Optimal Chiller Loading Distribution Using Genetic Algorithm

• Main Authors: Jui-Kun Lin, 林瑞昆
• Other Authors: Yung-Chung Chang
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/56025246537289038113

碩士 === 國立臺北科技大學 === 冷凍與低溫科技研究所 === 91 === The chillers loading distribution methods include Equal Loading Distribution (ELD) method and Largrangian Multiplier (LGM) method at present. The ELD considers every chiller operating at equal part load ratio. This leads to the system power consumption being not at lowest and every chiller’s COP being not optimal. The LGM can find the optimal operation and conform to the system load, but the LGM will diverge if the initial condition isn’t suitable. The research method of the thesis is based on the Genetic Algorithm (GA). It has high accurate characteristic and can find the near optimal operation and conform to the system load, and can overcome the shortcomings described above. The purpose of the Optimal Chiller Load Distribution (OCLD) is to meet the system load and decides the chiller’s optimal part load ratio (PLR) to reduce the system power consumption. The kW-PLR curve and the COP-PLR curve of centrifugal chiller are usually non-linear polynomials, and kW-PLR curve is more reliable than COP-PLR. This thesis use a cubic equation to simulate the chiller’s kW-PLR curve and to find a set of chiller output which doesn’t violate the operating limits while minimizing the objective function. The Genetic Algorithm (GA) is adopted to find the near optimal solution of the function.