Energy Consumption Forecasting in Government Buildings Using Machine Learning

• Author(s): Akalya P; Dr. Haripriya V
• Paper ID: 1717926
• Page: 2558-2567
• Published Date: 19-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

Abstract

Government buildings represent a significant yet underexplored domain in machine learning-based energy forecasting. Existing studies predominantly target residential or commercial facilities, leaving a critical contextual gap for public sector infrastructure, which operates under rigid occupancy schedules, multi-department load diversity, and policy-driven operational constraints. This paper presents a structured review of 15 IEEE-indexed publications (2021–2026) on ML-based building energy consumption forecasting, analysing methodologies, datasets, model architectures, and key limitations. Thematic classification identifies five major research directions: classical regression ML, deep learning and LSTM-based approaches, hybrid and ensemble methods, IoT-integrated systems, and neuro-fuzzy approaches. Systematic gap analysis reveals ten critical deficiencies — including absence of government building datasets, exclusion of occupancy features, lack of real-time deployment validation, limited interpretability, and insufficient multi-department modelling — and maps targeted research questions and objectives. A novel intelligent occupancy-aware ML-based energy consumption forecasting framework is proposed, aimed at improving forecast accuracy, enabling near-real-time energy management, and supporting data-driven sustainability decisions in government infrastructure.

Keywords

Energy Consumption Forecasting, Government Buildings, Machine Learning, LSTM, Random Forest, Hybrid Ensemble, Occupancy-Aware Features, Smart Buildings, Time-Series Forecasting, Sustainable Energy.

Citations

IRE Journals:
Akalya P, Dr. Haripriya V "Energy Consumption Forecasting in Government Buildings Using Machine Learning" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 2558-2567 https://doi.org/10.64388/IREV9I11-1717926

IEEE:
Akalya P, Dr. Haripriya V "Energy Consumption Forecasting in Government Buildings Using Machine Learning" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717926