Hybrid method for benchmarking the operating costs of Brazilian energy distributors
DOI:
https://doi.org/10.15675/gepros.3021Palavras-chave:
Electricity Distribution, Efficient Operating Costs, Benchmarking, Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA)Resumo
Purpose: This study aims to propose a model for benchmarking evaluation, applied to the Brazilian regulatory system in establishing efficient operating costs for electricity distribution concessionaires.
Theoretical framework: The application of data envelopment analysis to the regulation of electrical energy distribution is discussed, elucidating how different regulatory models accompany this modality.
Methodology: The proposed methodology is based on a benchmarking evaluation model that integrates the associated use of Data Envelopment Analysis and Stochastic Frontier Analysis, through a methodology that establishes the evaluation of efficiency in Three Stages.
Findings: The results of the performance assessment were expressed in terms of management efficiency, in which the effects of the operational environment and statistical noise are controlled, resulting in a rigorous measure of efficiency, by introducing manageable and unmanageable variables into the calculation directly from efficiency.
Originality: The methodology allows to adjust operational costs, by levelling the operating environment of each electricity distribution concessionaire before repeating the DEA analysis, making the concessionaires' performance more coherent with the characteristics of the Brazilian market.
Keywords: Electricity Distribution; Efficient Operating Costs; Benchmarking; Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA).
Referências
ABRADEE (2013). Relatório SIG: Continuidade do Fornecimento (DEC/FEC). Associação Brasileira dos Distribuidores de Energia Elétrica, Brasil.
Aigner, D., Lovell, C.A.K., Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6 (1), 21-37. https://doi.org/10.1016/0304-4076(77)90052-5. DOI: https://doi.org/10.1016/0304-4076(77)90052-5
ANEEL (2013). Consulta pública Nº 11/2013. Agência Nacional de Energia Elétrica, Brasil.
Angulo-Meza, L., Estellita Lins, M.P. (2002). Review of Methods for Increasing Discrimination in Data Envelopment Analysis. Annals of Operations Research, 116, 225-242. https://doi.org/10.1023/A:1021340616758. DOI: https://doi.org/10.1023/A:1021340616758
Avkiran, N.K., Rowlands, T. (2008). How to better identify the true managerial performance: State of the art using DEA. Omega, 36, 317-324. https://doi.org/10.1016/j.omega.2006.01.002. DOI: https://doi.org/10.1016/j.omega.2006.01.002
Banker, R.D., Cooper, W.W., Rhodes, E. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30 (9), 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078. DOI: https://doi.org/10.1287/mnsc.30.9.1078
Blázquez-Gómez, L., Grifell-Tatjé, E. (2011). Evaluating the regulator: Winners and losers in the regulation of Spanish electricity distribution. Energy Economics, 33, 807-815. https://doi.org/10.1016/j.eneco.2011.01.006. DOI: https://doi.org/10.1016/j.eneco.2011.01.006
Boonlert, T., Thampipattanakul, P., Hongesombut,K., Rerkpreedapong, D. (2023) .Tiered Reliability Assessment of Electric Distribution Utilities using DEA with Malmquist Index. In 2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC), Chiang Mai, Thailand, 1-4.
