|Title:||Model-based optimization of centrifugal chiller seawater condenser using global cost function of operation cycle|
Hong Kong Polytechnic University -- Dissertations
Department of Building Services Engineering
|Pages:||xiv, 91 leaves : ill. ; 30 cm|
|Abstract:||In this paper comprehensive models predicting the energy cost, maintenance cost and risk constraint for the evaluation of the optimum cleaning cycle of condenser is presented. The models are used to compile a cost function that would be used in optimizing the cycle of the condenser's cleaning of the Centrifugal Chiller Plant. Two models, namely the condenser scale build-up model and chiller efficiency model, are established in the Energy Cost to calculate the extra electrical energy incurred due to the build- up of scale when routine cleaning of the condenser tubes is not due carried out. The scale build-up model, which is introduced to replace the sophisticated thermodynamic equation in heat transfer coefficient analysis, is found slightly susceptible to the change in seawater temperature whereas the chiller efficiency model is defined as a function relates to the seawater temperatures and load ratios. A model contains one single variable, i.e. the cleaning interval, is used in assessing the Maintenance cost. By knowing the headcount and hourly rate of labour, the maintenance cost could be evaluated. In this study, the maintenance cost is found to be a decreasing function against the cleaning interval. Risk Constraint relates to the unavailability of the air-conditioning plant. In order to minimize the potential losses, both tangible and intangible, due to the interruption of the air-conditioning plant, the plant has to be maintained at a reasonable low unavailability. The repair history of the plant on condenser's tubes replacement in the past few years is used in determining the parameters used in the risk function. A Weibull distribution is recommended to be used to characterize the failure rate of the condenser tubes in the unavailability analysis. A simple algorithm using the above cost and unavailability functions as parameters for optimization analysis is proposed. Two optimum cleaning intervals are presented in this study in response to the different of operational characteristics and constraints in summer and winter seasons respectively.|
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