Dynamic Modeling and Model-Free Real-Time Optimization for Cold Climate Heat Pump Systems
Air source heat pump (ASHP) has been a well-received technology to provide space and/or water heating for building and industrial applications, while its efficiency and heating capacity can be severely limited when operated in cold climate. Various modifications have been proposed for cold-climate operation of ASHP over the single-stage refrigeration cycle, such as vapor injection techniques and cascade configuration. However, there has been a lack of effective control strategies for such systems to maintain the optimal energy efficiency for operations across different combinations of ambient and load conditions. Previous work has paid great efforts in model based strategies, anchored on deriving system models with simulation and experimental testing. Such approaches can be prohibitively expensive due to the inherent nonlinear nature of refrigeration systems and unmeasurable equipment degradation. This dissertation investigates on model-free control strategies for real-time efficiency optimization for several configurations of cold-climate ASHP, by use of Extremum Seeking Control (ESC). By utilizing periodic dither inputs for online gradient estimation, ESC bears significant robustness against process variation and external disturbance, which has proved to be more advantageous in handling the challenging applications like heating, ventilation and air conditioning (HVAC) systems. Three types of ASHP configurations are studied in this dissertation: the internal heat exchanger vapor injection, flash-tank vapor injection, and cascade configuration. For both vapor injection ASHP configurations, the intermediate pressure setpoint is optimized by standard ESC and Newton-based ESC based on the feedback of the total power consumption, with the constant heating load considered. For the cascade ASHP, multivariable ESC is designed to handle two operational scenarios: minimizing the total power for fixed heating capacity and maximizing the coefficient of performance (COP) for variable heating capacity. For the power based ESC, the manipulated inputs include the intermediate temperature, high temperature cycle superheat and low temperature cycle superheat; while for the COP based ESC, the high- and low-temperature cycle compressor speeds and evaporator fan mass flow rate are adopted as inputs. The proposed ESC strategies are evaluated with Modelica based dynamic simulation models of the three system configurations. Simulations have been conducted under both fixed and realistic ambient temperature profiles. The simulation results show good steady-state and transient performance of real-time efficiency optimization with the proposed strategies, in terms of tracking unknown and dynamic optimum settings.