https://doi.org/10.1109/APPEEC57400.2023.10561925. DOI: https://doi.org/10.1109/APPEEC57400.2023.10561925
Charnes, A., Cooper, W.W., Rhodes, E. (1978). Measuring efficiency of decision making units. European Journal of Operational Research, 1, 429-444. https://doi.org/10.1016/0377-2217(78)90138-8. DOI: https://doi.org/10.1016/0377-2217(78)90138-8
Cook, W.D., Seiford, L.M. (2009). Data envelopment analysis (DEA): Thirty years on. European Journal of Operational Research, 192, 1-17. https://doi.org/10.1016/j.ejor.2008.01.032. DOI: https://doi.org/10.1016/j.ejor.2008.01.032
Cook, W.D., Tone, K., Zhu, J. (2014). Data envelopment analysis: Prior to choosing a model. Omega, 44, 1-4. https://doi.org/10.1016/j.omega.2013.09.004. DOI: https://doi.org/10.1016/j.omega.2013.09.004
Cooper, W., Seiford, L. M. & Tone, K. (2006). Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References. New York: Springer, DOI: https://doi.org/10.1007/0-387-29122-9
Cordero, J.M., Pedraja, F., Santín, D. (2009). Alternative approaches to include exogenous variables in DEA measures: A comparison using Monte Carlo. Computers & Operations Research, 36, 2699-2706. https://doi.org/10.1016/j.cor.2008.11.019. DOI: https://doi.org/10.1016/j.cor.2008.11.019
Doyle, J.R., Green, R.H. (1994). Efficiency and Cross-efficiency in DEA: Derivations, Meanings and Uses. Journal of the Operational Research Society, 45, 567-578. https://doi.org/10.2307/2584392. DOI: https://doi.org/10.1057/jors.1994.84
Dyson, R.G., Allen, R., Camanho, A.S., Podinovski, V.V., Sarrico, C.S., Shale, E.A. (2001). Pitfalls and protocols in DEA. European Journal of Operational Research, 132, 245-259. https://doi.org/10.1016/S0377-2217(00)00149-1. DOI: https://doi.org/10.1016/S0377-2217(00)00149-1
Edvardsen, D.F., Førsund, F.R. (2003). International benchmarking of electricity distribution utilities. Resource and Energy Economics, 25, 353-371. https://doi.org/10.1016/S0928-7655(03)00045-9. DOI: https://doi.org/10.1016/S0928-7655(03)00045-9
Estellita Lins, M.P., Sollero, M.K.V., Calôba, G.M., Silva, A.C.M. (2007). Integrating the regulatory and utility firm perspectives, when measuring the efficiency of electricity distribution. European Journal of Operational Research, 181, 1413-1424. https://doi.org/10.1016/j.ejor.2005.10.072. DOI: https://doi.org/10.1016/j.ejor.2005.10.072
Fried, H.O., Lovell, C.A.K., Schmidt, S.S., Yaisawarng, S. (2002). Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis. Journal of Productivity Analysis, 17, 157-174. https://doi.org/10.1023/A:1013548723393. DOI: https://doi.org/10.1023/A:1013548723393
Fried, H.O., Schmidt, S.S., Yaisawarng, S. (1999). Incorporating the Operating Environment into a Nonparametric Measure of Technical Efficiency. Journal of Productivity Analysis, 12, 249-267. https://doi.org/10.1023/A:1007800306752. DOI: https://doi.org/10.1023/A:1007800306752
Giannakis, D., Jamasb, T., Pollitt, M. (2005). Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks. Energy Policy, 33, 2256-2271. https://doi.org/10.1016/j.enpol.2004.04.021. DOI: https://doi.org/10.1016/j.enpol.2004.04.021
Growitsch, C., Jamasb, T., Muller, C., Wissner, M. (2010). Social cost-efficient service quality−Integrating customer valuation in incentive regulation: Evidence from the case of Norway. Energy Policy, 38, 2536-2544. https://doi.org/10.1016/j.enpol.2009.12.049. DOI: https://doi.org/10.1016/j.enpol.2009.12.049
Haney, A.B., Pollitt, M.G. (2009). Efficiency analysis of energy networks: An international survey of regulators. Energy Policy, 37 (12), 5814-5830. https://doi.org/10.1016/j.enpol.2009.08.047. DOI: https://doi.org/10.1016/j.enpol.2009.08.047
Hsu, F.M., Hsueh, C.C. (2009). Measuring relative efficiency of government-sponsored R&D projects: A three-stage approach. Evaluation and Program Planning, 32, 178-186. https://doi.org/10.1016/j.evalprogplan.2008.10.005. DOI: https://doi.org/10.1016/j.evalprogplan.2008.10.005
Jamasb, T., Nillesen, P., Pollitt, M. (2004). Strategic behaviour under regulatory benchmarking. Energy Economics, 26, 825-843. https://doi.org/10.1016/j.eneco.2004.04.029. DOI: https://doi.org/10.1016/j.eneco.2004.04.029
Jamasb, T., Pollitt, M. (2001). Benchmarking and regulation: international electricity experience. Utilities Policy, 9, 107-130. https://doi.org/10.1016/S0957-1787(01)00010-8. DOI: https://doi.org/10.1016/S0957-1787(01)00010-8
Kuosmanen, T.; Saastamoinen, A.; Sipilainen, T. (2013) What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods. Energy Policy, 61, 740-750. https://doi.org/10.1016/j.enpol.2013.05.091. DOI: https://doi.org/10.1016/j.enpol.2013.05.091
Liu, J. S., Lu, L. Y. Y., Lu, W., Lin, B. J.Y. (2013). Data envelopment analysis 1978-2010: A citation-based literature survey. Omega, 41, 3-15. https://doi.org/10.1016/j.omega.2010.12.006. DOI: https://doi.org/10.1016/j.omega.2010.12.006
Martins, R. A., Batalha, M. O., Tavares, Neto R. F., et al. (2024). Systematic Literature Review on Performance Measurement Systems for Power Distribution Companies. In ICQEM 2024 International Conference on Quality Engineering and Management, Girona, 47 – 68. Disponível em:
<https://publicacoes.riqual.org/wp-content/uploads/2024/06/icqem_24_47_68.pdf
Medeiros, G. O. S., Marangon-Lima, L. M., de Queiroz, A. R., et al. (2022). Efficiency analysis for performance evaluation of electric distribution companies. International Journal of Electrical Power & Energy Systems, 134.
