Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization
碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 104 === The industry for the chiller of energy measurement performed ESCO (IPMVP) saving improvement works follow the measurement and verification (M &; V) approach Option B to perform, before the system improvement through short-term measurement data 1 to 3...
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ndltd-TW-104TIT057030072019-05-15T22:34:51Z http://ndltd.ncl.edu.tw/handle/s4933p Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization 應用粒子族群演算法進行冰水主機性能分析之資料修正與限制 Cjun-Ting Chen 陳俊廷 碩士 國立臺北科技大學 能源與冷凍空調工程系碩士班 104 The industry for the chiller of energy measurement performed ESCO (IPMVP) saving improvement works follow the measurement and verification (M &; V) approach Option B to perform, before the system improvement through short-term measurement data 1 to 3 months, the use of ASHRAE No. 14 of the guidelines out of the period of regression interval chiller performance equation A0, A1, A2, will improve the performance equation set into improved measurement data to estimate ice before and after the improvement of energy improvement host of differences, in order to that the effect of improving, the industry application of this method is quite common, but the improvement works generally improved in winter is often measured in summer and the return they belong extrapolation, through winter and regression equation set into the summer performance improved volume test data to calculate energy consumption, will have a great error. This study will be amended ASHRAE performance calculation method is expected to develop a simple and easy to use correction method, in order to facilitate the industry to use. Best Solution coefficient obtained through the particle population correction formula algorithms performed chiller performance analysis of Kaohsiung in a store, using the relevant variables ASHRAE No. 14 of the guidelines, the ice water temperature, cooling water inlet temperature and cooling The amount included in variable correction formula, and comparative analysis with ASHRAE. The analysis showed that, when measured after the long winter, the amount of data error correction COP value will be lower. After the statistical classification that corrected the error to be corrected COP and energy consumption to less than 10% at least to 115.17 pen data, such as error correction to less than 5% is required to 161.15 pen. Wen-Shing Lee 李文興 學位論文 ; thesis zh-TW |
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碩士 === 國立臺北科技大學 === 能源與冷凍空調工程系碩士班 === 104 === The industry for the chiller of energy measurement performed ESCO (IPMVP) saving improvement works follow the measurement and verification (M &; V) approach Option B to perform, before the system improvement through short-term measurement data 1 to 3 months, the use of ASHRAE No. 14 of the guidelines out of the period of regression interval chiller performance equation A0, A1, A2, will improve the performance equation set into improved measurement data to estimate ice before and after the improvement of energy improvement host of differences, in order to that the effect of improving, the industry application of this method is quite common, but the improvement works generally improved in winter is often measured in summer and the return they belong extrapolation, through winter and regression equation set into the summer performance improved volume test data to calculate energy consumption, will have a great error.
This study will be amended ASHRAE performance calculation method is expected to develop a simple and easy to use correction method, in order to facilitate the industry to use. Best Solution coefficient obtained through the particle population correction formula algorithms performed chiller performance analysis of Kaohsiung in a store, using the relevant variables ASHRAE No. 14 of the guidelines, the ice water temperature, cooling water inlet temperature and cooling The amount included in variable correction formula, and comparative analysis with ASHRAE.
The analysis showed that, when measured after the long winter, the amount of data error correction COP value will be lower. After the statistical classification that corrected the error to be corrected COP and energy consumption to less than 10% at least to 115.17 pen data, such as error correction to less than 5% is required to 161.15 pen.
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author2 |
Wen-Shing Lee |
author_facet |
Wen-Shing Lee Cjun-Ting Chen 陳俊廷 |
author |
Cjun-Ting Chen 陳俊廷 |
spellingShingle |
Cjun-Ting Chen 陳俊廷 Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization |
author_sort |
Cjun-Ting Chen |
title |
Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization |
title_short |
Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization |
title_full |
Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization |
title_fullStr |
Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization |
title_full_unstemmed |
Data Analysis And Correction of Chiller Performance Using Particle Swarm Optimization |
title_sort |
data analysis and correction of chiller performance using particle swarm optimization |
url |
http://ndltd.ncl.edu.tw/handle/s4933p |
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