 Elsevier Ltd. All rights reserved.