Integrated demand response method for heating multiple rooms based on fuzzy logic considering dynamic price

We consider an educational building heated by a combination of district heating (DH) and a local air source heat pump. We have developed an integrated demand response method for multiple rooms, consisting of an optimization layer and a control layer, to maintain thermal comfort and save energy and costs. For the optimization layer, we apply fuzzy logic to adjust indoor temperature setpoints to respond to dynamic heat prices and propose an optimal heat supply method to find optimal heat supply schemes. For the control layer, a multi-objective model predictive control (MPC) has been developed to manage indoor thermal conditions across multiple rooms. To test and verify the integrated demand response method, we build a multi-room simulation model using the CARNOT Toolbox. The results show that adopting different indoor temperature setpoints during working and nonworking hours, combined with the MPC method, has an energy-saving potential of 9.1 % compared to maintaining a constant indoor temperature using DH alone. Adjusting temperature setpoints using fuzzy logic utilizes the building's heat storage capacity to increase energy flexibility, reaching 16.0 % savings in energy and reducing 12.6 % heating costs.