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Application of Entropy Method in Fuzzy Synthetic Evaluation for Micro-Turbine Performance

[+] Author Affiliations
Guohua Shi, Youyin Jing, Songling Wang, Yuefen Gao

North China Electric Power University, Baoding, China

Paper No. ES2008-54087, pp. 729-733; 5 pages
  • ASME 2008 2nd International Conference on Energy Sustainability collocated with the Heat Transfer, Fluids Engineering, and 3rd Energy Nanotechnology Conferences
  • ASME 2008 2nd International Conference on Energy Sustainability, Volume 1
  • Jacksonville, Florida, USA, August 10–14, 2008
  • Conference Sponsors: Advanced Energy Systems Division and Solar Energy Division
  • ISBN: 978-0-7918-4319-2 | eISBN: 0-7918-3832-3
  • Copyright © 2008 by ASME


Distributed generation (DG) is becoming the indispensable supplement to the centralized generation. Micro-turbine is paid more and more attention in scientific research and commercial application due to its unique advantages and gradually becomes the core of distributed generation. It is essential to make a synthetic and scientific evaluation on the performance of micro-turbine in order to promote the progress of the distributed generation technology using micro-turbine. This article gives the synthetic performance evaluation of micro-turbine. Some performance characters (rated capacity, generating efficiency, rotation speed, pressure ratio, fuel consumption, multi-fuel, intake temperature, exhaust temperature, NOx emission level, noises and life time) were chosen as evaluating indicators and some common micro-turbines were taken as evaluating objects in this paper. Considering the difficulty of fuzzy synthetic evaluation method in calculation of the multiple factors and the ignorance of the relationship among evaluating objects, a new weight evaluation process using entropy method was introduced. The entropy method is an objective way for weight determination. The improved method for weight determination of the evaluating indicators was applied in performance assessment of the micro-turbines. The evaluation result of the example showed that this method was favorable for fuzzy synthetic evaluation when there was more than one evaluating objects and the entropy method for determination of weight was a very effective method for evaluating indicators. The method predigested the fuzzy synthetic evaluation process greatly and the evaluation results are more reasonable.

Copyright © 2008 by ASME
Topics: Entropy , Turbines



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