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Published on 18 October 2024
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Sang,M. (2024). A Study on Energy Production and Consumption Based on Seasonal ARIMA and REAO. Advances in Economics, Management and Political Sciences,112,47-56.
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A Study on Energy Production and Consumption Based on Seasonal ARIMA and REAO

Meizhen Sang *,1,
  • 1 Institute of Management of Nanchang University, Nanchang University, No. 999 Xuefu Avenue, Honggutan District, Nanchang City, Jiangxi Province

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/112/20242273

Abstract

In the face of the global energy challenge, this study delves into the intricate landscape of energy dynamics within the rapidly evolving global economy and technological sphere. Recognizing energy as a pivotal driver of societal progress, we present a comprehensive evaluation and optimization model for China's energy sources, emphasizing economic, cost, electric energy, and environmental considerations. Employing time series models, specifically ARIMA and gray scale forecasting, we meticulously analyze wind and solar power generation, as well as overall power consumption. The results showcase nuclear power and hydropower as significant contributors to the energy landscape. Leveraging a linear programming model, we simulate and optimize the future energy development structure, considering constraints such as cost, energy, capacity, and carbon emissions. Our findings reveal the optimal quota contributions of thermal power, hydro power, nuclear power, wind power, and solar power as 13.7%, 14.2%, 17.6%, 54.5%, and 0%. Building upon these insights, we propose strategic recommendations for sustainable electric energy development. Emphasizing wind and solar energy's potential, we advocate for continued interest and increased support for technological advancements. Additionally, we call for the establishment of comprehensive power and energy development plans, integrating economic and environmental goals. To address imperfections in China's electricity tariff system, we recommend ongoing reforms aligned with market dynamics and environmental considerations.

Keywords

Electric Energy, Seasonal ARIMA model, Time Series, Analysis REAO model

[1]. Cable, Vincent. "What is international economic security?." International Affairs 71.2 (1995): 305-324.

[2]. Scientific Platform Serving for Statistics Professional 2021. SPSSPRO. (Version 1.0.11)[Online Application Software]. Retrieved from https://www.spsspro.com.

[3]. Shumway, Robert H., et al. "ARIMA models." Time series analysis and its applications: with R examples (2017): 75-163.

[4]. Xue, Dong-mei, and Zhi-qiang Hua. "ARIMA based time series forecasting model." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 9.2 (2016): 93-98.

[5]. Yang, Xiaojun, Liaoliao Yan, and Luan Zeng. "How to handle uncertainties in AHP: The Cloud Delphi hierarchical analysis." Information Sciences 222 (2013): 384-404.

Cite this article

Sang,M. (2024). A Study on Energy Production and Consumption Based on Seasonal ARIMA and REAO. Advances in Economics, Management and Political Sciences,112,47-56.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 8th International Conference on Economic Management and Green Development

Conference website: https://2024.icemgd.org/
ISBN:978-1-83558-637-2(Print) / 978-1-83558-638-9(Online)
Conference date: 26 September 2024
Editor:Lukáš Vartiak
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.112
ISSN:2754-1169(Print) / 2754-1177(Online)

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