IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v52y2015icp937-947.html
   My bibliography  Save this article

Big Data issues and opportunities for electric utilities

Author

Listed:
  • Schuelke-Leech, Beth-Anne
  • Barry, Betsy
  • Muratori, Matteo
  • Yurkovich, B.J.

Abstract

Advances and innovations are crucial for a sustainable electricity system that includes smart grid technologies, renewable energy sources, and greater energy efficiency. These technologies are often layered on top of the existing infrastructure and legacy information systems. The management and utilization of the data generated from the different components of the electrical system are critical for the successful deployment and operation of this system. This paper reviews the issues and opportunities of the use of Big Data for electric utilities. Big Data provides the opportunity to better monitor, correct, and integrate smart grid technologies and renewable energy. At the same time, data management and utilization must be integrated into organizational operations if the potentials are to be realized. Electric utilities are conservative, heavily-regulated, and concerned with both system reliability and overall profitability. Thus, technological, economic, institutional, and policy constraints must all be addressed. After reviewing these issues and opportunities, we empirically analyze whether these are part of the discussions about electric utilities with federal policymakers. The results show that while conversations about electric utilities overall are plentiful, conversations about data in the context of electric utilities are relatively rare.

Suggested Citation

  • Schuelke-Leech, Beth-Anne & Barry, Betsy & Muratori, Matteo & Yurkovich, B.J., 2015. "Big Data issues and opportunities for electric utilities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 937-947.
    • Handle: RePEc:eee:rensus:v:52:y:2015:i:c:p:937-947
    DOI: 10.1016/j.rser.2015.07.128
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032115007753
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2015.07.128?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. Paul L. Joskow, 2006. "Markets for Power in the United States: An Interim Assessment," The Energy Journal, , vol. 27(1), pages 1-36, January.
    2. Nick Johnstone & Ivan Haščič & David Popp, 2010. "Renewable Energy Policies and Technological Innovation: Evidence Based on Patent Counts," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 45(1), pages 133-155, January.
    3. Paul L. Joskow, 2012. "Creating a Smarter U.S. Electricity Grid," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 29-48, Winter.
    4. Walawalkar, Rahul & Fernands, Stephen & Thakur, Netra & Chevva, Konda Reddy, 2010. "Evolution and current status of demand response (DR) in electricity markets: Insights from PJM and NYISO," Energy, Elsevier, vol. 35(4), pages 1553-1560.
    5. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    6. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    7. Perrons, Robert K. & Jensen, Jesse W., 2015. "Data as an asset: What the oil and gas sector can learn from other industries about “Big Data”," Energy Policy, Elsevier, vol. 81(C), pages 117-121.
    8. Li, Hui & Jenkins-Smith, Hank C. & Silva, Carol L. & Berrens, Robert P. & Herron, Kerry G., 2009. "Public support for reducing US reliance on fossil fuels: Investigating household willingness-to-pay for energy research and development," Ecological Economics, Elsevier, vol. 68(3), pages 731-742, January.
    9. Karellas, S. & Panopoulos, K.D. & Panousis, G. & Rigas, A. & Karl, J. & Kakaras, E., 2012. "An evaluation of Substitute natural gas production from different coal gasification processes based on modeling," Energy, Elsevier, vol. 45(1), pages 183-194.
    10. Jamasb, Tooraj & Pollitt, Michael, 2008. "Liberalisation and R&D in network industries: The case of the electricity industry," Research Policy, Elsevier, vol. 37(6-7), pages 995-1008, July.
    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. El Hage, Fabio S. & Rufín, Carlos, 2016. "Context analysis for a new regulatory model for electric utilities in Brazil," Energy Policy, Elsevier, vol. 97(C), pages 145-154.
    2. Tu, Chunming & He, Xi & Shuai, Zhikang & Jiang, Fei, 2017. "Big data issues in smart grid – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1099-1107.
    3. Isaac Machorro-Cano & Giner Alor-Hernández & Mario Andrés Paredes-Valverde & Lisbeth Rodríguez-Mazahua & José Luis Sánchez-Cervantes & José Oscar Olmedo-Aguirre, 2020. "HEMS-IoT: A Big Data and Machine Learning-Based Smart Home System for Energy Saving," Energies, MDPI, vol. 13(5), pages 1-24, March.
    4. Dong, Qingli & Sun, Yuhuan & Li, Peizhi, 2017. "A novel forecasting model based on a hybrid processing strategy and an optimized local linear fuzzy neural network to make wind power forecasting: A case study of wind farms in China," Renewable Energy, Elsevier, vol. 102(PA), pages 241-257.
    5. Schuelke-Leech, Beth-Anne, 2018. "A model for understanding the orders of magnitude of disruptive technologies," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 261-274.
    6. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    7. Purna Prakash Kasaraneni & Venkata Pavan Kumar Yellapragada & Ganesh Lakshmana Kumar Moganti & Aymen Flah, 2022. "Analytical Enumeration of Redundant Data Anomalies in Energy Consumption Readings of Smart Buildings with a Case Study of Darmstadt Smart City in Germany," Sustainability, MDPI, vol. 14(17), pages 1-24, August.
    8. Pablo David Necoechea-Porras & Asunción López & Juan Carlos Salazar-Elena, 2021. "Deregulation in the Energy Sector and Its Economic Effects on the Power Sector: A Literature Review," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    9. Matti Grosse & Hendrik Send & Thomas Schildhauer, 2019. "Lessons Learned from Establishing the Energy-Informatics Business Model: Case of a German Energy Company," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    10. Colak, Ilhami & Sagiroglu, Seref & Fulli, Gianluca & Yesilbudak, Mehmet & Covrig, Catalin-Felix, 2016. "A survey on the critical issues in smart grid technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 396-405.
    11. Adriana Mar & Pedro Pereira & João F. Martins, 2019. "A Survey on Power Grid Faults and Their Origins: A Contribution to Improving Power Grid Resilience," Energies, MDPI, vol. 12(24), pages 1-21, December.
    12. Li, Francis G.N. & Bataille, Chris & Pye, Steve & O'Sullivan, Aidan, 2019. "Prospects for energy economy modelling with big data: Hype, eliminating blind spots, or revolutionising the state of the art?," Applied Energy, Elsevier, vol. 239(C), pages 991-1002.
    13. Olga Pilipczuk, 2020. "Sustainable Smart Cities and Energy Management: The Labor Market Perspective," Energies, MDPI, vol. 13(22), pages 1-24, November.

