Estimating Plant Level Energy Efficiency with a Stochastic Frontier

By G. Boyd. 2008

138 citations recorded by the source corpus.

Subfields: Environmental Engineering, Management Science and Operations Research, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/32bd729b33f416f61b544cc5a68df234e9712fdb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Peng Zhou
2. Dequn Zhou
3. Massimo Filippini
4. Beng Wah Ang
5. Ning Zhang
6. Boqiang Lin
7. Xiaoling Ouyang
8. Hui Wang

In Management Science and Operations Research

1. Peng Zhou
2. Dequn Zhou
3. Massimo Filippini
4. Beng Wah Ang
5. Ning Zhang
6. Boqiang Lin
7. Xiaoling Ouyang
8. Yongrok Choi

In Renewable Energy, Sustainability and the Environment

1. Massimo Filippini
2. Peng Zhou
3. Dequn Zhou
4. Beng Wah Ang
5. Ning Zhang
6. L. Hunt
7. Inês Lima Azevedo
8. Qiang Cui

Citations in the corpus

• US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach (2012, background): “…Analysis (DEA).6 Examples of the use of parametric FA at the sectoral level are Buck and Young (2007) who measured the level of energy efficiency of a sample of Canadian commercial buildings and Boyd (2008) who estimated an energy use frontier function for a sample of wet corn milling plants.”
• Measuring economy-wide energy efficiency performance: A parametric frontier approach (2012, methodology): “More recently, Boyd [15] and Boyd et al. [16] use stochastic frontier regression to develop a statistical benchmarking tool called energy performance index (EPI).”