The presence or absence of occupants in a building has a direct effect on its energy use,as it influences the operation of various building energy systems.Buildings with high occupancy variability,such as universities...The presence or absence of occupants in a building has a direct effect on its energy use,as it influences the operation of various building energy systems.Buildings with high occupancy variability,such as universities,where fluctuations occur throughout the day and across the year,can pose challenges in developing control strategies that aim to balance comfort and energy efficiency.This situation becomes even more complex when such buildings are integrated with renewable energy technologies,due to the inherently intermittent nature of these energy source.To promote widespread integration of renewable energy sources in such buildings,the adoption of advanced control strategies such as model predictive control(MPC)is imperative.However,the variable nature of occupancy patterns must be considered in its design.In response to this,the present study evaluates a price responsive MPC strategy for a solar thermal heating system integrated with thermal energy storage(TES)for buildings with high occupancy variability.The coupled system supplies the building heating through a low temperature underfloor heating system.A case study University building in Nottingham,UK was employed for evaluating the feasibility of the proposed heating system controlled by MPC strategy.The MPC controller aims to optimize the solar heating system’s operation by dynamically adjusting to forecasted weather,occupancy,and solar availability,balancing indoor comfort with energy efficiency.By effectively integrating with thermal energy storage,it maximizes solar energy utilization,reducing reliance on non-renewable sources and ultimately lowering energy costs.The developed model has undergone verification and validation process,utilizing both numerical simulations and experimental data.The result shows that the solar hot water system provided 63%heating energy in total for the case study classroom and saved more than half of the electricity cost compared with that of the original building heating system.The electricity cost saving has been confirme展开更多
文摘The presence or absence of occupants in a building has a direct effect on its energy use,as it influences the operation of various building energy systems.Buildings with high occupancy variability,such as universities,where fluctuations occur throughout the day and across the year,can pose challenges in developing control strategies that aim to balance comfort and energy efficiency.This situation becomes even more complex when such buildings are integrated with renewable energy technologies,due to the inherently intermittent nature of these energy source.To promote widespread integration of renewable energy sources in such buildings,the adoption of advanced control strategies such as model predictive control(MPC)is imperative.However,the variable nature of occupancy patterns must be considered in its design.In response to this,the present study evaluates a price responsive MPC strategy for a solar thermal heating system integrated with thermal energy storage(TES)for buildings with high occupancy variability.The coupled system supplies the building heating through a low temperature underfloor heating system.A case study University building in Nottingham,UK was employed for evaluating the feasibility of the proposed heating system controlled by MPC strategy.The MPC controller aims to optimize the solar heating system’s operation by dynamically adjusting to forecasted weather,occupancy,and solar availability,balancing indoor comfort with energy efficiency.By effectively integrating with thermal energy storage,it maximizes solar energy utilization,reducing reliance on non-renewable sources and ultimately lowering energy costs.The developed model has undergone verification and validation process,utilizing both numerical simulations and experimental data.The result shows that the solar hot water system provided 63%heating energy in total for the case study classroom and saved more than half of the electricity cost compared with that of the original building heating system.The electricity cost saving has been confirme
