Assessment of Monthly Electricity Generation in Thermal Power Plants through Mapping Total Societal Energy Generation Dynamics

Although monthly electricity generation assessment has been studied for many years in the fields of new energy generation, hydropower, and load, with mature modeling and improved assessment accuracy, it cannot be completely applied to the monthly electricity generation assessment model for thermal power. Accurate assessment of monthly electricity generation for thermal power can help thermal power plants to improve coal storage management and enhance the economic efficiency of power generation. Firstly, a prediction model driven by both data and physics is established for different power generation sources to obtain the monthly electricity generation assessment results for thermal power across society. Secondly, using the monthly electricity generation of thermal power to assess the load rate of the whole society, a correction model between the load rate of the whole society and the load rate of thermal power plants is established to assess the monthly electricity generation of thermal power plants. Then, in order to more comprehensively explore the unobtainable factors in thermal power generation, a data-driven method and historical data averaging method are used for assessment, with weighted coefficients set to obtain the assessed value of monthly electricity generation for thermal power plants. Finally, the actual operation data of a certain power plant is used for verification, demonstrating the effectiveness of the method proposed in this paper.