Global warming, climate change and the energy crisis are trending topics around the world,
especially within the energy sector. The rising cost of energy, greenhouse gas (GHG) …

Mitigating climate change challenges in the built environment through the decarbonisation
of energy and construction materials remains a pressing challenge. The circular economy …

Daily peak load forecasting (DPLF) and total daily load forecasting (TDLF) are essential for
optimal power system operation from one day to one week later. This study develops a …

Accurate predictions for buildings' energy performance (BEP) are crucial for retrofitting
investment decisions and building benchmarking. With the increasing data availability and …

Prediction of building energy consumption using mathematical modeling is crucial for
improving the efficiency of building energy utilization, assisting in building energy …

The considerable amount of energy utilized by buildings has led to various environmental
challenges that adversely impact human existence. Predicting buildings' energy usage is …

Reducing the energy consumption of buildings in the public sector is an important
component in our efforts towards reaching our sustainability goals. In this context, a decisive …

Federated Learning (FL) enhances predictive accuracy in load forecasting by integrating
data from distributed load networks while ensuring data privacy. However, the …

The prediction of electricity consumption in a building is critical for recognizing the
possibilities for energy savings as a part of the digitalization of the built environment. This …

Federated Learning (FL) in load forecasting improves predictive accuracy by leveraging
data from distributed load networks while preserving data privacy. However, the …