Stochastic Model Predictive Control (SMPC) is a control strategy that can be used to optimize the energy efficiency of building climate control systems. It uses predictions of future weather conditions to anticipate changes in the building’s thermal loads and adjust the heating, ventilation, and air conditioning (HVAC) system accordingly.
Weather predictions provide information about the temperature, humidity, and other meteorological conditions that will affect the building’s thermal loads. This information is used to model the building’s response to these conditions and predict the energy consumption of the HVAC system. The SMPC algorithm then uses this information to optimize the HVAC system’s operation, by adjusting the setpoints of the heating and cooling system, to minimize energy consumption while maintaining a comfortable indoor environment.
Building climate control systems generally fall into two categories: open-loop and closed-loop control systems. Open-loop systems operate based on pre-determined schedules or fixed setpoints, without any feedback from the building or the occupants. Closed-loop systems, on the other hand, use feedback from sensors to adjust the HVAC system in real-time. SMPC is a type of closed-loop control system.
In order to use SMPC for energy-efficient building climate control, several types of sensor data are typically used. These include indoor temperature and humidity, outdoor temperature and humidity, solar radiation, and occupancy. These sensors are used to measure the building’s thermal loads, which are used to predict the energy consumption of the HVAC system.
For example, a building equipped with SMPC may use weather predictions to anticipate a heat wave, and adjust the HVAC system accordingly. The algorithm may adjust the setpoints of the cooling system to lower temperatures in anticipation of the heat wave, reducing the energy consumption of the HVAC system during the heat wave.
The amount of energy that can be saved using SMPC depends on the specific building and HVAC system, as well as the accuracy of the weather predictions. However, it has been reported that SMPC can lead to significant energy savings, typically in the range of 5-15%.
In addition to energy savings, SMPC also has other benefits, such as improved comfort for the building occupants and reduced wear and tear on the HVAC system. It also allows building operators to better manage the energy consumption of the building and reduce costs associated with energy consumption.
It’s important to note that, while SMPC can be a powerful tool for energy-efficient building climate control, it relies heavily on accurate weather predictions and high-quality sensor data. Inaccurate weather predictions or sensor failures can lead to sub-optimal performance of the SMPC algorithm.