Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change

Abstract

With the increasing energy prices and growing concerns over energy security, an accelerated transition to net zero carbon built environment has never been more important. Many studies have shown the capabilities of advanced control strategies such as model predictive control (MPC) to achieve energy efficiency, balance with thermal comfort and air quality. It has also shown its capability to provide demand flexibility, minimising peak load demands and maximising the production of renewable energy sources in buildings. This work investigates the potential of integrating price-responsive MPC with a low-temperature heating system and passive structural thermal energy storage (STES). Integration with a photovoltaic (PV) system is also explored. The system performance under future climate conditions is evaluated considering different design and operating conditions, including different thermal mass, occupancy patterns and internal heat gains, setpoint strategies and operation temperatures of the low-temperature heating system. The coupled model developed has been verified and validated with numerical and experimental data, and good agreement is observed. The results showed that mediumweight thermal mass and a medium-temperature (45 °C) under-floor heating inlet temperature provided a higher load shifting ability, based on a realistic occupancy profile for a residential building and a high tolerance setpoint strategy during unoccupied periods. The result also showed that higher low-price energy usage and lower heating energy usage could be achieved in future climate conditions. Finally, an increase in the load shifting ability was observed after the integration of rooftop solar PV system.