Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis

Vaninsky, Alexander

doi:10.1016/j.eneco.2006.02.007

Cited by 115 publications

(45 citation statements)

References 18 publications

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“…Their results show that the efficiency levels during 1994-2000 remain at 99% or full efficiency, while they decline to 94-95% thereafter. [25] is another empirical research that analyzes American electric power generation plants using DEA method, and they found that those power plants have an average cost efficiency of 0.653 and technical efficiency of 0.983 in 1996, which is very close to the results of [24]. [26] analyzed the technical efficiency of Portuguese thermal power generation plants with a two-stage DEA-Tobit procedure.…”

Section: Literature Review On Efficiency Estimation In Electricity Inmentioning

confidence: 76%

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Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function

Tian

Zou

2015

Applied Energy

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Section: Literature Review On Efficiency Estimation In Electricity Inmentioning

confidence: 76%

“…Instead of parametric estimation technique, [24] used DEA method to estimate the efficiency of electric power plants in U.S. during 1991-2004. Their results show that the efficiency levels during 1994-2000 remain at 99% or full efficiency, while they decline to 94-95% thereafter.…”

Section: Literature Review On Efficiency Estimation In Electricity Inmentioning

confidence: 99%

Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function

Tian

Zou

2015

Applied Energy

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“…Entering the 21st century, DEA model was still the main method for studying the energy efficiency. For example, Vaninsky used DEA to analyze the efficiency changes and forecast the future values of the U.S. power generation efficiency [3]. Olatubi and Dismukes considered the influences of burning technology and operation efficiency from the cost perspective [4].…”

Section: Literature Reviewsmentioning

confidence: 99%

Total-Factor Energy Efficiency (TFEE) Evaluation on Thermal Power Industry with DEA, Malmquist and Multiple Regression Techniques

Liu

Yang

2017

Energies

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Abstract:Under the background of a new round of power market reform, realizing the goals of energy saving and emission reduction, reducing the coal consumption and ensuring the sustainable development are the key issues for thermal power industry. With the biggest economy and energy consumption scales in the world, China should promote the energy efficiency of thermal power industry to solve these problems. Therefore, from multiple perspectives, the factors influential to the energy efficiency of thermal power industry were identified. Based on the economic, social and environmental factors, a combination model with Data Envelopment Analysis (DEA) and Malmquist index was constructed to evaluate the total-factor energy efficiency (TFEE) in thermal power industry. With the empirical studies from national and provincial levels, the TFEE index can be factorized into the technical efficiency index (TECH), the technical progress index (TPCH), the pure efficiency index (PECH) and the scale efficiency index (SECH). The analysis showed that the TFEE was mainly determined by TECH and PECH. Meanwhile, by panel data regression model, unit coal consumption, talents and government supervision were selected as important indexes to have positive effects on TFEE in thermal power industry. In addition, the negative indexes, such as energy price and installed capacity, were also analyzed to control their undesired effects. Finally, considering the analysis results, measures for improving energy efficiency of thermal power industry were discussed widely, such as strengthening technology research and design (R&D), enforcing pollutant and emission reduction, distributing capital and labor rationally and improving the government supervision. Relative study results and suggestions can provide references for Chinese government and enterprises to enhance the energy efficiency level.

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“…Note that DEA applications in this area include Sueyoshi and Goto (2011, 2012b, c, e, 2013a, Sueyoshi et al (2010), Tavassoli et al (2015), Vaninsky (2006), von Geymueller (2009) and von Hirschhausen et al (2006.…”

Section: Secondary Energy (Electricity)mentioning

confidence: 99%

World trend in energy: an extension to DEA applied to energy and environment

Sueyoshi

Goto

2017

Economic Structures

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This study describes how to use Data Envelopment Analysis (DEA) for assessing the performance of energy firms. The methodology has been widely used for performance assessment on various organizations in public and private sectors because of its computational practicality (i.e., solving by linear programming) and less assumption (e.g., nonparametric) on production relationship between inputs and outputs. It is indeed true that it has a high level of practicality. However, the conventional uses of DEA were often misguiding many applications, in particular, in guiding energy industries. See the recent book and article prepared by and , both AbstractThis study proposes a use of data envelopment analysis (DEA) to assess the performance of energy industries. The DEA is a nonparametric approach that does not assume any functional form for performance assessment. The purpose of this study is to discuss how DEA can examine the current energy industries and their trends in the world. The energy is separated into primary and secondary categories. The primary energy is classified into fossil and non-fossil fuels. The fossil fuels include oil, natural gas and coal, while the non-fossil ones include nuclear and renewable energies (e.g., solar, wind, biomass, water and others). Energy consumption is essential for developing economic prosperity in all nations. However, a use of various energy resources usually produces many different types of pollutions (e.g., air, soil and water pollutions), leading to a huge damage on our society and human health. Thus, it is important for us to understand a general trend of world energy when we consider various environmental issues. This study discusses electricity as a representative of secondary energy. It is not easy to maintain a high level of social balance, so-called sustainability between economic development and environmental protection. As the initial step for sustainability development, this study summarizes a general trend of energy whose consumption has been increasing along with an economic development and a population increase in the world. Along with discussing the trend of world energy, this study describes why DEA is useful as one of the methodologies to assess a social balance between economic success and environmental protection by identifying a level of efficiency, later referred to as "unified (operational and environmental) efficiency. " Thus, this study conveys the research necessity of DEA environmental assessment on energy and sustainability from a perspective of supply and demand on energy resources in the world.

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Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis

Cited by 115 publications

References 18 publications

Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function

Impact analysis of coal-electricity pricing linkage scheme in China based on stochastic frontier cost function

Total-Factor Energy Efficiency (TFEE) Evaluation on Thermal Power Industry with DEA, Malmquist and Multiple Regression Techniques

World trend in energy: an extension to DEA applied to energy and environment

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