Provincial electricity spot market supervision framework based on hesitant fuzzy linguistic cloud model from the perspective of sustainable development

Abstract This study proposes a supervision framework for provincial electricity spot markets based on hesitant fuzzy linguistic cloud model to address supervision complexities and uncertainties. Firstly, a comprehensive supervision criteria system is proposed covering five perspectives, which provides a robust foundation for fluctuating market supervision. Then, a hesitant fuzzy linguistic improved cloud model is constructed to achieve accurate supervision state analysis. A case study reveals that the proposed framework can effectively identify critical supervision problems and give an objective electricity spot market supervision state. Based on above, targeted supervision strategies are proposed to enhance market stability and operational transparency.