An optimal electricity consumption strategy for steel enterprises with short processes in the context of low-carbon DR

Currently， large industrial enterprises， such as steel mills， have reduced electricity costs by participating in demand response programs； however， they have not yet achieved their carbon and emission reduction goals. To address this， an optimal electricity consumption strategy is proposed for steel enterprises with short processes in the context of low-carbon demand response （DR）. First， the resource-task network （RTN） model is used to model the various stages of short-process steel production. Next， based on daily regional electricity carbon emission factor curves and carbon pricing， the electricity consumption strategy of enterprises participating in low-carbon demand response is optimized. This strategy fully schedules the start-up and shutdown of various production equipment to reduce both the enterprises’ energy costs and carbon emissions. Subsequently， the behavior of steel enterprises in participating in low-carbon demand response under different scenarios is simulated， and the optimized electricity consumption strategy after participation is compared with the pre-optimization strategy in terms of total cost and carbon reduction. The results validate the effectiveness of the proposed method. Finally， the impact of carbon pricing and carbon emission factor curves on low-carbon demand response is explored.