Performance evaluation of Iranian electricity distribution units by using stochastic data envelopment analysis

Abstract This paper introduces an approach based on stochastic data envelopment analysis (SDEA) for performance assessment of electricity distribution units. A new approach is applied for assessment of Iranian distribution units from 2001 to 2011 in this paper. There are usually incomplete and stochastic data or lack of data with respect to electricity distribution companies. Due to lack of information about some parameters, theory of probability is imported to the model. Different Iranian distribution units are considered as decision making units (DMUs). Network length, transport capacity and the number of employees are chosen as inputs while number of customers and total electricity sales are chosen as stochastic outputs. Then, the best electricity distributions units are selected with respect to efficiency scores in stochastic environment. Also, SDEA model is performed for each input, separately to identify the most important input indicators by comparing the results of associated efficiencies with SDEA model. The empirical results show that network length is the most important and influential input factor in this particular case study. To the best of our knowledge this is the first paper that examines stochastic outputs for assessment of electricity distribution units by SDEA in Iran.

[1]  Zuren Feng,et al.  A proposed grey model for short-term electricity price forecasting in competitive power markets , 2012 .

[2]  Catherine Waddams Price,et al.  Efficiency and ownership in electricity distribution: A non-parametric model of the Turkish experience , 1996 .

[3]  Ali Azadeh,et al.  A consistent approach for performance measurement of electricity distribution companies , 2010 .

[4]  Toshiyuki Sueyoshi,et al.  Stochastic DEA for restructure strategy: an application to a Japanese petroleum company , 2000 .

[5]  Mohammad Hassan Behzadi,et al.  Multiplier Models in Stochastic DEA , 2014 .

[6]  Ilias Petrounias,et al.  A hybrid intelligent approach for the prediction of electricity consumption , 2012 .

[7]  Seyed Farid Ghaderi,et al.  Measuring efficiency and productivity change in power electric generation management companies by us , 2011 .

[8]  Paul L. Joskow,et al.  Incentive Regulation For Electric Utilities , 1986 .

[9]  M. Pollitt,et al.  Benchmarking and regulation: international electricity experience , 2000 .

[10]  Ali Azadeh,et al.  A deterministic approach for performance assessment and optimization of power distribution units in Iran , 2009 .

[11]  G. Debreu.  The Coefficient of Resource Utilization , 1951 .

[12]  Jati K. Sengupta,et al.  Data envelopment analysis for efficiency measurement in the stochastic case , 1987, Comput. Oper. Res..

[13]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[14]  L. J. Hill,et al.  A primer on incentive regulation for electric utilities , 1995 .

[15]  Ali Azadeh,et al.  An integrated DEA–COLS–SFA algorithm for optimization and policy making of electricity distribution units , 2009 .

[16]  Ali Azadeh,et al.  An intelligent algorithm for performance evaluation of job stress and HSE factors in petrochemical plants with noise and uncertainty , 2013 .

[17]  R. Bartels,et al.  The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand , 1998 .

[18]  Ned Greene,et al.  Performance Based Ratemaking for Electric Utilities: Review of Plans and Analysis of Economic and Re , 1995 .

[19]  Timothy Coelli,et al.  An analysis of factors that influence the technical efficiency of Malaysian thermal power plants , 2012 .

[20]  R. Pacudan,et al.  Impact of energy efficiency policy to productive efficiency of electricity distribution industry in the Philippines , 2002 .

[21]  M. Farrell.  The Measurement of Productive Efficiency , 1957 .

[22]  Andreas Kappeler,et al.  Efficiency analysis of German electricity distribution utilities – non-parametric and parametric tests , 2006 .

[23]  Adnan Sözen,et al.  Efficiency assessment of the hydro-power plants in Turkey by using Data Envelopment Analysis , 2012 .

[24]  Desheng Dash Wu,et al.  Stochastic DEA with ordinal data applied to a multi-attribute pricing problem , 2010, Eur. J. Oper. Res..

[25]  C. Mar Molinero,et al.  Behind DEA efficiency in financial institutions , 1970 .

[26]  M. Giannakis,et al.  A multi-agent based framework for supply chain risk management , 2011 .

[27]  Ahmad Makui,et al.  An interactive robust data envelopment analysis model for determining alternative targets in Iranian electricity distribution companies , 2011, Expert Syst. Appl..