Non-Intrusive Load Monitoring: A Systematic Review of Methods, Scenario-Specific Challenges, and Pathways to Practical Deployment
非侵入型負荷監視：手法、シナリオ固有の課題、実用展開への道筋に関する体系的レビュー (AI 翻訳)
Haotian Xiang, Wenjing Su, Yi Zong
🤖 gxceed AI 要約
日本語
本論文は非侵入型負荷監視（NILM）の手法を体系的にレビューし、リアルタイムフィードバックや需要応答などの実用化における課題を分析。データ品質やアルゴリズム転用性などの横断的課題も議論し、研究から実装への移行を促進する枠組みを提供する。
English
This paper systematically reviews event-based and state-based NILM methods, focusing on challenges such as real-time feedback, energy efficiency optimization, and demand response. It discusses cross-cutting issues like data quality and algorithm transferability, providing a scenario-based framework to bridge research and practical deployment for refined energy management and decarbonization.
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
日本でも省エネルギー・スマートグリッド推進が進む中、NILM技術は需要側のエネルギー可視化に有効。本レビューは実用化の障壁を整理しており、技術導入を検討する企業や自治体にとって参考となる。
In the global GX context
NILM is a key enabler for building and grid energy efficiency, supporting global decarbonization goals. This review offers a structured analysis of deployment challenges, relevant for utilities, energy service companies, and policymakers aiming to scale demand-side management and renewable integration.
👥 読者別の含意
🔬研究者:Provides a comprehensive taxonomy of NILM methods and challenges, useful for identifying research gaps in load disaggregation and edge computing.
🏢実務担当者:Highlights practical barriers (e.g., data quality, system integration) that companies must address when deploying NILM for energy management solutions.
🏛政策担当者:Illustrates how NILM can support demand response programs and energy efficiency policies, offering insights for regulatory frameworks.
📄 Abstract（原文）
Non-intrusive load monitoring (NILM), as a key technology for decomposing power loads by analyzing aggregate electrical signals, holds significant importance for advancing refined energy management and achieving carbon peaking and carbon neutrality goals. This paper systematically reviews the technical processes of event-based and state-based NILM methods. It focuses on analyzing key technical challenges in typical application scenarios, such as real-time feedback, energy efficiency optimization, and demand response. These challenges include balancing high real-time performance with accuracy, leveraging edge computing while ensuring privacy protection, and addressing issues like unknown load identification and user behavior modeling. Furthermore, this paper discusses cross-cutting challenges related to data quality, algorithm transferability, system integration, and cost. This review aims to provide a systematic, scenario-based analytical framework to facilitate the transition of NILM from theoretical research to practical application, offering insights for subsequent technological development and engineering implementation.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/en19081883first seen 2026-05-17 07:02:33 · last seen 2026-05-20 05:15:46
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