基于实测数据因果推断的燃煤机组低碳经济运行评估决策OA北大核心CSTPCD

As the first industry to participate in the national carbon market,thermal power companies need to fulfill their compliance obligations according to market rules.The power supply carbon emission intensity and power supply of these companies jointly influence their compliance requirements in the carbon market.With the development of the new type power systems,coal-fired units will take on more system regulation responsibilities,and their power supply carbon emission intensity will be increasingly affected by their operational conditions.In light of the current situation of thermal power companies,this paper proposes a low carbon economic operation assessment and decision making for coal-fired units based on measured-data-driven causal inference method.By depicting the causal graph among variables using prior knowledge,a generalized propensity score matching model is constructed to assess the impact functions of power supply on carbon emission intensity and coal consumption of power supply.This assists in decision making for low carbon operation of coal-fired units.The case study results verify the feasibility and effectiveness of the proposed method,providing an efficient and convenient approach for the assessment and decision making of low carbon economic operation of coal-fired units.