Adaptability Analysis of Dual Clearing Systems in Spot Electricity Markets Based on Fuzzy Evaluation Metrics: An Inner Mongolia Case Study

The construction of spot electricity markets plays a pivotal role in power system reforms, where market clearing systems profoundly influence market efficiency and security. Current clearing systems predominantly adopt a single-system architecture, with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models. Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems in contingency scenarios—a critical gap given redundant systems’ expanding applications in operational environments. This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability, demonstrated through an in-depth case study of the Inner Mongolia power market. First, we establish the innovative “Dual-Active Heterogeneous” architecture that enables independent parallelized operation and fault-isolated redundancy. Subsequently, key performance indices are quantitatively evaluated across four critical dimensions: unit commitment decisions, generator output constraints, transmission section congestion patterns, and clearing price formation mechanisms. An integrated fuzzy evaluation methodology incorporating grey relational analysis is employed for objective indicator weighting, enabling systematic quantification of system superiority under specific grid operating states. Empirical results based on actual operational data from 200 generation units demonstrate the framework’s efficacy in guiding optimal system selection, with particularly strong performance observed during peak load periods. The proposed approach shows high generalization potential for other regional markets employing redundant clearing mechanisms—particularly those with increasing renewable penetration and associated uncertainty.