Publications [#302602] of Gale A. Boyd

Journal Articles

1. Boyd, GA, Estimating plant level energy efficiency with a stochastic frontier, Energy Journal, vol. 29 no. 2 (January, 2008), pp. 23-43, International Association for Energy Economics (IAEE), ISSN 0195-6574 [doi]
   (last updated on 2024/04/19)

   Abstract:
   A common distinguishing feature of engineering models is that they explicitly represent best practice technologies, while parametric/ statistical models represent average practice. It is more useful to energy management or goal setting to have a measure of energy performance capable of answering the question, "How close is observed performance from the industry best practice?" This paper presents a parametric/statistical approach to measure best practice. The results show how well a plant performs relative to the industry. A stochastic frontier regression analysis is used to model plant level energy use, separating energy into systematic effects, inefficiency, and random error. One advantage is that physical product mix can be included, avoiding the problem of aggregating output to define a single energy/ output ratio to measure energy intensity. The paper outlines the methods and gives an example of the analysis conducted for a non-public micro-dataset of wet corn milling plants. Copyright © 2008 by the IAEE. All rights reserved.