Comparative Evaluation of PID, MPC and Fuzzy Logic Control Strategies for Energy Transfer Stations in District Cooling Networks

Energy transfer stations (ETS) play a vital role in district cooling networks by facilitating thermal energy transfer between central chilled water plants and connected buildings. Effective control of ETS is crucial to maintain optimal temperature conditions and energy efficiency. However, traditional proportional-integral-derivative (PID) control may not always provide robust performance under changing operating conditions. This study aimed to evaluate and compare the control performances of PID, model predictive control (MPC), and fuzzy logic control (FLC) for an ETS process. A dynamic model of an ETS system incorporating a plate heat exchanger, control valve, temperature sensors and disturbances was developed. PID, MPC and FLC controllers were designed and tuned using the model. Controller performances were assessed through simulation-based experiments under setpoint changes and disturbances. Performance metrics such as rise time, settling time, overshoot, peak time and integral error were analyzed. Results showed that the MPC approach achieved the fastest rise time and lowest overshoot compared to PID and FLC. Meanwhile, FLC offered more robust control with minimal variations in performance metrics under changing conditions. Overall control effort was also lower with MPC and FLC. Proper selection of control strategy based on system requirements could help prevent issues like low delta-T syndrome in district cooling networks.