No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
An Evaluation Method of Ultra Supercritical Thermal Power Generating Units based on DEA cross-evaluation
Abstract
Since the 11th "five-year plan", China's super-critical technology has been greatly developed, and more and more ultra supercritical units with high parameter have been put into operation formally. The reasonable evaluation on their economic operation efficiency can promote the rational distribution of each unit resource and the improvement of operation efficiency. In accordance with the characteristics of the thermal power unit, as well as the advantages of DEA (data envelopment analysis) method in a multi-input and multi-output model, the evaluation model of ultra supercritical thermal power generating units is established on DEA cross-evaluation model, the evaluation index system of thermal power unit operation is structured simultaneously, and further discussion are expounded with actual examples, which provides a theoretical basis for reference in grasping the actual level of thermal power units and charting the direction of improvement.
DEA (data envelopment analysis) has been widely used for the efficiency analysis of industrial production process. However, the conventional DEA model is difficult to analyze the pros and cons of the multi DMUs (decision-making units). The DEACM (DEA cross-model) can distinguish the pros and cons of the effective DMUs, but it is unable to take the effect of the uncertainty data into account. This paper proposes an efficiency analysis method based on FDEACM (fuzzy DEA cross-model) with Fuzzy Data. The proposed method has better objectivity and resolving power for the decision-making. First we obtain the minimum, the median and the maximum values of the multi-criteria ethylene energy consumption data by the data fuzzification. On the basis of the multi-criteria fuzzy data, the benchmark of the effective production situations and the improvement directions of the ineffective of the ethylene plants under different production data configurations are obtained by the FDEACM. The experimental result shows that the proposed method can improve the ethylene production conditions and guide the efficiency of energy utilization during ethylene production process.
Data envelopment analysis (DEA) has been widely used for efficiency evaluation of industrial plants. A conventional DEA model may easily lead to the situation where more than one-third of efficiency values are set to 1, so it is hard to analyze the pros and cons of the multi-decision-making units. The DEA cross-model can distinguish the pros and cons of the effective decision-making units, but it is unable to indicate the improvement direction of the ineffective decision-making units. This paper proposes an efficiency analysis method based on an improved DEA cross-model, which can get higher efficiency discrimination in identifying the efficiency state of the decision-making units compared with the conventional DEA model. The improved DEA cross-model avoids the impacts of unreasonable weight allocation of input and output indices. Meanwhile, self-evaluation of the improved DEA cross-model with the slack variables can find the improvement direction of the ineffective decision-making units. Also, the Malmquist productivity index (MPI) based on the improved DEA cross-model can comprehensively consider various input–output factors and obtain dynamic consistent analysis performance of industrial plants. To get relative effectiveness of ethylene plants under different technologies and different scales, the performance analysis of 19 ethylene plants in China were executed by proposed MPI. According to the results, various indices of MPI are evaluated over time by the improved DEA cross-model to obtain the root causes and direction of performance improvement of ethylene plants. As a result, the method proposed in this paper is effective and practical.
In order to comprehensive evaluate running state of generator unit, about operation optimizing, condition monitoring and fault diagnosis, an idea of using Principal Component Analysis (PCA) method to integrate the relevant generator unit information, is presented. Based on its basic principle and examples, it shows that PCA can provide the effective and impersonal evaluation for operation, management, state monitoring and diagnosis of generator unit. The result can be used to quantificationally evaluated turbine, and provide proofs for on line monitoring.
This review introduces the history and present status of data envelopment analysis (DEA) research, particularly the evaluation
process. And extensions of some DEA models are also described. It is pointed out that mathematics, economics and management
science are the main forces in the DEA development, optimization provides the fundamental method for the DEA research, and
the wide range of applications enforces the rapid development of DEA.
Keywordsdata envelopment analysis-non-dominated solution-production frontier
The second edition of An Introduction to Efficiency and Productivity Analysis is designed to be a general introduction for those who wish to study efficiency and productivity analysis. The book provides an accessible, well-written introduction to the four principal methods involved: econometric estimation of average response models; index numbers, data envelopment analysis (DEA); and stochastic frontier analysis (SFA). For each method, a detailed introduction to the basic concepts is presented, numerical examples are provided, and some of the more important extensions to the basic methods are discussed. Of special interest is the systematic use of detailed empirical applications using real-world data throughout the book. In recent years, there have been a number of excellent advance-level books published on performance measurement. This book, however, is the first systematic survey of performance measurement with the express purpose of introducing the field to a wide audience of students, researchers, and practitioners. Indeed, the 2nd Edition maintains its uniqueness: (1) It is a well-written introduction to the field. (2) It outlines, discusses and compares the four principal methods for efficiency and productivity analysis in a well-motivated presentation. (3) It provides detailed advice on computer programs that can be used to implement these performance measurement methods. The book contains computer instructions and output listings for the SHAZAM, LIMDEP, TFPIP, DEAP and FRONTIER computer programs. More extensive listings of data and computer instruction files are available on the book's website: (www.uq.edu.au/economics/cepa/crob2005).
A Technical and Economical Comprehensive Evaluation of 600MW Coal Fired Power Units Based on Grey Relational Analysis
- Yu Li-Yong
- Huo Li
- Li Han-Ling
The application of DEA cross-evaluation model to perform evaluation of universities". Science & Technology information
- Wu Jie-Jun
- Zhang Qiang
- Kou Xiao-Dong Et
Principal Component Analysis for Comprehensive Evaluation on Information of Power Plant Unit
- Fu Zhong-Guang
- Wang Li-Ping
- Jin Ge Zhi-Hua
- Zhang Tao
- Guang
Use of FAHP in Evaluation Index System of Applied Technical Achievements
- Yue Hong-Weil
- Liu Fa-Guil
- Zhang Quan