Comprehensive Forecasting of Electrical Quantities in an Educational Building via Artifical Intelligence-Driven Distributed Measurement System

Sensors, Journal Year: 2025, Volume and Issue: 25(8), P. 2456 - 2456

Published: April 14, 2025

Recent environmental concerns have heightened attention toward new solutions across all fields to mitigate human impact. The power system community is also deeply committed addressing this issue, with research increasingly focused on sustainable practices. For instance, there a growing trend in designing buildings be net-zero emitters, while older structures are being retrofitted for energy efficiency achieve similar goals. To purpose, the study aims enhance management capabilities of an educational building by implementing smart infrastructure. Equipped photovoltaic panels and distributed measurement system, captures voltage current data calculates power. These electrical quantities then forecasted through AI-driven framework that manages data. paper details AI model used, including its experimental validation. results show provides reliable forecasts parameters. evaluation collected offers valuable insights, which support more informed actions optimizing performance. A key novelty lies exploration generalization nodes. This approach supported correlation analysis data, highlights potential accurate predictions case gaps. Moreover, ease deployment practical application were highlighted as factors scalability, allowing adaptation infrastructures.

Language: Английский

Evaluation of machine learning applications in building life cycle processes for energy efficiency: A systematic review

Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 4900 - 4916

Published: April 22, 2025

Language: Английский