| Central chiller plant is one of the main forms of a central air conditioning system.The control strategy affects the operating energy consumption of the system,so the development of a reasonable strategy is of great significance to the energy-saving operation of the system.The control strategy optimization method based on modeling and simulation is one of the important ways to reduce the energy consumption of the system.Although the research on control strategy based on simulation is not rare.However,the traditional building energy system simulation program usually uses the static device models and the virtual and simplified handling of the control process makes it difficult to fit the actual control system and simulate its operation.This thesis takes practical central chiller plant in Shanghai as the research object.Firstly,Modelica is used as the modeling and simulation language to construct the system simulation model of thermal,hydraulic and control coupling.Then based on the measured data,the device models are calibrated using the least-squares method and the co-simulation optimization method.The system composed of the calibrated model was simulated.Compared with the measured results,the normalized mean bias error of the total energy consumption of the system was 5.78%,and the calibrated simulation system was taken as the baseline.The model-based control method is used as the controller of the system supervision level to control the on/off of the equipment and specify the optimal setpoint for the local controller.The sequential optimization method and the particle swarm optimization algorithm were used to optimize the operating number of the devices,the differential pressure setpoint,the chilled water outlet temperature setpoint and the supply air temperature setpoint.The results show that the total daily energy consumption of the system can be reduced by 7.09～10.03% within one week. |