https://doi.org/10.1016/j.ijepes.2021.107430. DOI: https://doi.org/10.1016/j.ijepes.2021.107430
Meeusen, W., van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 8, 435-444. https://doi.org/10.2307/2525757. DOI: https://doi.org/10.2307/2525757
Moreno, P., Naciff Andrade, G., Angulo Meza, L., Soares de Mello, J. C. (2015). Evaluation of Brazilian electricity distributors using a Network DEA model with shared inputs. In IEEE Latin America Transactions, 13(7), 2209-2216. https://doi.org/10.1109/TLA.2015.7273779. DOI: https://doi.org/10.1109/TLA.2015.7273779
Mullarkey, S., Caulfield, B., McCormack, S. & Basu, B. (2015). A framework for establishing the technical efficiency of Electricity Distribution Counties (EDCs) using Data Envelopment Analysis. Energy Conversion and Management, 94, 112-123. https://doi.org/10.1016/j.enconman.2015.01.049. DOI: https://doi.org/10.1016/j.enconman.2015.01.049
Muñiz, M.A. (2002). Separating managerial inefficiency and external conditions in data envelopment analysis. European Journal of Operational Research, 143, 625-643. https://doi.org/10.1016/S0377-2217(01)00344-7. DOI: https://doi.org/10.1016/S0377-2217(01)00344-7
Omrani, H., Beiragh, R.G. & Kaleibari, S.S. (2015). Performance assessment of Iranian electricity distribution companies by an integrated cooperative game data envelopment analysis principal component analysis approach. Electrical Power and Energy Systems, 64, 617-625. https://doi.org/10.1016/j.ijepes.2014.07.045. DOI: https://doi.org/10.1016/j.ijepes.2014.07.045
Omrani, H., Emrouznejad, A., Teplova, T., Amini, M. (2024). Efficiency evaluation of electricity distribution companies: Integrating data envelopment analysis and machine learning for a holistic analysis. Engineering Applications of Artificial Intelligence, 133(F).
https://doi.org/10.1016/j.engappai.2024.108636. DOI: https://doi.org/10.1016/j.engappai.2024.108636
Pérez-Reyes, R., Tovar, B. (2009). Measuring efficiency and productivity change in the Peruvian electricity distribution companies after reforms. Energy Policy, 37 (6), 2249-2261. https://doi.org/10.1016/j.enpol.2009.01.037. DOI: https://doi.org/10.1016/j.enpol.2009.01.037
Pessanha, J. F. M., Souza, R. C., Laurence, L.C. (2007). Um modelo de análise envoltória de dados para estabelecimento de metas de continuidade do fornecimento de energia elétrica. Pesquisa Operacional, 27 (1), 51-83. https://doi.org/10.1590/S0101-74382007000100004. DOI: https://doi.org/10.1590/S0101-74382007000100004
Pedrosa, P. Desafios da Regulação do Setor Elétrico, modicidade tarifária e atração de investimentos. Brasília: ANEEL, 2005.
