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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

Author

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  • Dong, Fugui
  • Wang, Peijun
  • Li, Wanying

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.

Suggested Citation

  • Dong, Fugui & Wang, Peijun & Li, Wanying, 2025. "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," Applied Energy, Elsevier, vol. 401(PC).
    • Handle: RePEc:eee:appene:v:401:y:2025:i:pc:s0306261925015326
    DOI: 10.1016/j.apenergy.2025.126802
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