Weight Analysis for Multi-objective Optimal Solution of Multi-energy Complementary System

Abstract

Abstract Multi-energy complementary system (MCS), integrating with renewable energy and new energy, is an effective way to promote low-carbon development and clean energy utilization. Reasonable system configurations and operation scheduling schemes play key roles in maintaining the long-term and efficient operations of the system. In general, multi-objective optimization of system integration is employed to achieve the optimal decision strategies for MCS operations. However, different weights used to determine the importance of each objective during the optimization may cause various optimization results. Thus, reasonable weight adopted is critical to the credibility of the optimization solutions and the resulting system efficiency. In this paper, a comprehensive weight analysis is implemented during the multi-objective optimization for the decision-making of the MCS. The weight determination of MCS design optimization objective is analyzed from three aspects namely subjective, objective, and the combination of subjective and objective. Based on a case analysis, it isfounded that when the weight is determined by subjective weighting method, the weight of economic index is the largest. When the objective weighting method is adopted, the environmental protection index is obviously greater than the economic index and the energy efficiency index. Due to the different information entropy carried by each target in each group of data, the weights obtained by objective weighting and subjective and objective comprehensive weighting are different. With different weight decision schemes, the capacity of each MCS equipment varies greatly. While using the intelligent optimization algorithm for multi-objective optimization, it is necessary to analyze the weight of each objective in the process of multiple independent experiments and make comprehensive decisions according to the objective preference of decision makers to determine the optimal solution. The results indicatethat the research provides an effective reference for the analysis of the weight of each objective and the decision of the optimal solution in the MCS optimization research process.