
1.中国科学技术大学能源科学与技术学院, 广州 510640
2.中国科学院广州能源研究所, 广州 510640
3.南方电网科学研究院, 广州 510663
Received:28 August 2025,
Online First:25 December 2025,
Published:20 August 2026
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裴越,张靖,唐孜童等.基于改进AHP法组合赋权的变权可拓云的乡村能源系统效益评估[J].南方电网技术,2026,20(08):3-17.
PEI Yue,ZHANG Jing,TANG Zitong,et al.Benefit Evaluation of Rural Energy Systems Based on Variable-Weight Extension Cloud with Combined Weighting via Improved AHP[J].Southern Power System Technology,2026,20(08):3-17.
裴越,张靖,唐孜童等.基于改进AHP法组合赋权的变权可拓云的乡村能源系统效益评估[J].南方电网技术,2026,20(08):3-17. DOI: 10.13648/j.cnki.issn1674-0629.2026.08.001.
PEI Yue,ZHANG Jing,TANG Zitong,et al.Benefit Evaluation of Rural Energy Systems Based on Variable-Weight Extension Cloud with Combined Weighting via Improved AHP[J].Southern Power System Technology,2026,20(08):3-17. DOI: 10.13648/j.cnki.issn1674-0629.2026.08.001.
在“双碳”和“乡村振兴”战略目标的驱动下,针对乡村能源能效低、清洁能源占比少等问题,乡村能源绿色转型迫在眉睫。乡村综合能源系统作为提升能源利用效率、降低碳排放的有效途径,已成为当前研究热点,然而针对该系统的效益评估研究仍显不足。为此提出了一种基于组合赋权的变权可拓云模型的乡村综合能源评估方法。首先构建了涵盖乡村经济、技术、生态、社会4个方向的评估指标体系;然后运用改进AHP法主观赋权降低了计算复杂度,使用反熵法客观赋权,然后使主客观权重最小化求解最优组合权重,最后运用改进的可拓云模型对乡村综合能源系统指标数据进行评估,通过对指标数据自适应变权更加突出系统短板和优势指标。以广西古辣镇示范工程数据为例对其进行评估,结果表明所提出的方法有效、科学。
Driven by the strategic goals of "dual carbon" and "rural revitalization"
and in response to issue such as low rural energy efficiency and a low proportion of clean energy in rural areas
the green transition of rural energy has become an urgent priority. As an effective approach to improve energy utilization efficiency and reduce carbon emissions
the rural integrated energy system has emerged as a current research focus. However
researches on the benefit evaluation of this system remains insufficient. To address this gap
a rural integrated energy evaluation method is proposed based on a variable-weight extension cloud model with combined weighting. Firstly
an evaluation index system covering four dimensions is constructed: rural economy
technology
ecology
and society. Secondly
the improved analytic hierarchy process (AHP) is adopted for subjective weighting to reduce computational complexity
while the anti-entropy method is used for objective weighting. Subsequently
the optimal combined weights are obtained by minimizing the deviation between subjective and objective weights. Finally
the improved extension cloud model is applied to evaluate the index data of the rural integrated energy system
and the adaptive variable weighting of index data is implemented to better highlight the system's shortcomings and advantageous indicators. Taking the data of the demonstration project in Gula Town
Guangxi as an example
the evaluation is conducted. The results show that the method proposed is effective and scientific.
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