计及用户低碳需求响应行为的动态碳排放因子预测方法OA

In view of the current problem of lack of key guiding signals for low-carbon energy consumption on the user side,a dynamic car-bon emission factor prediction method taking into account the low-carbon demand response behavior on the user side is proposed.First,a us-er dynamic electricity carbon emission factor calculation model is constructed based on the carbon emission flow theory,and a carbon emis-sion factor data pool is constructed in combination with system operation simulation.Second,a low-carbon energy consumption response be-havior model for power users facing dynamic carbon emission factors is constructed,and a dynamic carbon emission factor prediction meth-od taking into account the low-carbon demand response behavior on the user side is proposed.Carbon emission factor prediction is carried out based on LSTM neural network,and effective prediction of node-level dynamic carbon emission factors for a given system based on arbi-trary source and load input is achieved.Finally,a case analysis is carried out based on a PJM-5 node power system and a 36-node power sys-tem with a high proportion of renewable energy,which verifies the effectiveness of the proposed method in predicting node-level electricity carbon emission factors taking into account the user's low-carbon demand response.