An Electricity Sale Package Recommendation Method Based on Prospect Strengths and Weaknesses Degree and Choquet Integral

Given that existing methods for recommending electricity sale packages primarily consider scenarios where customers are familiar with all package attributes, they overlook psychological factors, attribute correlations, and the determination of attribute weights during decision-making. To address these limitations, this paper proposes a recommendation method for electricity sale package based on prospect strengths and weaknesses degree and the Choquet integral. The details are as follows: Firstly, a label system for evaluating electricity sale packages and customer clustering is utilized to identify similar customers to a new customer. Secondly, a set of similar customers is identified, and N similar customers are selected as experimental customers. Their decision-making information is aggregated using the Choquet integral to construct a customer group decision-making matrix. Next, to account for customers’ psychological risk preferences, the Prospect Theory is integrated into the preference difference function of the classical Superiority–Inferiority Ranking method, resulting in the degree of prospect strengths and weaknesses. Building on this, and addressing the challenges of attribute correlation and weight determination, a model is constructed using the Choquet integral and comprehensive attribute weights. This model ranks electricity sale packages based on the degree of prospect strengths and weaknesses, capturing the differences between various schemes through the prospect strengths and weaknesses flow. The ranking of packages for recommendation is then derived from this flow. Finally, a case analysis is conducted with customers in a western Zhejiang region in China to verify the accuracy and effectiveness of the proposed recommendation method.