E3S Web of Conferences (Jan 2023)

Design of Substation Carbon Emission Prediction Model Based on Cloud Model

  • Wang Zilei,
  • Wang Shuhao,
  • Li Yu

DOI
https://doi.org/10.1051/e3sconf/202339303002
Journal volume & issue
Vol. 393
p. 03002

Abstract

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In order to achieve the goal of energy conservation and emission reduction, all walks of life are taking active actions. Power system, as the main dispatching application of energy, is in full swing in the monitoring and management of carbon emissions and other related studies. The purpose of this paper is to study the design of substation carbon emission prediction model based on the cloud model. First, the basic concepts and numerical characteristics of the cloud model are introduced. Secondly, it introduces the principle of carbon emission prediction method based on cloud model and the common carbon emission prediction method. Combining the real-time substation carbon emission data simulation with the cloud model prediction, the prediction results were compared with the BP neural network, and two average error values were used to measure the prediction results. It was found that the cloud model had a higher accuracy in predicting carbon emission, which verified its feasibility and superiority.