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An integrated DEA-COLS-SFA algorithm for optimization and policy making of electricity distribution units

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  • Azadeh, A.
  • Ghaderi, S.F.
  • Omrani, H.
  • Eivazy, H.

Abstract

This paper presents an integrated data envelopment analysis (DEA)-corrected ordinary least squares (COLS)-stochastic frontier analysis (SFA)-principal component analysis (PCA)-numerical taxonomy (NT) algorithm for performance assessment, optimization and policy making of electricity distribution units. Previous studies have generally used input-output DEA models for benchmarking and evaluation of electricity distribution units. However, this study proposes an integrated flexible approach to measure the rank and choose the best version of the DEA method for optimization and policy making purposes. It covers both static and dynamic aspects of information environment due to involvement of SFA which is finally compared with the best DEA model through the Spearman correlation technique. The integrated approach would yield in improved ranking and optimization of electricity distribution systems. To illustrate the usability and reliability of the proposed algorithm, 38 electricity distribution units in Iran have been considered, ranked and optimized by the proposed algorithm of this study.

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  • Azadeh, A. & Ghaderi, S.F. & Omrani, H. & Eivazy, H., 2009. "An integrated DEA-COLS-SFA algorithm for optimization and policy making of electricity distribution units," Energy Policy, Elsevier, vol. 37(7), pages 2605-2618, July.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:7:p:2605-2618
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    18. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "Operational synergy in the US electric utility industry under an influence of deregulation policy: A linkage to financial performance and corporate value," Energy Policy, Elsevier, vol. 39(2), pages 699-713, February.
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    20. Omrani, Hashem & Valipour, Mahsa & Jafari Mamakani, Saeid, 2019. "Construct a composite indicator based on integrating Common Weight Data Envelopment Analysis and principal component analysis models: An application for finding development degree of provinces in Iran," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    21. Omrani, Hashem & Fahimi, Pegah & Mahmoodi, Abdollah, 2020. "A data envelopment analysis game theory approach for constructing composite indicator: An application to find out development degree of cities in West Azarbaijan province of Iran," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    22. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
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