Grey-box modeling, as one of the three fundamental modeling techniques for building
energy models, has many advantages compared with black-box modeling and white-box …

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 …

Three main groups of internal and external influencing factors have been identified through
this review, including building characteristics, equipment and technologies, and occupant's …

The energy performance in buildings is influenced by many factors, such as ambient
weather conditions, building structure and characteristics, the operation of sub-level …

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 …

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 …

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 …