Synergistic Optimization of Renewable Energy Supply Chains under the Dual Carbon Goals

Under China’s strategic commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060 (the “Dual Carbon Goals”), renewable energy enterprises face unprecedented pressure to simultaneously expand capacity, reduce costs, enhance supply chain resilience, and minimize carbon footprints. This study systematically investigates supply chain synergy optimization for wind and solar power enterprises within the Dual Carbon policy framework. Employing a multi-method approach integrating literature review, system analysis, and a case study of LONGi Green Energy, this research identifies three core synergy barriers: geographic fragmentation and policy decoupling, carbon traceability credibility crises, and inherent conflicts among efficiency, decarbonization, and resilience objectives. A three-tier collaborative optimization framework is proposed, comprising: (1) an information synergy layer based on blockchain-enabled carbon data pools; (2) an operational synergy engine integrating multi-objective optimization models with dynamic carbon taxation and shared warehousing; and (3) a carbon synergy mechanism incorporating tiered supplier incentives and green transition funds. Empirical validation through the LONGi case demonstrates significant improvements: total supply chain costs reduced by 15.3%, lifecycle carbon emissions per watt decreased by 39.6%, and disruption recovery time shortened by 58.3%. This research contributes a “policy-geography-technology” three-dimensional synergy blockage theory, a tri-objective dynamic equilibrium model, and a responsibility-sharing carbon governance framework, offering both theoretical advancements and practical pathways for sustainable energy supply chain management.

Keywords: Dual Carbon Goals, Renewable Energy, Supply Chain Synergy, Carbon Traceability, Supply Chain Resilience, Blockchain, Multi-Objective Optimization, Green Supply Chain.