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AI in Energy Management Strategies for Environmental Sustainability

環境持続可能性のためのエネルギー管理戦略におけるAI (AI 翻訳)

Mamta

ジャーナル2026-04-20#エネルギー転換Origin: Global
DOI: 10.1201/9781003592204-10
原典: https://doi.org/10.1201/9781003592204-10

🤖 gxceed AI 要約

日本語

本論文は、人工知能（AI）がエネルギー管理と環境持続可能性にどのように貢献するかを包括的に検討する。ビル、産業、電力網、貯蔵システムにおけるAI応用を解説し、データセキュリティやプライバシー保護などの実装上の考慮事項も扱う。ケーススタディを通じて持続可能性の改善効果を示し、将来の技術展望を提供する。エネルギー技術者や政策立案者にAI導入の指針を与える。

English

This chapter examines how AI technologies enhance energy management for environmental sustainability. It covers AI applications in buildings (HVAC, lighting), industrial processes, electrical grids (demand response, renewable integration), and storage systems, along with implementation considerations like data security. Case studies demonstrate measurable sustainability improvements, and future emerging technologies are explored. It serves as a resource for engineers, facility managers, and policymakers.

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

本論文は日本のGX文脈に特化した内容ではないが、AIによるエネルギー管理の基本概念を網羅しており、日本の事業者がスマートグリッドやZEB（ネット・ゼロ・エネルギー・ビル）導入を検討する際の基礎知識として有用。

In the global GX context

This paper provides a broad overview of AI for energy management, relevant to global energy transition efforts. It aligns with TCFD/ISSB frameworks that encourage technological innovation for decarbonization, though it lacks specific disclosure or policy linkages.

👥 読者別の含意

🔬研究者:Provides a structured overview of AI applications across energy domains, serving as a starting point for further research into specific technologies.

🏢実務担当者:Offers practical examples of AI-driven energy efficiency measures in buildings, industry, and grids, useful for corporate sustainability teams planning technology adoption.

🏛政策担当者:Supports the case for integrating AI into national energy strategies and provides a framework for evaluating AI's role in sustainability targets.

📄 Abstract（原文）

This chapter examines the critical intersection of artificial intelligence, energy management, and environmental sustainability, highlighting how AI technologies are becoming essential tools in addressing global climate challenges through smarter energy utilization. AI systems are revolutionizing energy management across multiple domains: in buildings, through intelligent HVAC and lighting systems that respond to occupancy patterns; in industrial settings, by optimizing complex processes and reducing carbon footprints; in electrical grids, by enabling dynamic demand response and seamless integration of intermittent renewable energy sources; and in storage systems, through predictive algorithms that maximize efficiency and reliability. The chapter addresses vital implementation considerations, including data security protocols, privacy safeguards, and practical deployment strategies, supported by case studies that demonstrate measurable sustainability improvements. Environmental impact assessment methodologies and emerging technologies are explored to provide forward-looking perspectives for continued innovation. This comprehensive analysis serves as an invaluable resource for energy engineers, facility managers, sustainability officers, and policymakers seeking to implement AI-driven solutions for environmental impact reduction. The vision presented establishes a pathway toward truly intelligent energy systems that balance human needs with environmental imperatives, creating a foundation for sustainable energy management in an increasingly resource-constrained world.

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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。