IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v56y2013icp456-465.html
   My bibliography  Save this article

Optimization of India's power sector strategies using weight-restricted stochastic data envelopment analysis

Author

Listed:
  • Vazhayil, Joy P.
  • Balasubramanian, R.

Abstract

India's power sector has a significant impact on the country's development and climate change mitigation efforts. Optimization of energy planning is therefore, key to achieving the overall planning goals. The hierarchical multi-objective policy optimization is a policy-centric multi-level bottom-up iterative approach, designed from a developing country perspective, utilizing the optimality principle of dynamic programming. It is applied to the Indian power sector by grouping the strategies into three portfolios, namely, power generation mix, demand side efficiency group and supply side efficiency group. Each portfolio is optimized taking into account the objectives of cost minimization and comprehensive risk and barrier reduction. The portfolios are further combined and optimized at a higher level with respect to higher level objectives, namely, economic growth, energy equity, energy security and climate sustainability. This paper focuses on the second level optimization utilizing data envelopment analysis (DEA). Both the deterministic and stochastic variations have been analysed and the results compared in respect of unrestricted as well as restricted weight models. The analysis shows that weight-restricted stochastic DEA model is most appropriate for efficiency optimization of power sector strategies. The methodology can be effectively used for energy planning in developing countries.

Suggested Citation

  • Vazhayil, Joy P. & Balasubramanian, R., 2013. "Optimization of India's power sector strategies using weight-restricted stochastic data envelopment analysis," Energy Policy, Elsevier, vol. 56(C), pages 456-465.
    • Handle: RePEc:eee:enepol:v:56:y:2013:i:c:p:456-465
    DOI: 10.1016/j.enpol.2013.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421513000098
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2013.01.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Brent, Alan C. & Heuberger, Renat & Manzini, Dumisani, 2005. "Evaluating projects that are potentially eligible for Clean Development Mechanism (CDM) funding in the South African context: a case study to establish weighting values for sustainable development cri," Environment and Development Economics, Cambridge University Press, vol. 10(5), pages 631-649, October.
    2. Abhay Kumar Singh & Rajendra Sahu & Shalini Bharadwaj, 2010. "Portfolio evaluation using OWA-heuristic algorithm and data envelopment analysis," Journal of Risk Finance, Emerald Group Publishing, vol. 11(1), pages 75-88, January.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    5. Guerra, Ana-Isabel & Sancho, Ferran, 2010. "Rethinking economy-wide rebound measures: An unbiased proposal," Energy Policy, Elsevier, vol. 38(11), pages 6684-6694, November.
    6. Felipe, Jesus & Laviña, Editha & Fan, Emma Xiaoqin, 2008. "The Diverging Patterns of Profitability, Investment and Growth of China and India During 1980-2003," World Development, Elsevier, vol. 36(5), pages 741-774, May.
    7. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 407-437.
    8. Roy, Joyashree, 2000. "The rebound effect: some empirical evidence from India," Energy Policy, Elsevier, vol. 28(6-7), pages 433-438, June.
    9. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    10. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264, October.
    11. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    12. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    13. Weisser, Daniel, 2007. "A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies," Energy, Elsevier, vol. 32(9), pages 1543-1559.
    14. Ekholm, Tommi & Krey, Volker & Pachauri, Shonali & Riahi, Keywan, 2010. "Determinants of household energy consumption in India," Energy Policy, Elsevier, vol. 38(10), pages 5696-5707, October.
    15. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    16. Jacobson, Mark Z. & Delucchi, Mark A., 2011. "Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials," Energy Policy, Elsevier, vol. 39(3), pages 1154-1169, March.
    17. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    18. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    19. R G Dyson & E A Shale, 2010. "Data envelopment analysis, operational research and uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 25-34, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Hao & Tang, Bao-Jun & Liao, Hua & Wei, Yi-Ming, 2016. "A multi-period power generation planning model incorporating the non-carbon external costs: A case study of China," Applied Energy, Elsevier, vol. 183(C), pages 1333-1345.
    2. Mohd Chachuli, Fairuz Suzana & Mat, Sohif & Ludin, Norasikin Ahmad & Sopian, Kamaruzzaman, 2021. "Performance evaluation of renewable energy R&D activities in Malaysia," Renewable Energy, Elsevier, vol. 163(C), pages 544-560.
    3. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    4. Sun, Jiasen & Li, Guo & Wang, Zhaohua, 2018. "Optimizing China’s energy consumption structure under energy and carbon constraints," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 57-72.
    5. Ji, L. & Niu, D.X. & Huang, G.H., 2014. "An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand," Energy, Elsevier, vol. 67(C), pages 186-199.
    6. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    7. Mohd Chachuli, Fairuz Suzana & Ahmad Ludin, Norasikin & Md Jedi, Muhamad Alias & Hamid, Norul Hisham, 2021. "Transition of renewable energy policies in Malaysia: Benchmarking with data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    8. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    2. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    3. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    4. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    5. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    6. Mohammadi, Ali & Rafiee, Shahin & Mohtasebi, Seyed Saeid & Mousavi Avval, Seyed Hashem & Rafiee, Hamed, 2011. "Energy efficiency improvement and input cost saving in kiwifruit production using Data Envelopment Analysis approach," Renewable Energy, Elsevier, vol. 36(9), pages 2573-2579.
    7. Wai‐Peng Wong & Qiang Deng & Ming-Lang Tseng & Loo‐Hay Lee & Chee‐Wooi Hooy, 2014. "A Stochastic Setting To Bank Financial Performance For Refining Efficiency Estimates," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 225-245, October.
    8. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    9. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Impact of emission regulation policies on Chinese power firms’ reusable environmental investments and sustainable operations," Energy Policy, Elsevier, vol. 108(C), pages 163-177.
    10. Salas-Velasco, Manuel, 2018. "Production efficiency measurement and its determinants across OECD countries: The role of business sophistication and innovation," Economic Analysis and Policy, Elsevier, vol. 57(C), pages 60-73.
    11. Chemak, Fraj, 2011. "Technical Change Performance and Water Use Efficiency in the Irrigated Areas: Data Envelopment Analysis Approach," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114311, European Association of Agricultural Economists.
    12. Mehdi Toloo & Soroosh Nalchigar & Babak Sohrabi, 2018. "Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 1027-1051, December.
    13. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    14. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
    15. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    16. Constantino J. Garcia Martin & Amparo Medal-Bartual & Marta Peris-Ortiz, 2014. "Analysis of efficiency and profitability of franchise services," The Service Industries Journal, Taylor & Francis Journals, vol. 34(9-10), pages 796-810, July.
    17. Edirisinghe, N.C.P. & Zhang, X., 2007. "Generalized DEA model of fundamental analysis and its application to portfolio optimization," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3311-3335, November.
    18. Cesaroni, Giovanni, 2020. "Technically and cost-efficient centralized allocations in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    19. Zervopoulos, Panagiotis D. & Brisimi, Theodora S. & Emrouznejad, Ali & Cheng, Gang, 2016. "Performance measurement with multiple interrelated variables and threshold target levels: Evidence from retail firms in the US," European Journal of Operational Research, Elsevier, vol. 250(1), pages 262-272.
    20. Djula Borozan & Luka Borozan, 2018. "Analyzing total-factor energy efficiency in Croatian counties: evidence from a non-parametric approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 673-694, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:56:y:2013:i:c:p:456-465. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.