Navigating Sustainable Energy Transitions and Environmental Constraints in PV Siting
持続可能なエネルギー転換を進める太陽光発電立地における環境制約の克服 (AI 翻訳)
Feihu Jiang, Zhanzhong Zhu, Shengyu Li, J F Zhang
🤖 gxceed AI 要約
日本語
本研究は、太陽光発電の拡大に伴う土地利用コンフリクトを解決するため、AHP（主観的政策選好）とCRITIC（客観的物理制約）を統合した加重最適化手法とGIS-TOPSISを組み合わせた空間意思決定支援フレームワークを提案する。中国7地域への適用結果、生態系や農地への圧迫を軽減しつつ再生可能エネルギー導入を調和させる有効性が確認された。
English
This study proposes a spatial decision support framework integrating AHP subjective policy preferences with CRITIC objective constraints and GIS-TOPSIS to address land-use conflicts from PV expansion. Applied to China's seven regions, it effectively mitigates ecological and agricultural land squeeze while harmonizing renewable energy deployment.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の再生可能エネルギー導入拡大においても、適地選定は重要な課題。本フレームワークは、地域ごとの環境制約と政策目標を統合する手法として参考になる可能性がある。
In the global GX context
Globally, this paper addresses the critical trade-off between renewable energy expansion and land-use conflicts. Its integrated MCDM framework offers a transferable methodology for spatial planning in other regions facing similar challenges.
👥 読者別の含意
🔬研究者:Provides a novel integration of AHP and CRITIC with GIS-TOPSIS for spatial decision-making in renewable energy siting.
🏢実務担当者:Offers a practical tool for balancing environmental constraints with renewable energy targets in spatial planning.
🏛政策担当者:Demonstrates how to reconcile macro climate goals with local environmental and land-use constraints through multi-criteria optimization.
📄 Abstract（原文）
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.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18083915first seen 2026-05-15 16:42:20
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