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Nowadays, with the wide installation of distributed energy resources and independent energy storage systems, prosumers as a new type of electricity market entity have emerged. Since numerous prosumers can significantly impact the carbon emission of the power grid, this paper proposes an improved carbon emission flow method for the power grid with prosumers. This method can accurately clarify the detailed distribution of electrical carbon emission flow in power grids. First, based on the power flow, prosumers’ impacts on the electrical carbon emission are quantified from three aspects that include the carbon emission sources, the network flow, and the indirect carbon emission individuals. Then, an improved power carbon emission flow model is proposed, in which the complex carbon emission intensity of prosumers is derived emphatically. Finally, case studies based on the IEEE 30-bus system verify the feasibility of the proposed method. This method provides a measurement basis for further research considering electrical carbon emissions.

Single-phase broken faults occur frequently, affecting the reliability of distribution network. In order to effectively identify the fault type of single-phase broken fault, this paper proposes a new identification method, which is based on the combination of variational mode decomposition and stacked auto encoder with double optimization (AO-VMD-PSO-SAE). Firstly, the zero sequence voltage, which collected in line, is decomposed into a set of variational modal components. Nextly, the stack automatic encoder is used to conduct unsupervised training on the denoised data to establish a depth learning model, and the AO optimization algorithm and the PSO optimization algorithm are used to determine the super parameters in the model.​ Finally, simulation results supported and the validity of the method was verified. What the results show is that the proposed model named AO-VMD-PSO-SAE can accurately predict the types of single-phase broken fault under noise interference.