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Journal ArticleDOI

Towards Enhancement of the Economy of a Thermal Power Generating System through Prediction of Plant Efficiency

16 May 2007-Journal of Applied Statistics (Routledge)-Vol. 34, Iss: 3, pp 249-259
TL;DR: In this paper, the authors proposed a prediction interval of the heat rate values on the basis of only EHV, keeping in mind that coal quality is one of the important (but not the only) factors that have a pronounced effect on the combustion process and hence on HR.
Abstract: The plant ‘Heat Rate’ (HR) is a measure of overall efficiency of a thermal power generating system. It depends on a large number of factors, some of which are non-measurable, while data relating to others are seldom available and recorded. However, coal quality (expressed in terms of ‘effective heat value’ (EHV) as kcal/kg) transpires to be one of the important factors that influences HR values and data on EHV are available in any thermal power generating system. In the present work, we propose a prediction interval of the HR values on the basis of only EHV, keeping in mind that coal quality is one of the important (but not the only) factors that have a pronounced effect on the combustion process and hence on HR. The underlying theory borrows the idea of providing simultaneous confidence interval (SCI) to the coefficients of a p-th p(≥1) order autoregressive model (AR(p)). The theory has been substantiated with the help of real life data from a power utility (after suitable base and scale transfo...
References
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Book
01 Jan 1974
TL;DR: Applied Linear Statistical Models 5e as discussed by the authors is the leading authoritative text and reference on statistical modeling, which includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half.
Abstract: Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.

10,747 citations

Journal ArticleDOI
TL;DR: The literature of regression analysis with missing values of the independent variables is reviewed in this article, where six classes of procedures are distinguished: complete case analysis, available case methods, least squares on imputed data, maximum likelihood, Bayesian methods, and multiple imputation.
Abstract: The literature of regression analysis with missing values of the independent variables is reviewed. Six classes of procedures are distinguished: complete case analysis, available case methods, least squares on imputed data, maximum likelihood, Bayesian methods, and multiple imputation. Methods are compared and illustrated when missing data are confined to one independent variable, and extensions to more general patterns are indicated. Attention is paid to the performance of methods when the missing data are not missing completely at random. Least squares methods that fill in missing X's using only data on the X's are contrasted with likelihood-based methods that use data on the X's and Y. The latter approach is preferred and provides methods for elaboration of the basic normal linear regression model. It is suggested that more widely distributed software is needed that advances beyond complete-case analysis, available-case analysis, and naive imputation methods. Bayesian simulation methods and mu...

1,074 citations

24 Oct 2011
TL;DR: Regression With Missing X's: A Review Author(s): Roderick J. A.
Abstract: Regression With Missing X's: A Review Author(s): Roderick J. A. Little Source: Journal of the American Statistical Association, Vol. 87, No. 420 (Dec., 1992), pp. 1227- Published by: American Statistical Association Stable URL: http://www.jstor.org/stable/2290664 . Accessed: 09/08/2011 18:31 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. American Statistical Association is collaborating with JSTOR to digitize, preserve and extend access to Journal of the American Statistical Association. http://www.jstor.org

1,049 citations


"Towards Enhancement of the Economy ..." refers methods in this paper

  • ...The techniques recommended by Little (1992), which deal with missing covariates are also not very handy....

    [...]

Book
01 Jan 1979
TL;DR: In this article, the authors present a Reliability Modeling in Electric Power Systems (RMS) approach for the purpose of reliability modeling in electric power systems and evaluate its performance.
Abstract: (1979). Reliability Modeling in Electric Power Systems. Journal of the Operational Research Society: Vol. 30, No. 8, pp. 769-769.

306 citations


"Towards Enhancement of the Economy ..." refers background in this paper

  • ...The operating cost can be lowered by running the station at a high load factor and by increasing the efficiency of the plant (Endrenyi, 1978)....

    [...]

Book
01 Jan 1970

225 citations