A Method for Measuring the Efficiency Gap between Average and Best Practice Energy Use: The ENERGY STAR Industrial Energy Performance Indicator
A common feature distinguishing between parametric/statistical models and engineering economics models is that engineering models explicitly represent best practice technologies, whereas parametric/statistical models are typically based on average practice. Measures of energy intensity based on average practice are of little use in corporate management of energy use or for public policy goal setting. In the context of companyor plant-level indicators, it is more useful to have a measure of energy intensity that is capable of indicating where a company or plant lies within a distribution of performance. In other words, is the performance close to (or far from) the industry best practice? This article presents a parametric/statistical approach that can be used to measure best practice, thereby providing a measure of the difference, or "efficiency gap," at a plant, company, or overall industry level. The approach requires plant-level data and applies a stochastic frontier regression analysis used by the ENERGY STARTM industrial energy performance indicator (EPI) to energy intensity. Stochastic frontier regression analysis separates energy intensity into three components: systematic effects, inefficiency, and statistical (random) error. The article outlines the method and gives examples of EPI analysis conducted for two industries, breweries and motor vehicle assembly. In the EPI developed with the stochastic frontier regression for the auto industry, the industry median "efficiency gap" was around 27%.
industrial energy use
More InfoShow full item record
Associate Research Professor in the Social Science Research Institute
Gale Boyd is an Associate Research Professor in the Social Science Research Institute & Department of Economics. He was the Director of the Triangle Federal Statistical Research Data Center from 2006-2020. Prior to joining Duke University, Gale was an economist at Argonne National Laboratory. His career has been primarily in area of industrial energy/environmental economics. His recent work includes using the non-public Census micro-data and other non-pubic dat
Showing items related by title, author, creator, and subject.
ALQAHTANI, BANDAR (2018)This PhD dissertation presents three studies that individually aim to increase understanding of various aspects of solar and wind energy and the challenge of integrating them in the electricity power system. The first study ...
Hollis, John (2017-04-28)Residential electricity is a significant component of total electricity use in the United States, and the residential market is also a key demographic for energy efficiency (EE) and distributed generation growth. Uncertainty ...
Lattanzio, Steven (2011)In applications of ocean wave energy conversion, it is well known that feedback control can be used to achieve favorable performance. Current techniques include methods such as tuning a device to harvest energy at a narrow ...