Proposes a decision support framework to balance land use and environmental constraints in renewable energy planning, highlighting socio-economic impacts in China.
The rapid expansion of photovoltaic (PV) power has escalated land-use conflicts, making spatial planning a complex socio-economic challenge. Existing Multi-Criteria Decision-Making (MCDM) methods often fail to reconcile top-down macro-climate goals with bottom-up local environmental and infrastructural constraints. To address this dilemma, this study proposes a novel spatial decision support framework integrating a mathematical compromise weighting method-optimizing AHP subjective policy preferences and CRITIC objective physical constraints with GIS-TOPSIS. Applied to China’s seven major geographic regions, the model accurately identifies four socio-economic evolutionary paradigms dictating PV spatial patterns. The results demonstrate that our framework effectively mitigates ecological and agricultural land squeezes, offering a robust tool for policymakers to harmonize renewable energy deployment with sustainable environmental management.
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Jiang et al. (2026) studied this question.
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