| Summary: | 碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 97 === The technology industry is facing fierce market competition today. If companies in this industry are able to cut back on energy expenses, their competitiveness will be substantially uplifted. Among the energy expenses, power consumption from air-conditioning takes up the largest portion; therefore, cutting back expenses by lowering the power consumption from air-conditioning should yield instant effect. In an air-conditioning System, the chiller consumes 60% of energy, the pump system 20%, and the air side facilities 20%. Since the chiller takes up over half of the power consumption, the current researches on air-conditioning system energy optimization concentrate mainly on the control of the chiller. The rest parts of a system are hardly researched because energy optimization can hardly be achieved as the configuration is often adjusted through experience even when an inverter is installed.
This research adopts the heat transfer equation developed by foreign scholars and uses regression analysis to establish the power consumption model of each component. Simulated Annealing algorithm (SA) is then used to find the best configurations of chilled water supply temperature, supply air flow, and water flow, targeting on the interrelationships among the chiller, air handing unit, and zone pump. SA is an algorithm with simple structure and randomness. It is applicable to a wide range of calculations, no matter whether it is a serial objective function or it can be differentiated, and probability function and control parameter-“temperature” can be used to determine if the results are accepted as new results. Therefore, by supplying the SA method, the algorithm is enabled to break away from the local minimum. This thesis configures the total power consumption of the system as the objective function and achieves the minimum overall air-conditioning system power consumption under the criteria of achieving the cooling capacity that satisfies the loading requirement. From the results, we find that power consumption is lowered by 17.15% if we compare the power consumption of the system using the three best operation parameters derived in this research to a system without any adjustments. It shows that this research indeed uncovers the best parameters for air-conditioning system operation that achieves the objective of power-saving.
|
|---|
