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Efficiency in angolan hydro-electric power station: A two-stage virtual frontier dynamic DEA and simplex regression approach

Author

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  • Barros, C.P.
  • Wanke, Peter
  • Dumbo, Silvestre
  • Manso, Jose Pires

Abstract

This research focuses on the efficiency assessment of Angolan hydro-electric power stations using the VDRAM (Virtual Frontier Dynamic Range Adjusted Model) DEA. In VDRAM, the reference and the DMU evaluation sets are different, thus allowing higher score discrimination. In this research, the VDRAM model is used firstly in a two-stage approach. In the second stage, Simplex Regression is adopted to handle skewed and asymmetrical efficiency scores. Results indicate that energy efficiency of hydro-electric power stations in Angola is impacted by the river proximity, location of the station, and the cost structure. Results also indicate the inexistence of a learning curve. Policy implications are discussed in terms of possible measures such as privatization and human resource training so that a learning curve is boosted while labor costs are kept under control. Finally, the cost-structure advantages of water-to-wire power stations are also discussed observing sustainable development practices encompassing social, agricultural, and logistical aspects for the country.

Suggested Citation

  • Barros, C.P. & Wanke, Peter & Dumbo, Silvestre & Manso, Jose Pires, 2017. "Efficiency in angolan hydro-electric power station: A two-stage virtual frontier dynamic DEA and simplex regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 588-596.
    • Handle: RePEc:eee:rensus:v:78:y:2017:i:c:p:588-596
    DOI: 10.1016/j.rser.2017.04.100
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    More about this item

    Keywords

    C6; D2; Q4; Angola; Hydro-electric power stations; VDRAM; Two-stage; Simplex Regression;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D2 - Microeconomics - - Production and Organizations
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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