| 引用本文: | 王雨晴,闫朝臣,王昭贞,等.基于OCC-IEGC模型的矿山综合能源系统运行效益评价[J].电力系统保护与控制,2025,53(13):11-22.[点击复制] |
| WANG Yuqing,YAN Chaochen,WANG Zhaozhen,et al.Operation benefit evaluation of mine integrated energy systems based on OCC-IEGC model[J].Power System Protection and Control,2025,53(13):11-22[点击复制] |
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| 摘要: |
| 矿山综合能源系统(mine integrated energy system, MIES)作为支撑煤矿绿色发展的重要途径，合理有效地对其运行效益进行评价是促进其发展的必要前提。然而，MIES运行效益评价一方面需要考虑能-煤流的强耦合关系，另一方面还需要应对系统运行不确定性对于评价结果准确性的影响，鉴于此，提出一种基于最优聚类系数的改进可拓灰云模型(optimal clustering coefficient based improved extension gray cloud, OCC-IEGC)的MIES运行效益评价框架。首先，考虑MIES生态特性，基于驱动力-压力-状态-影响-响应(driving-pressure-state-impact-response, DPSIR) 模型建立MIES运行效益评价指标体系，并应用云雾化权重筛选方法获得具有最优合理性的组合权重。其次，构建基于可拓灰云的MIES运行效益评价模型，削弱系统运行不确定性及评价过程中的主观性和模糊性对评价结果的影响，并采用最优灰云聚类系数提高评价结果的可靠性。最后，通过算例验证所提指标体系和评价模型的有效性。 |
| 关键词: 矿山综合能源系统 运行效益评价 改进可拓灰云模型 最优聚类系数 云雾化权重筛选 |
| DOI：10.19783/j.cnki.pspc.241282 |
| 投稿时间：2024-09-21修订日期：2024-12-31 |
| 基金项目:国家自然科学基金项目资助(62133015)；河北省自然科学基金项目资助(G2022502004)；中央高校基金项目资助(2023MS156) |
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| Operation benefit evaluation of mine integrated energy systems based on OCC-IEGC model |
| WANG Yuqing1,2,YAN Chaochen1,2,WANG Zhaozhen2,GUO Haonan2,WANG Liying2,ZENG Ming1 |
| (1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric
Power University), Beijing 102206, China; 2. Department of Economic Management,
North China Electric Power University (Baoding), Baoding 071000, China) |
| Abstract: |
| The mine integrated energy system (MIES) is an important approach for supporting the green development of coal mines. Conducting a reasonable and effective evaluation of its operation benefits is an necessary prerequisite for promoting its development. However, evaluating the operation benefits of MIES requires not only consideration of the strong coupling between energy and coal flows, but also addressing the influence of operational uncertainties on the accuracy of the evaluation. To address these challenges, a MIES operation benefit evaluation framework is proposed based on the optimal clustering coefficient-based improved extension grey cloud (OCC-IEGC) model. First, considering the ecological characteristics of MIES, an evaluation index system is established based on the driving-pressure-state- impact-response (DPSIR) model, and the cloud-weighted selection method is applied to obtain an optimal rational combination weights. Second, the MIES operation benefit evaluation model based on the extensive grey cloud theory is constructed to mitigate the influence of system operational uncertainty, subjectivity and ambiguity during the evaluation process, while the optimal clustering coefficients are used to further improve the reliability of the evaluation results. Finally, the effectiveness of the proposed index system and evaluation model is verified through case studies. |
| Key words: mine integrated energy system operation benefit evaluation improved extensive grey cloud model optimal clustering coefficients cloudy weight screening |
