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DeepValve: Development and experimental testing of a Reinforcement Learning control framework for occupant-centric heating in offices

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The process synthesis and optimization methods used in this work include simulation of biomass gasification, hydrogen and synthetic natural gas production, and jet fuel production via a Fisher Tropsch unit. An energy integration approach, carried out by th ...

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Solar radiation reaching the surface of the earth for a period of one hour contains more energy than that consumed by mankind over an entire year. Some of this solar energy is already collected by photovoltaic cells to cover the electricity needs of buildi ...

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The aluminium remelting industry relies on natural gas to transform recycled aluminium into aluminium feedstock, entailing significant atmospheric emissions. Hydric resources are also affected as they are used as sinks of waste heat from the casting proces ...

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Occupant behavior, defined as the presence and energy-related actions of occupants, is today known as a key driver of building energy use. Closing the gap between what is provided by building energy systems and what is actually needed by occupants requires ...

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When it comes to residential buildings, there are several stochastic parameters, such as renewable energy production, outdoor air conditions, and occupants’ behavior, that are hard to model and predict accurately, with some being unique in each specific bu ...

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The application of Personal Comfort Systems (PCS) in the buildings demonstrated their potential to improve thermal comfort and reduce energy use by the space conditioning HVAC systems. With its personal controllability (on-demand) PCS is a practical soluti ...

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Customized Neural Network training to predict the highly imbalanced data of domestic hot water usage

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Despite space heating and cooling, the energy use for hot water production has not changed significantly over time and accounts for a big share in modern, well-insulated buildings. The main challenge of hot water generation lies in the highly stochastic na ...

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District energy network potentials in a city territory

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