Closed-Loop Energy Supply Chain Design under Lean Economics: A Synergistic Design of Resource Efficiency and Social Adaptability

Abstract

This study aims to design a closed-loop supply chain network for photovoltaic and wind energy systems, targeting the dual objectives of lean economics and sustainable development. To address the limitations of existing research regarding the integration of multi-energy systems and the handling of uncertainties, we propose a nonlinear mixed-integer multi-objective optimization model incorporating economic, environmental, and social objectives. The model comprehensively considers forward and reverse flows, including energy production, transportation, and recycling. To address uncertainties such as demand fluctuations, variations in solar radiation intensity, and wind speed changes, we employ an enhanced constrained epsilon method and a two-stage stochastic programming approach. Experimental design and scenario analysis were conducted to validate the model's effectiveness. The results demonstrate that the optimized supply chain network significantly reduces total costs, enhances reliability, and decreases carbon emissions. These findings provide energy enterprises and policymakers with decision support for optimizing renewable energy systems under complex market conditions, thereby promoting the efficient utilization of renewable energy and advancing sustainable development.