Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades …
Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the …
The increasing world population and availability of energy hungry smart devices are major reasons for alarmingly high electricity consumption in the current times. So far, various …
H Zhao, F Magoulès - Renewable and Sustainable Energy Reviews, 2012 - Elsevier
The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, the operation of sub-level …
X Li, J Wen - Renewable and Sustainable Energy Reviews, 2014 - Elsevier
Abstract Buildings consume about 41.1% of primary energy and 74% of the electricity in the US Better or even optimal building energy control and operation strategies provide great …
A Foucquier, S Robert, F Suard, L Stéphan… - … and Sustainable Energy …, 2013 - Elsevier
In the European Union, the building sector is one of the largest energy consumer with about 40% of the final energy consumption. Reducing consumption is also a sociological …
Three main groups of internal and external influencing factors have been identified through this review, including building characteristics, equipment and technologies, and occupant's …
T Ahmad, H Chen - Sustainable Cities and Society, 2020 - Elsevier
Energy forecasting and planning play an important role in energy sector development and policy formulation. The forecasting model selection mostly based on the availability of the …
This paper reviews occupancy based model predictive control (MPC) for building indoor climate control. Occupancy behavior in buildings is stochastic and complex in nature. With …