Study On Operation Optimal Control Of Ground Source Heat Pump System (GSHPS) Based On Dynamic Process Model

The proportion of building energy consumption to total social energy consumption is increasing gradually. In the total life cycle of building, the operation energy consumption has an important role in building energy saving. Enhancing utility efficiency of HVAC is crucial to building energy saving. Ground source heat pump system (GSHPS), which has advantages of energy saving, environmental protection and high reliability, is regarded as an air conditioning technique having the greatest developmental future in the 21st century. So GSHPS is developed rapidly and applied widely all over the world. As a complex system engineering, it attracts more attention and many in-depth researches are implemented in the last decades. However, most of the studies focus on heat transfer of geothermal heat exchangers, enhancing heat transfer performance, designing method, simulation and testing of GSHPS and are mainly used as theoretical guidance in the designing of GSHPS. If continuously maintaining the GSHPS running at its optimum operating condition, despite the changes of environmental condition and equipment behavior, and digging the energy saving potential to the greatest extent, it is possible to achieve an important performance improvement. Continuous tracking and driving the process to its best operating conditions are termed as optimizing control. The essence of optimal control for GSHPS is to analyze dynamic characteristic with respect to energy. So Theoretical and experimental study on GSHPS optimal control is carried out in this dissertationGSHPS is continuously subjected to a variety of disturbances during operation. Design and implementation of optimizing control are strongly depended on the characteristics of the disturbances. The process disturbances of GSHPS are divided in two categories:one is fast varying disturbances which are irrelevant for the long term optimization of the process; another is relatively slow varying disturbances which have a significant impact on the optimum economic performance of the GSHPS. Thus the multilayer approach of hierarchical control theory based on the control task decomposion can be used to synthesis the control structure to reduce the mathematical complexity. Based on the analysis of feasibility and characteristics, a multilevel hierarchical control structure scheme for GHSPS including regulatory layer, optimization layer and dynamic adaptive layer is proposed. The regulatory layer takes care of the control tasks of keeping the controlled variables at given set-points, and suppress the influence of the "fast varying" uncontrolled disturbances. The optimization layer takes care of the optimizing control tasks, where the objective is to determine optimum set-points based on an appropriate performance criterion and a mathematical process model. The purpose of the adaptive layer is to compensate for model-induced errors by adjusting the model parameters. This control structure supplies the theoretic frame to further research.Process model of GSHPS is the foundation to realize the optimal control. GSHPS consist of water-to-water heat pump and geothermal exchanger (GHE), whose dynamic model act as the model structure in parameter identification phase. And corresponding steady model supplies necessary constraint condition for optimal layer. Water-to-water heat pump consists of evaporator, condenser, expansion valve and compressor in more detail. The spatially distributed heat exchanger including evaporator and condenser are partitioned into spatial zones in the model formulation stage, and lump parameter method model spatial zones based on the first principle. Coupled with compressor and expansive valve of steady model, an apace state model described by state variable and input variable is established. To verify the validity of modeling procedure of heat pump, the simulation outputs were compared with the corresponding values reported in reference papers and the results validate the accuracy of the model.GHE couple with water-to-water heat pump through energy carrier media and affect each other mutually. Under the assumption of the finite line source and considering the heat conduction and heat advection effect, mathematical GHE model is established. The analytical solution of temperature-field distribution is obtained by utilizing Green function method. The analytical solution under the condition of pure heat conduction is a special case. In the internal of bore well the thermal conduction of single U-tube and double U-tube is modeled and temperature distribution along the vertical of bore well is obtained using energy balance principle, thus the input and out temperature of GHE can be calculated.To achieve faster convergence to the optimum operating region, and to cope with persistent disturbances, a nonlinear non-steady-state process model is identified in the identification phase by change manipulative to make mismatch error between model and real system minimum. The identification result is transfer to optimal layer to revise optimal model to make optimal solution approach to the genuine optimal solution. According to the maximum likelihood estimate method, the parameter identification transform nonlinear program problem. Avoid complicated mathematical deduction. And a priori parameter information is included in the minimization criterion, thus this makes the estimation problem more robust with respect to missing process excitations and over-parameterization. Furthermore, by theory analysis the GSHPS model exit uniqueness solution and parameter identifiability are proved。Based on the improved scatter search algorithm and the local search SQP algorithm that fit continuity space optimization, a new mixing algorithm SS-SQP is proposed. Comparing to SS and GAS, the result of parameter identification shows that this new mixing algorithm can improve computing efficiency.According to the above optimal control structure, the operation optimal model for the global system is established, which the objective function, constraint condition and manipulate variable is defined. Each of the components is coupled and influence interactively. Optimization problem of GSHPS is nonlinear in both objective function and constraint conditions. The updated steady-state part of the process model is used to optimize the economic performance of the process, where new optimum set-points are calculated for the regulatory control system. Through simulating, effecting factors of bore well temperature, return water temperature and load ratio are investigated. Whenever operating under the heating or cooling mode, the total energy consumption can be decreased by the optimal control compared to constant water volume, and the system COP can be improved.Finally, experimental studies on GSHPS are carried out. Comprehensive thermal conductivity coefficient and initial temperature of soil are obtained. And then the GHSPS model is verified. To demonstrate the feasibility and reliable of optimal control, the set values in control loops are adjusted to their optimal values. Then the total system energy consumption is compared with that before optimization, and the result shows that the total energy consumption decreases after optimization, and the GSHPS can operate reliable and stably.