Multi-Objective Optimal Scheduling of Community Integrated Energy System Considering Comprehensive Customer Dissatisfaction Model

Based on the system with combined cooling, heating and power, this paper formulates a multi-objective balance optimization scheduling framework of community integrated energy systems, in which demand response programs are considered. To quantify the customer's dissatisfaction caused by the changes in energy use style and a decline in comfort, the electricity dissatisfaction function and heat/cold dissatisfaction function are constructed based on Kano's model. Then, a comprehensive customer dissatisfaction model is proposed based on a combination of subjective weight and objective weight method. Furthermore, a multi-objective optimization model is constructed to minimize total operating costs, comprehensive customer dissatisfaction and carbon dioxide emissions. The case study is considered in two different customer dissatisfaction functions: the linear customer dissatisfaction function and Kano's model-based customer dissatisfaction function. Finally, non-dominated sorting genetic algorithm (NSGA-II) is utilized to simultaneously optimize three goals and get the Pareto fronts. From the obtained Pareto fronts, the best scheme is obtained by using the entropy-weighting Similarity to Ideal Solution (TOPSIS) method. The results show that the proposed customer dissatisfaction model can effectively reduce the operating costs, customer dissatisfaction, and carbon emissions, under the premise of balancing the three objective functions, compared with the linear customer dissatisfaction model.