National Carbon Price Prediction Considering Carbon Emissions from the Power Industry

In order to better predict the trend of national carbon prices, a national carbon price prediction model is constructed based on the autoregressive integrated moving average with exogenous variable model (ARIMAX), using different exogenous variables during the fulfillment and non-fulfillment period....

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Bibliographic Details
Main Authors: Yirong WANG, Haolin CHEN, Lishen LIN, Jin TANG
Format: Article
Language:zho
Published: State Grid Energy Research Institute 2024-05-01
Series:Zhongguo dianli
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Online Access:https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202308084
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Summary:In order to better predict the trend of national carbon prices, a national carbon price prediction model is constructed based on the autoregressive integrated moving average with exogenous variable model (ARIMAX), using different exogenous variables during the fulfillment and non-fulfillment period. Firstly, based on research on the institutional rules of the national carbon market and analysis of trading characteristics, it is found that the national carbon price is mainly influenced by the expectations of participants during the non-fulfillment period, and is mainly driven by the fulfillment demand of enterprises during the fulfillment period. Secondly, in terms of model training, an autoregressive differential moving average model is adopted to introduce different exogenous variables at different stages to improve the effectiveness of carbon price prediction. Finally, the real price data of the first compliance period in the national carbon market are used for verification, and the results show that the proposed national carbon price prediction model in this article is superior to the benchmark model in terms of accuracy.
ISSN:1004-9649