An Improved Modeling Method for Electrolyte Aluminum Loads Considering Thermal Balance and Flexible Regulation Cost

Exploring the potential of electrolytic aluminum loads (EALs) for demand response helps address the challenges of integrating renewable energy into power systems. However, most existing EAL models fail to consider thermal balance constraints and cost characteristics comprehensively. Recent studies attempting to address this issue still face difficulties in balancing modeling accuracy and computational efficiency, limiting their application in large-scale scheduling scenarios. This paper proposes an improved EAL modeling method that introduces more accurate thermal balance constraints by considering the dynamic variations in reaction energy and heat dissipation. We employ piecewise linearization and time decoupling techniques to handle nonlinear constraints and discontinuous cost functions. Case studies demonstrate that the improved model yields more reliable operation strategies by maintaining electrolyte temperatures within safe ranges during prolonged power regulation. By embedding EAL’s complex energy-material-temperature conversion mechanisms into a computationally efficient optimization framework, this work helps EALs better participate in real-world grid interaction scenarios.