Monthly Electricity Price Forecast Analysis Considering Economics and Renewable Energy in the Electricity-carbon Coupling Market

Regional economic growth will promote the increase of social electricity consumption. At the same time, the seasonal changes of renewable energy will also affect the supply and demand relationship in the electricity market. Therefore, the change of electricity price is affected by factors such as economic and renewable energy seasonal changes. This paper first establishes the Census X12 seasonal adjustment multiplication model to convert the monthly electricity price, and then establishes the prediction model according to the characteristics of each component of the electricity price. Finally, the prediction results of each component are reconstructed to obtain the predicted value of the monthly electricity price.

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Publication Details

Published
2025-04-15
DOI
https://doi.org/10.1109/acpee64358.2025.11040612
Primary Topic
Energy Load and Power Forecasting
Type
article
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Monthly Electricity Price Forecast Analysis Considering Economics and Renewable Energy in the Electricity-carbon Coupling Market

Tao Cai, Linjie Kan, Ji Bian, Jie Chen et al.
Energy Load and Power Forecasting
article

Monthly Electricity Price Forecast Analysis Considering Economics and Renewable Energy in the Electricity-carbon Coupling Market

Tao Cai, Linjie Kan, Ji Bian, Jie Chen, Jie Yu, Wu Chenxuan, Yu Wenshuai, Cen Zengguang, Ge Huiwen
article en

Abstract

Regional economic growth will promote the increase of social electricity consumption. At the same time, the seasonal changes of renewable energy will also affect the supply and demand relationship in the electricity market. Therefore, the change of electricity price is affected by factors such as economic and renewable energy seasonal changes. This paper first establishes the Census X12 seasonal adjustment multiplication model to convert the monthly electricity price, and then establishes the prediction model according to the characteristics of each component of the electricity price. Finally, the prediction results of each component are reconstructed to obtain the predicted value of the monthly electricity price.

State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 87%
Energy Load and Power Forecasting
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