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Hybrid-Oriented Intelligent Operational and Architectural Foundations of IoT-Enabled Smart Grids: A System-Level Review and Challenge-Oriented Comparative Synthesis

IoT対応スマートグリッドのハイブリッド志向インテリジェント運用とアーキテクチャ基盤：システムレベルレビューと課題指向比較合成 (AI 翻訳)

Diachenko G, Laktionov I, Fainshtein D

Research Squareプレプリント2026-05-27#エネルギー転換
DOI: 10.20944/preprints202604.1327.v2
原典: https://doi.org/10.20944/preprints202604.1327.v2

🤖 gxceed AI 要約

日本語

本論文は、IoT対応スマートグリッドのインテリジェント運用とアーキテクチャに関するシステムレベルのレビューを提供する。データ駆動、モデル駆動、知識駆動、エージェントベース、ハイブリッド志向の各パラダイムを分析し、ハイブリッドアプローチが将来のスマートグリッド進化に最も有望であることを示す。また、運用課題と技術のクロスレイヤーマッピングを確立し、相互運用性、スケーラビリティ、調整の課題を特定する。

English

This paper provides a system-level integrative review of intelligent operational and architectural foundations for IoT-enabled Smart Grids. It analyzes data-driven, model-driven, knowledge-driven, agent-based, and hybrid-oriented paradigms, demonstrating that hybrid approaches are most promising for future smart grid evolution. It establishes cross-layer mapping between operational challenges and enabling technologies, identifying interoperability, scalability, and coordination constraints.

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

日本では再生可能エネルギー導入拡大に伴い、スマートグリッドの高度化がGX政策の鍵となる。本レビューは、異なるインテリジェント手法を統合するハイブリッドアプローチを提示し、SSBJや有報におけるエネルギー管理・気候リスク開示の基盤技術として参考になる。

In the global GX context

Globally, smart grids are critical for renewable integration and decarbonization. This review synthesizes hybrid intelligent approaches that combine AI, digital twins, and multi-agent systems, offering a roadmap for next-generation energy systems aligned with ISSB and TCFD disclosure requirements for climate resilience and transition planning.

👥 読者別の含意

🔬研究者:Provides a comprehensive taxonomy and comparison of intelligent paradigms for IoT-enabled smart grids, identifying research gaps and future directions for hybrid approaches.

🏢実務担当者:Offers a system-level framework for designing scalable, interoperable smart grid architectures that integrate AI and IoT for operational optimization.

🏛政策担当者:Highlights the need for standards and interoperability in decentralized energy ecosystems, informing regulatory support for smart grid infrastructure.

📄 Abstract（原文）

The rapid digitalization of energy systems and the increasing integration of distributed energy re-sources, renewable energy technologies, and prosumer-oriented infrastructures have accelerated the development of IoT-enabled Smart Grids as a foundation for intelligent and adaptive energy management. Modern Smart Grids increasingly depend on the coordinated interaction of IoT ar-chitectures, artificial intelligence, distributed analytics, and decentralized control mechanisms to ensure reliability, scalability, and real-time operational flexibility. Despite extensive research activ-ity, existing studies remain predominantly technology-centric, focusing on isolated architectural layers or individual intelligent methods without providing a unified system-level perspective on their coordinated operation and interoperability. This article presents a system-level integrative review and challenge-oriented comparative synthesis of intelligent operational and architectural foundations of IoT-enabled Smart Grids. The study analyzes data-driven, model-driven, knowledge-driven, agent-based, and hybrid-oriented intelligent paradigms within multi-layer IoT energy infrastructures. In addition, the research establishes a cross-layer mapping between Smart Grid operational challenges, enabling technologies, and corresponding analytical approaches while identifying interoperability constraints, scalability limitations, and coordination challenges associ-ated with decentralized energy ecosystems. The conducted synthesis demonstrates that hy-brid-oriented intelligent approaches represent the most promising direction for future Smart Grid evolution due to their ability to integrate AI, ML, digital twins, semantic reasoning, and decen-tralized multi-agent coordination within unified IoT architectures. The presented results provide a conceptual foundation for the prospective development of adaptive, interoperable, scalable, and explainable Smart Grid ecosystems integrating decentralized computing, distributed energy re-source coordination, vehicle-to-grid interaction, and intelligent cyber–physical orchestration.

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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。