Pereira de Souza, M.V.P., Diallo, M., Souza, R.C., Baidya, T.K.N. (2010a). The Cost Efficiency of the Brazilian Electricity Distribution Utilities: A Comparison of Bayesian SFA and DEA Models. Mathematical Problems in Engineering, 2010. https://doi.org/10.1155/2010/593059 DOI: https://doi.org/10.1155/2010/593059
Pereira de Souza, M.V., Souza, R.C., Pessanha, J.F.M. (2010b). Custos operacionais eficientes das distribuidoras de energia elétrica: um estudo comparativo dos modelos DEA e SFA. Gestão e Produção, 17 (4), 653-667. https://doi.org/10.1590/S0104-530X2010000400002. DOI: https://doi.org/10.1590/S0104-530X2010000400002
Ramos-Real, F.J., Tovar, B., Iootty, M., Almeida, E.F., Pinto Junior, H.Q. (2009). The evolution and main determinants of productivity in Brazilian electricity distribution 1998–2005: An empirical analysis. Energy Economics, 31, 298-305. https://doi.org/10.1016/j.eneco.2008.11.002. DOI: https://doi.org/10.1016/j.eneco.2008.11.002
Resende, M. (2002). Relative efficiency measurement and prospects for yardstick competition in Brazilian electricity distribution. Energy Policy 30, 63-647. https://doi.org/10.1016/S0301-4215(01)00132-X. DOI: https://doi.org/10.1016/S0301-4215(01)00132-X
Saleem, M. (2007). Benchmarking and Regulation for the Electricity Distribution Sector in Pakistan: Lessons for Developing Countries. South Asia Economic Journal, 8, 117-138. https://doi.org/10.1177/139156140600800107. DOI: https://doi.org/10.1177/139156140600800107
Santos, S.P., Amado, C.A.F., Rosado, J.R. (2011). Formative evaluation of electricity distribution utilities using data envelopment analysis. Journal of the Operational Research Society, 62, 1298-1319. https://doi.org/10.1057/jors.2010.66. DOI: https://doi.org/10.1057/jors.2010.66
Seiford, L.M., Zhu, J. (2002). Modelling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142, 16-20. https://doi.org/10.1016/S0377-2217(01)00293-4. DOI: https://doi.org/10.1016/S0377-2217(01)00293-4
Simab, M., Haghifam, M.R. (2012). Quality performance based regulation through designing reward and penalty scheme for electric distribution companies. Electrical Power and Energy Systems, 43, 539-545. https://doi.org/10.1016/j.ijepes.2012.06.070. DOI: https://doi.org/10.1016/j.ijepes.2012.06.070
Tschaffon, P.B., Meza, L. A. (2014). Assessing the Efficiency of the Electric Energy Distribution using Data Envelopment Analysis with undesirable outputs. IEEE Latin America Transactions, 12 (6), 1027-135. https://doi.org/10.1109/TLA.2014.6893996. DOI: https://doi.org/10.1109/TLA.2014.6893996
Wagner, J.M., Shimshak, D.G. (2007). Stepwise selection of variables in data envelopment analysis: Procedures and managerial perspectives. European Journal of Operational Research, 180, 57–67. https://doi.org/10.1016/j.ejor.2006.02.048. DOI: https://doi.org/10.1016/j.ejor.2006.02.048
Yadav, V.K., Chauhan, Y.K., Padhy, N.P., Gupta, H.O. (2013). A novel power sector restructuring model based on Data Envelopment Analysis. Electrical Power and Energy Systems, 44, 629-637. https://doi.org/10.1016/j.ijepes.2012.08.013. DOI: https://doi.org/10.1016/j.ijepes.2012.08.013
Yadav, V.K., Padhy, N.P., Gupta, H.O. (2010). A micro level study of an Indian electric utility for efficiency enhancement. Energy, 35, 4053-4063. https://doi.org/10.1016/j.energy.2010.06.011. DOI: https://doi.org/10.1016/j.energy.2010.06.011
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2024 Luís Filipe Azevedo de Oliveira, Mariana Rodrigues de Almeida
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
O(s) autor(es) do artigo autorizam a publicação do texto na revista e garantem que a contribuição é original e inédita, não estando em processo de avaliação em outra(s) revista(s). As opiniões, ideias e conceitos emitidos nos textos são de inteira responsabilidade do(s) autor(es), não sendo a revista responsável por tais conteúdos.
Os editores da revista reservam o direito de efetuar ajustes textuais e de adequação às normas da publicação, caso necessário.
Os autores mantêm os direitos autorais sobre o trabalho e concedem à revista o direito de primeira publicação, sendo o trabalho simultaneamente licenciado sob a Attribution 4.0 International (CC BY 4.0), o que permite o compartilhamento do trabalho com reconhecimento da autoria e publicação inicial nesta revista.
Os autores têm autorização para firmar contratos adicionais, separadamente, para distribuição não-exclusiva da versão do trabalho publicada nesta revista (ex.: publicar em repositório institucional ou como capítulo de livro), com reconhecimento de autoria e publicação inicial nesta revista.
