Development and Selection of Load Forecasting Techniques for Non-Residential Buildings

• Published in: 2024 18th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) pp. 1 - 6
• Main Authors: Massucco, S., Mosaico, G., Saviozzi, M., Almaleck, P., Santarelli, M., Serra, P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24-06-2024
• Subjects: Accuracy; building management system; Buildings; Key performance indicator; load demand; Load forecasting; Probabilistic logic; Radio frequency; Training
• ISSN: 2642-6757
• DOI: 10.1109/PMAPS61648.2024.10667140

Non-residential buildings account for a significant portion of energy consumption and greenhouse gas emissions among all structures. A key element of their Building Management System (BMS) is the electrical load forecasting functionality. As numerous techniques have been developed for load forecasting, adaptability has emerged as a fundamental feature of a robust forecasting system, given that no single technique outperforms all others. In this paper, we evaluate a diverse pool of twelve load forecasting techniques for a hourly 24-hour-ahead load forecasting task across four real non-residential building datasets using two Key Performance Indicators (KPIs). The results demonstrate that the diversity of the pool is essential for producing the most accurate forecasts.