gxceed
← 論文一覧に戻る

A conceptual study examining solar energy adoption for community resilience

コミュニティのレジリエンスのための太陽エネルギー導入に関する概念的研究 (AI 翻訳)

Lisa Bosman, József Kádár, Esteban Soto, Amy LeGrande, Brandon Yonnie, Rhea Dutta

Environment Systems & Decisions📚 査読済 / ジャーナル2026-06-12#再生可能エネルギーOrigin: Global
DOI: 10.1007/s10669-026-10099-6
原典: https://doi.org/10.1007/s10669-026-10099-6
📄 PDF

🤖 gxceed AI 要約

日本語

この概念研究は、気候変動による異常気象の増加に対し、太陽光発電(PV)とバッテリー蓄電を組み合わせたシステムがコミュニティレベルの緊急時電源として有効であることを検討している。仙台防災枠組の4つの優先事項を分析の枠組みとして用い、太陽エネルギーが災害リスクの理解、ガバナンス強化、リスク削減への投資、および復旧対応の準備にどのように貢献するかを論じている。課題としてコスト、インフラ整備、規制枠組み、公平なアクセスが挙げられる。

English

This conceptual study examines solar photovoltaic (PV) systems with battery storage as a resilient and sustainable alternative for community emergency power in the face of increasing extreme weather events due to climate change. Using the Sendai Framework for Disaster Risk Reduction (2015-2030) as an analytical lens, it explores how solar energy contributes to understanding disaster risk, strengthening governance, investing in risk reduction, and enhancing preparedness. Challenges in cost, infrastructure readiness, regulatory frameworks, and equitable access are acknowledged.

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

日本では、災害時におけるエネルギー安全保障が重要な課題であり、太陽光発電と蓄電池の組み合わせは、停電時のレジリエンス向上に寄与する。本稿は、仙台防災枠組を参照することで、防災政策との連携を示唆しており、自治体やBESS(蓄電所)導入の検討に有用。

In the global GX context

Globally, this study aligns with the Sendai Framework and highlights the role of decentralized renewable energy in disaster risk reduction. It contributes to the growing literature on climate adaptation and energy resilience, relevant for regions vulnerable to extreme weather.

👥 読者別の含意

🔬研究者:Provides a conceptual framework linking solar energy adoption to disaster risk reduction using the Sendai Framework, offering a lens for empirical research.

🏢実務担当者:Offers insights for community planners and emergency managers on integrating solar-plus-storage as a resilient backup power solution, but lacks specific implementation details.

🏛政策担当者:Reinforces the value of integrating renewable energy into disaster risk reduction policies, supporting investment in decentralized energy infrastructure.

📄 Abstract(原文)

Abstract The increasing frequency and severity of extreme weather events due to climate change have exposed major vulnerabilities in conventional power systems, often resulting in prolonged blackouts and critical service disruptions. Traditional backup solutions, such as diesel generators, provide only short-term relief and are constrained by fuel availability, logistical challenges, and significant environmental impacts. This conceptual study explores solar energy, specifically photovoltaic (PV) systems paired with battery storage, as a resilient and sustainable alternative for community-level emergency power. Advances in smart grid technologies now enable the integration of decentralized renewable energy systems, enhancing both resilience and energy efficiency. This conceptual study is grounded in the Sendai Framework for Disaster Risk Reduction (2015–2030), using its four priorities as an analytical lens to examine how solar energy contributes to community resilience: (1) understanding disaster risk through improved visibility of energy-system vulnerabilities and climate-risk linkages; (2) strengthening disaster risk governance by enabling decentralized, adaptive, and policy-integrated energy systems; (3) investing in disaster risk reduction through distributed solar infrastructure, cost savings, and local economic benefits; and (4) enhancing preparedness for response and recovery through technologies such as real-time monitoring, peer-to-peer energy sharing, microgrids, and energy storage systems. Despite these advantages, challenges remain in cost, infrastructure readiness, regulatory frameworks, and equitable access.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。