    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. Nesta, Lionel & Vona, Francesco & Nicolli, Francesco, 2014. "Environmental policies, competition and innovation in renewable energy," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 396-411.
    2. Jamasb, Tooraj & Pollitt, Michael G., 2011. "Electricity sector liberalisation and innovation: An analysis of the UK's patenting activities," Research Policy, Elsevier, vol. 40(2), pages 309-324, March.
    3. Gosnell, Greer & McCoy, Daire, 2023. "Market failures and willingness to accept smart meters: Experimental evidence from the UK," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    4. Nyga-Łukaszewska Honorata, 2016. "Selected Issues in Innovation in the Energy Industry. The Case of Poland," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 50(1), pages 100-112, June.
    5. Kim, Jihwan & Kim, Yeonbae & Flacher, David, 2012. "R&D investment of electricity-generating firms following industry restructuring," Energy Policy, Elsevier, vol. 48(C), pages 103-117.
    6. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    7. Evens Salies, 2010. "A Test of the Schumpeterian Hypothesis in a Panel of European Electric Utilities," Chapters, in: Jean-Luc Gaffard & Evens Salies (ed.), Innovation, Economic Growth and the Firm, chapter 6, Edward Elgar Publishing.
    8. Nicolli, Francesco & Vona, Francesco, 2019. "Energy market liberalization and renewable energy policies in OECD countries," Energy Policy, Elsevier, vol. 128(C), pages 853-867.
    9. Wiesenthal, Tobias & Leduc, Guillaume & Haegeman, Karel & Schwarz, Hans-Günther, 2012. "Bottom-up estimation of industrial and public R&D investment by technology in support of policy-making: The case of selected low-carbon energy technologies," Research Policy, Elsevier, vol. 41(1), pages 116-131.
    10. Jamasb, Tooraj & Pollitt, Michael G., 2015. "Why and how to subsidise energy R+D: Lessons from the collapse and recovery of electricity innovation in the UK," Energy Policy, Elsevier, vol. 83(C), pages 197-205.
    11. Geoffroy G Dolphin & Michael G Pollitt, 2020. "Identifying innovative actors in the Electricity Supply Industry using machine learning: an application to UK patent data," Working Papers EPRG2004, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    12. Nesta, Lionel & Vona, Francesco & Nicolli, Francesco, 2014. "Environmental policies, competition and innovation in renewable energy," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 396-411.
    13. Grubb, Michael & Drummond, Paul & Poncia, Alexandra & McDowall, Will & Popp, David & Samadi, Sascha & Penasco, Cristina & Gillingham, Kenneth T. & Smulders, Sjak & Glachant, Matthieu & Hassall, Gavin , 2021. "Induced innovation in energy technologies and systems: A review of evidence and potential implications for CO2 mitigation," LSE Research Online Documents on Economics 113439, London School of Economics and Political Science, LSE Library.
    14. Evens Salies & Lionel Nesta, 2010. "Libéralisation et dépôts de brevets verts des utilités électriques en Europe," SciencePo Working papers Main hal-01069447, HAL.
    15. Pollitt, Michael G., 2012. "The role of policy in energy transitions: Lessons from the energy liberalisation era," Energy Policy, Elsevier, vol. 50(C), pages 128-137.
    16. Wang, Nan & Mogi, Gento, 2017. "Deregulation, market competition, and innovation of utilities: Evidence from Japanese electric sector," Energy Policy, Elsevier, vol. 111(C), pages 403-413.
    17. repec:hal:spmain:info:hdl:2441/eu4vqp9ompqllr09j0h0ji242 is not listed on IDEAS
    18. repec:hal:wpspec:info:hdl:2441/eu4vqp9ompqllr09j0h0ji242 is not listed on IDEAS
    19. Woo, C.K. & Sreedharan, P. & Hargreaves, J. & Kahrl, F. & Wang, J. & Horowitz, I., 2014. "A review of electricity product differentiation," Applied Energy, Elsevier, vol. 114(C), pages 262-272.
    20. Olmos, Luis & Ruester, Sophia & Liong, Siok-Jen & Glachant, Jean-Michel, 2011. "Energy efficiency actions related to the rollout of smart meters for small consumers, application to the Austrian system," Energy, Elsevier, vol. 36(7), pages 4396-4409.
    21. Galo, Joaquim J.M. & Macedo, Maria N.Q. & Almeida, Luiz A.L. & Lima, Antonio C.C., 2014. "Criteria for smart grid deployment in Brazil by applying the Delphi method," Energy, Elsevier, vol. 70(C), pages 605-611.

    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:rensus:v:52:y:2015:i:c:p:937-947. 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/wps/find/journaldescription.cws_home/600126/description#description .

    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.