Test and evaluation of energy saving potentials in a complex building central chilling system using genetic algorithms
This article presents the test and evaluation of energy saving potentials of complex building central chilling systems using genetic algorithm (GA). The evaluation was conducted based on a simulated virtual system representing the actual complex central chilling system in a super high-rise building in Hong Kong. GA was used as the optimisation tool to search for globally optimal control settings. The simulated virtual system was used as the test platform and acted as the performance predictor in estimating the overall system performance and responses to the changes of control settings. The test results show that about 4.54—5.06% daily energy in the system studied can be saved by using optimal control settings, as compared to that using the conventional control settings. The results also show that the evaluation process by using the simulated virtual system and the GA optimiser is time costly due to strong dynamic effects of the simulated virtual system and the optimisation principle of GA.
Practical applications: This article presents an approach for evaluating energy saving potentials of complex central chilling systems using GA. This approach can be used to identify maximum energy saving potentials in air-conditioning systems by optimising the major control variables simultaneously. The results can be used to guide the development of advanced control and optimisation strategies suitable for practical applications.