エネルギー管理システムのためのAI
AI for Energy Management System (原題)
Dr. V. SRIDEVI, STEPHY ANGELIN J, Dr. SANJAY L. KURKUTE, Dr. A. SATHISHKUMAR
🤖 gxceed AI 要約
日本語
本書は、スマートで効率的かつ持続可能なエネルギーシステム構築におけるAI応用を包括的に解説する。機械学習による需要予測、最適化、再生可能エネルギー統合、スマートグリッド技術、IoT監視、予知保全、サイバーセキュリティ、デジタルツイン、Edge AI、説明可能AIなどを扱い、将来のトレンドと機会を示す。
English
This book comprehensively explores AI applications for smart, efficient, and sustainable energy systems. It covers machine learning for demand forecasting, optimization, renewable integration, smart grids, IoT monitoring, predictive maintenance, cybersecurity, digital twins, edge AI, and explainable AI, concluding with future trends and opportunities.
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GX文脈では、再エネ導入拡大と需給調整力の確保が課題であり、AIによる需要予測や系統運用の高度化は重要。本書はエネルギー管理の実務に役立つが、SSBJや開示への直接的な示唆は限定的。
In the global GX context
Globally, AI-driven energy management is critical for integrating renewables and enhancing grid flexibility. This book provides a broad overview useful for practitioners, though it lacks specific focus on disclosure frameworks or transition finance.
👥 読者別の含意
🔬研究者:Provides a broad overview of AI techniques applied to energy systems, useful for identifying research gaps in AI-driven optimization and forecasting.
🏢実務担当者:Offers practical insights into AI tools for energy efficiency, demand response, and predictive maintenance, aiding corporate sustainability teams in operational decarbonization.
🏛政策担当者:Highlights the potential of AI in grid management and renewable integration, informing policies that support AI adoption in the energy sector.
📄 Abstract（原文）
AI for Energy Management Systems explores the application of Artificial Intelligence in developing smart, efficient, reliable, and sustainable energy systems. The book covers AI and Machine Learning techniques, energy prediction and demand forecasting, intelligent energy optimization, demand-side management, renewable energy integration, energy storage, and smart grid technologies. It also discusses IoT-based monitoring, fault detection, predictive maintenance, cybersecurity, Digital Twins, Edge AI, and Explainable AI. The book concludes with emerging trends and future opportunities for AI-driven energy management and sustainable power systems.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/22076054first seen 2026-08-25 04:12:35 · last seen 2026-08-26 04:13:15
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