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Home / Journals / ENERGY / Online First / doi:10.32604/ee.2026.084439
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A Multi-Dimensional Evaluation of New Rural Integrated Energy Systems Based on the Combination Weighting Method and Cloud Model

Yijun Miao1, Erxun Huang1, Tao Shen1, Chuansheng Cao1, Jing Liu1, Ruonan Li2,3,*, Chang Wen2,3, Tianyu Liu2,3,*
1 Power China HuBei Electric Engineering Co., Ltd., Wuhan, China
2 School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, China
3 China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan, China
* Corresponding Author: Ruonan Li. Email: email; Tianyu Liu. Email: email
(This article belongs to the Special Issue: AI in Green Energy Technologies and Their Applications)

Energy Engineering https://doi.org/10.32604/ee.2026.084439

Received 22 April 2026; Accepted 26 May 2026; Published online 29 June 2026

Abstract

To improve the comprehensiveness and uncertainty representation of rural integrated energy system evaluation, this study develops a multidimensional assessment framework covering efficiency, supply reliability, low-carbon performance, environmental impacts, economic benefits, social benefits, and system development. The framework integrates improved AHP, entropy weighting, and a sum-of-squared-deviations combination strategy to balance expert judgment with data-driven information, while the cloud model is used to quantify both fuzziness and randomness in the evaluation process. Three rural energy revolution pilot counties in China—Wendeng District, Changfeng County, and Liyang City—were selected for empirical validation. The comprehensive expectation values were 78.573, 81.032, and 81.824, respectively. Liyang achieved the highest overall evaluation level, Changfeng showed the strongest system stability, and Wendeng exhibited greater uncertainty due to weaker energy-efficiency and low-carbon-sustainability performance. The proposed framework provides a practical tool for identifying regional weaknesses and supporting county-level rural energy-system planning.

Keywords

New rural integrated energy system; improved analytic hierarchy process; entropy weight method; combination weighting based on sum of squared deviations; cloud model

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