A Multi-Market Hierarchical Joint Clearing Optimization Method Considering Dynamic Carbon Emissions Based on Transformer

Against the backdrop of China’s dual-carbon goals and the development of new power systems, the large-scale integration of renewable energy has intensified system regulation requirements and imposed higher demands on the low-carbon performance and flexibility of electricity market clearing mechanisms. To address the inability of conventional static carbon emission factors to accurately reflect the actual emission levels of coal-fired units, this paper proposes a joint energy and frequency regulation ancillary service clearing model incorporating dynamic carbon emission factors. First, a Transformer-based dynamic carbon emission factor model is developed using features such as unit output, load rate, start-up and shutdown status, and unit type to characterize the dynamic variation in the carbon emission intensity of coal-fired units. Second, a coordinated day-ahead and intraday market clearing model is established to jointly optimize unit commitment, generation scheduling, frequency regulation capacity allocation, energy storage operation, and renewable energy accommodation, thereby achieving coordinated improvements in economic efficiency, low-carbon performance, and operational flexibility. Case studies based on actual data from a provincial power grid in southern China demonstrate that the proposed model increases the renewable energy accommodation rate by 2.01%, reduces the total system cost by 1.51%, lowers total carbon emissions by 3.52%, and decreases carbon emission intensity by 5.15%. The results confirm that incorporating dynamic carbon emission factors into joint market clearing can effectively improve both the economic performance and emission reduction capability of the power system.