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基于GIS与云加权幂Heronian平均算子的风光氢储一体化项目投资适宜性评估与多属性决策研究

Investment suitability assessment and multi-attribute decision-making research for wind-photovoltaic‑hydrogen-storage integrated project based on GIS and cloud weighted power Heronian mean operator

作者 Fugui Donga · Peijun Wanga · Wanying Lib
期刊 Applied Energy
出版日期 2025年1月
卷/期 第 401 卷
技术分类 储能系统技术
技术标签 储能系统
相关度评分 ★★★★★ 5.0 / 5.0
关键词 A macro-level and micro-level indicator system for WPHSI investments have been established.
语言:

中文摘要

在全球能源转型背景下,可再生能源项目的投资决策至关重要。风光氢储一体化(WPHSI)项目的评估涉及多源信息、复杂指标和动态专家意见,传统方法难以满足其动态性与复杂性的决策需求。本研究提出了一种基于多属性决策(MADM)的新型投资适宜性评估框架。首先构建了宏观—微观评价体系;设计了一种具有权重更新机制的动态社会网络专家赋权方法,并进一步提出三阶段赋权流程:(1)基于云模型的决策试验与评价实验室方法(CDEMATEL)量化指标间的因果关系并计算主观权重;(2)引入基尼系数改进传统的基于标准间相关性的指标重要性确定方法(CRITIC),提出改进型CRITIC(ICRITIC)以计算客观权重;(3)构建CDEMATEL-ICRITIC-博弈论集成模型,融合主客观权重。此外,开发了云加权幂Heronian平均算子(CWPHMO)用于评估信息的聚合与排序。结合GIS技术,在内蒙古地区识别出11个适宜建设的候选场址。优先级评估结果显示,鄂尔多斯市A3场址得分最高,表现出最优的适宜性和投资潜力。通过权重波动测试、蒙特卡洛模拟及参数敏感性分析,验证了A3场址排名首位的稳定性。不同方法所得结果高度一致(Kendall协同系数达0.957)且高度相关(Pearson相关系数大于0.97),进一步证实A3为最优选址。本研究所提出的框架相较于传统方法,能够在复杂动态环境中实现更科学、全面的投资决策,兼具可扩展性与实际应用价值,为WPHSI及其他多能耦合项目提供了理论支持与方法借鉴。

English Abstract

Abstract Amid the global energy transition, investment decisions for renewable energy projects are crucial. Evaluating wind-photovoltaic‑hydrogen-storage integrated (WPHSI) projects involves multi-source information, complex metrics, and dynamic expert opinions, rendering traditional methods struggling to meet dynamic and complex decision-making demands of WPHSI projects. This study proposes a novel investment suitability framework based on multi-attribute decision-making (MADM). First, a macro–micro evaluation system was established. A dynamic social network expert weighting method with weight updates was designed, followed by a three-stage weighting approach: (1) Cloud-based Decision Making Trial and Evaluation Laboratory (CDEMATEL) quantified causal relationships and computed subjective weights; (2) Gini coefficient was introduced to enhance traditional Criteria Importance Through Intercriteria Correlation (CRITIC) method, proposing Improved CRITIC (ICRITIC) to compute objective weights; (3) A combined CDEMATEL-ICRITIC-game theory model integrated both weight types. Furthermore, cloud weighted power Heronian mean operator (CWPHMO) was developed to aggregate and rank evaluations. Using GIS technology, 11 suitable locations were identified in Inner Mongolia. The priority assessment results indicate, site A3 in Ordos received the highest score, showing optimal suitability and investment potential. Weight fluctuation tests, Monte Carlo simulation, and parameter sensitivity analysis confirmed stability of A3's top ranking. Results from different methods were highly consistent (Kendall's coefficient = 0.957) and correlated (Pearson correlation coefficient > 0.97), validating A3 as optimal site. This study's framework enables more scientific and comprehensive investment decision-making in complex, dynamic environments than traditional methods, combining scalability with practical applicability while providing theoretical and methodological support for WPHSI and other multi-energy projects.
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SunView 深度解读

该风光氢储一体化项目多属性决策框架对阳光电源具有重要战略价值。研究提出的GIS选址与动态评估方法可直接应用于PowerTitan储能系统和ST系列PCS的项目部署优化,特别是在内蒙古等新能源富集区的多能互补场景。云加权赫罗尼安算子的多维评估机制可融入iSolarCloud平台,增强智慧运维的投资决策支持能力。该方法论为阳光电源拓展风光氢储一体化解决方案、优化ESS系统配置提供了科学的量化工具,助力公司在复杂多能源项目中实现精准投资与技术协同创新。