太陽光発電システムにおける故障診断と制御戦略：信頼性向上・寿命延長・廃棄削減に関する最近の進展
Fault Diagnosis and Control Strategies in Photovoltaic Systems: Recent Advances in Reliability Improvement, Lifetime Extension, and Waste Reduction (原題)
Iga Pietrucha, Krzysztof Barbusiński, Paweł Kwaśnicki
🤖 gxceed AI 要約
日本語
本レビューは2015〜2026年の太陽光発電システムの故障検出・診断・制御技術を体系的に整理する。電気的・モデルベース手法、熱・発光イメージング、AI、MPPT、耐故障制御を扱い、予知保全・RUL推定・デジタルツインと統合する。故障発生から検出・診断・予後・保守・信頼性向上・寿命延長・廃棄削減をライフサイクル枠組みで連結する点が特徴である。
English
This structured review synthesizes 2015–2026 literature on PV fault detection, diagnosis, and control, covering electrical/model-based methods, thermal and luminescence imaging, AI, MPPT, and fault-tolerant control. It integrates diagnostics with predictive maintenance, remaining-useful-life estimation, and digital twins within a lifecycle framework linking faults to reliability, lifetime extension, and waste reduction. Quantitative evidence tying diagnostics to added service years or avoided waste remains limited.
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FIT後の大量廃棄・再エネ主力電源化が政策課題であり、太陽光の長期安定運用と廃棄抑制はGX推進・循環経済政策に直結する。SSBJ開示とは直接の接続は薄いが、再エネ資産の維持管理・寿命延長は投資家の長期リスク評価に関わる。
In the global GX context
Globally, PV reliability and lifetime extension connect to transition finance and asset-level climate risk, while circular-economy indicators for solar waste are increasingly relevant to CSRD and sustainable-finance taxonomies. The review's lifecycle framing supports disclosure of operational resilience and resource efficiency in renewable portfolios.
👥 読者別の含意
🔬研究者:PV故障診断・予知保全・デジタルツイン研究の統合的な枠組みと未解決課題を把握できる。
🏢実務担当者:太陽光発電所の保守戦略・寿命延長・廃棄削減の意思決定に診断技術をどう組み込むかの示唆を得られる。
🏛政策担当者:再エネ廃棄物政策や長期運用インセンティブ設計において、診断・保守の役割を考慮する根拠となる。
📄 Abstract（原文）
The continuous growth of photovoltaic (PV) installations worldwide has increased the need for reliable and sustainable energy conversion systems. Failures occurring in PV modules, power electronic converters, and control units can significantly reduce energy production, accelerate component degradation, and shorten system lifetime. This structured narrative review synthesizes the literature published primarily between 2015 and 2026, with particular emphasis on studies from 2020 to 2026; earlier publications are included selectively when they provide foundational or normative concepts relevant to contemporary PV systems. The review examines recent developments in fault detection, diagnosis, and control techniques, including electrical and model-based methods, thermal and luminescence imaging, artificial intelligence, maximum power point tracking, and fault-tolerant control. Particular attention is given to the integration of diagnostics with predictive maintenance, remaining useful life estimation, digital twins, and operational decision-making. Rather than considering these areas independently, the review links fault occurrence, detection, diagnosis, prognostics, control or maintenance action, reliability improvement, service-life extension, and waste reduction within a common lifecycle-oriented framework. The available evidence indicates that early fault detection, targeted maintenance, and appropriate control can limit secondary damage, reduce unnecessary component replacement, and improve resource utilization, although direct quantitative evidence linking diagnostic actions to additional service years or avoided waste remains comparatively limited. The review also identifies current challenges related to cross-site generalization, multimodal data fusion, edge deployment, second-life qualification, and the integration of reliability and circular-economy indicators.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/app16199498first seen 2026-09-29 05:29:14
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