A plan decision framework of agricultural and photovoltaic hybrid projects from the safety resilience respective

Engineering notes

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

Agricultural–photovoltaic hybrid projects (APHPs) have been widely promoted as an effective solution to improve land-use efficiency and support the large-scale deployment of photovoltaic power stations. However, increasing climate variability and the growing frequency of extreme weather events pose substantial threats to the safe and stable operation of APHPs, making safety resilience a critical concern in project planning and decision-making. Existing studies primarily focus on economic performance and sustainability, while systematic and scientifically grounded evaluations of APHP safety resilience remain limited, particularly under conditions of uncertainty and extreme weather risk. To address this gap, this study proposes an integrated decision-making framework for evaluating and enhancing APHP safety resilience. First, a comprehensive safety resilience evaluation index system is constructed from four dimensions—technological, economic, organizational, and social resilience—explicitly reflecting the impacts of extreme weather. Second, interval-valued intuitionistic fuzzy numbers (IVIFNs) are employed to model uncertainty arising from incomplete data and expert hesitation. Third, an IVIFN–TOPSIS method with fixed positive and negative ideal solutions is developed to ensure robust and consistent resilience assessment across different decision scenarios. Furthermore, an assignment-based optimization model is introduced to translate evaluation results into actionable resource-allocation strategies. A real-world case study demonstrates the effectiveness and practical applicability of the proposed framework in supporting resilient APHP planning under extreme weather conditions. These findings provide a scientific basis for resilience-oriented decision-making in APHP planning under extreme weather conditions.

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