From Energy Flow Regimes to Regime Dynamics: A Window-Based Hidden Markov Modeling Framework for Photovoltaic–Building Systems
エネルギーフローレジームからレジームダイナミクスへ：太陽光発電・建物システムのためのウィンドウベース隠れマルコフモデリングフレームワーク (AI 翻訳)
Andrzej Marciniak, Agnieszka Dudziak, Katarzyna Piotrowska, Arkadiusz Małek
🤖 gxceed AI 要約
日本語
本研究は、太陽光発電・建物統合システムの高解像度データを用いて、運転レジームとその遷移を特定するウィンドウベースの分析パイプラインを提案する。エネルギー流の分解、スライディングウィンドウ、隠れマルコフモデルを組み合わせ、短期的な行動パターンと遷移経路を捉える。結果、システムは少数の持続的レジームに支配され、遷移は中間状態を介して構造化されることを示す。
English
This study proposes a window-based analytical pipeline to identify operating regimes and their dynamic transitions in an integrated PV-building energy system, combining energy flow decomposition, sliding windows, and hidden Markov modeling. Results show that system operation is dominated by a few persistent regimes with diurnal organization, and transitions are structured through intermediate states. The framework enhances interpretability and supports advanced monitoring of integrated energy systems.
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
日本の再生可能エネルギー導入拡大に伴い、PV建物システムの効率的運用は重要。本手法は、建物のエネルギー管理システム（BEMS）の高度化や、FIT後の自家消費最適化に貢献する可能性がある。
In the global GX context
Globally, as PV-building integration grows, understanding operational dynamics is key for grid stability and demand-side management. This framework offers a process-oriented approach that could inform smart building controls and energy management systems, aligning with broader energy transition goals.
👥 読者別の含意
🔬研究者:Provides a novel method for analyzing PV-building system dynamics using HMM, useful for energy systems research.
🏢実務担当者:Can be applied to enhance building energy management systems for better operational efficiency.
📄 Abstract（原文）
High-resolution measurement data from photovoltaic–building systems enable analyses that extend beyond static energy balances toward the temporal structure of system operation. This study proposes a window-based analytical pipeline to identify operating regimes and their dynamic transitions in an integrated PV–building energy system. The approach combines energy flow decomposition, sliding temporal windows, and hidden Markov modeling to capture short-term behavioral patterns, regime persistence, and transition pathways. The results indicate that system operation is dominated by a limited number of persistent regimes with a pronounced diurnal organization. Regime transitions are structured and directional, typically occurring through intermediate operating states rather than via abrupt switching between energetically extreme conditions. The analysis of regime residence times reveals distinct characteristic temporal scales associated with different operating modes. Overall, the proposed framework provides a process-oriented representation of PV–building system dynamics that enhances interpretability and supports advanced monitoring and analysis of integrated energy systems.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/en19143371first seen 2026-08-07 04:54:57
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
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。