Measurement of productive efficiency with frontier methods: A case study for wind farms

Iglesias, Guillermo R.; Castellanos, Pablo; Seijas, Amparo

doi:10.1016/j.eneco.2010.03.004

Cited by 61 publications

(42 citation statements)

References 40 publications

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“…The third approach is stochastic frontier analysis (SFA), which originated in Aigner et al (1977) and Meeusen and van den Broeck (1977 Hjalmarsson et al (1996) and Iglesias et al (2010).…”

Section: Introductionmentioning

confidence: 99%

A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions

Honma,

2014

Energy

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“…The third approach is stochastic frontier analysis (SFA), which originated in Aigner et al (1977) and Meeusen and van den Broeck (1977 Hjalmarsson et al (1996) and Iglesias et al (2010).…”

Section: Introductionmentioning

confidence: 99%

A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions

Honma,

2014

Energy

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“…The works performed by Iglesias et al [12] and Pestana and Barros [16] focus on the efficiency assessment of wind farms and argue the importance to model the non-discretionary factors such as the wind speed and its availability in each farm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Iglesias et al [12] used DEA and Stochastic Frontier Analysis (SFA) methodologies to measure the efficiency of a group of wind farms located in Spain. Models are output oriented concerning the generated energy, based on a relationship between capital, labor and fuel, similar to a conventional energy conversion system.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency and Productivity Assessment of Wind Farms

Vaz

Ferreira

2015

Operational Research

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This study develops a framework to provide insights regarding the performance of the farms of an energy player in the Portuguese wind sector. The focus of the wind farm performance assessment is on the operating stage which corresponds to the electrical energy generation process, during 2010 and 2011. In a first stage, Data Envelopment Analysis is used to measure the efficiency of wind farms in generating electrical energy from the resources available and nondiscretionary variables. This analysis enables the identification of the best practices of the efficient farms which can be emulated by inefficient ones. In a second stage, changes in wind farms productivity are investigated using Malmquist index. Bootstrap procedures are applied to obtain statistical inference on the efficiency estimates. We conclude that almost all farms decreased overall productivity levels, mainly due to the decline in the productivity levels of the frontier, which is in accordance with the decrease in wind availability observed in 2011.

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“…Wind farms can be considered homogenous as they result from similar set-up stages and use similar generation processes. The efficiency assessment is addressed to the operating stage although the farm performance is also linked to decisions taken prior the start up phase [3]. The output-oriented perspective is used, as the objective of the farms is to maximize the active electric energy delivered to the public grid.…”

Section: Performance Assessment Of Wind Farms: Case Studymentioning

confidence: 99%

“…Data Envelopment Analysis (DEA) has been accepted as an important method for benchmarking energy sectors in many countries, particularly in the electricity sector [2], although its application in the wind sector is still scarce [3]. The development of wind energy sector and the growing need of performance assessment models for promoters and regulators motivated this study.…”

Section: Introductionmentioning

confidence: 99%

Efficiency assessment of wind farms: A two-stage approach

Vaz

Ferreira

2015

AIP Conference Proceedings

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Abstract. This study proposes an integrated methodology to provide insights regarding the efficiency of wind farms of two major promoters in the Portuguese energy sector. The focus of the wind farms performance assessment is on the operating stage which corresponds to the electrical energy production process. In a first stage, Data Envelopment Analysis is used to measure the efficiency of wind farms in producing electrical energy from the resources available and exogenous variables. This method is complemented by bootstrapping to refine the efficiency estimates. In a second stage, the factors which may influence the performance of wind farms are investigated by using truncated regression with bootstrapping. The methodology proposed may be used by promoters in management of wind farms and may also be useful to regulator agents on the supervision of the energy market.

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Measurement of productive efficiency with frontier methods: A case study for wind farms

Cited by 61 publications

References 40 publications

A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions

A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions

Efficiency and Productivity Assessment of Wind Farms

Efficiency assessment of wind farms: A two-stage approach

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