IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v88y2016icp11-26.html
   My bibliography  Save this article

Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers

Author

Listed:
  • Jang, Dongsik
  • Eom, Jiyong
  • Jae Park, Min
  • Jeung Rho, Jae

Abstract

To the extent that demand response represents an intentional electricity usage adjustment to price changes or incentive payments, consumers who exhibit more-variable load patterns on normal days may be capable of altering their loads more significantly in response to dynamic pricing plans. This study investigates the variation in the pre-enrollment load patterns of Korean commercial and industrial electricity customers and their impact on event-day loads during a critical peak pricing experiment in the winter of 2013. Contrary to conventional approaches to profiling electricity loads, this study proposes a new clustering technique based on variability indices that collectively represent the potential demand–response resource that these customers would supply. Our analysis reveals that variability in pre-enrollment load patterns does indeed have great predictive power for estimating their impact on demand–response loads. Customers in relatively low-variability clusters provided limited or no response, whereas customers in relatively high-variability clusters consistently presented large load impacts, accounting for most of the program-level peak reductions. This study suggests that dynamic pricing programs themselves may not offer adequate motivation for meaningful adjustments in load patterns, particularly for customers in low-variability clusters.

Suggested Citation

  • Jang, Dongsik & Eom, Jiyong & Jae Park, Min & Jeung Rho, Jae, 2016. "Variability of electricity load patterns and its effect on demand response: A critical peak pricing experiment on Korean commercial and industrial customers," Energy Policy, Elsevier, vol. 88(C), pages 11-26.
  • Handle: RePEc:eee:enepol:v:88:y:2016:i:c:p:11-26
    DOI: 10.1016/j.enpol.2015.09.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421515301154
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2015.09.029?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. Herriges, Joseph A, et al, 1993. "The Response of Industrial Customers to Electric Rates Based upon Dynamic Marginal Costs," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 446-454, August.
    2. Wai Choi & Anindya Sen & Adam White, 2011. "Response of industrial customers to hourly pricing in Ontario’s deregulated electricity market," Journal of Regulatory Economics, Springer, vol. 40(3), pages 303-323, December.
    3. Peter M. Schwarz & Thomas N. Taylor & Matthew Birmingham & Shana L. Dardan, 2002. "Industrial Response to Electricity Real-Time Prices: Short Run and Long Run," Economic Inquiry, Western Economic Association International, vol. 40(4), pages 597-610, October.
    4. Chicco, Gianfranco, 2012. "Overview and performance assessment of the clustering methods for electrical load pattern grouping," Energy, Elsevier, vol. 42(1), pages 68-80.
    5. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    6. 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.
    7. Ashok, S. & Banerjee, R., 2000. "Load-management applications for the industrial sector," Applied Energy, Elsevier, vol. 66(2), pages 105-111, June.
    8. Greening, Lorna A., 2010. "Demand response resources: Who is responsible for implementation in a deregulated market?," Energy, Elsevier, vol. 35(4), pages 1518-1525.
    9. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    10. Prywes, Menahem, 1986. "A nested CES approach to capital-energy substitution," Energy Economics, Elsevier, vol. 8(1), pages 22-28, January.
    11. Ahmad Faruqui & Sanem Sergici, 2010. "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, Springer, vol. 38(2), pages 193-225, October.
    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. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    2. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    3. Chen Wang & Kaile Zhou & Lanlan Li & Shanlin Yang, 2018. "Multi-agent simulation-based residential electricity pricing schemes design and user selection decision-making," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(3), pages 1309-1327, February.
    4. Miller, Clayton & Nagy, Zoltán & Schlueter, Arno, 2018. "A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1365-1377.
    5. Hyeri Choi & Min Jae Park, 2019. "Evaluating the Efficiency of Governmental Excellence for Social Progress: Focusing on Low- and Lower-Middle-Income Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 111-130, January.
    6. van Zoest, Vera & El Gohary, Fouad & Ngai, Edith C.H. & Bartusch, Cajsa, 2021. "Demand charges and user flexibility – Exploring differences in electricity consumer types and load patterns within the Swedish commercial sector," Applied Energy, Elsevier, vol. 302(C).
    7. Brewer, Dylan, 2023. "Household responses to winter heating costs: Implications for energy pricing policies and demand-side alternatives," Energy Policy, Elsevier, vol. 177(C).
    8. Thimmel, Markus & Fridgen, Gilbert & Keller, Robert & Roevekamp, Patrick, 2019. "Compensating balancing demand by spatial load migration – The case of geographically distributed data centers," Energy Policy, Elsevier, vol. 132(C), pages 1130-1142.
    9. Fridgen, Gilbert & Keller, Robert & Thimmel, Markus & Wederhake, Lars, 2017. "Shifting load through space–The economics of spatial demand side management using distributed data centers," Energy Policy, Elsevier, vol. 109(C), pages 400-413.
    10. Piscitelli, Marco Savino & Giudice, Rocco & Capozzoli, Alfonso, 2024. "A holistic time series-based energy benchmarking framework for applications in large stocks of buildings," Applied Energy, Elsevier, vol. 357(C).
    11. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    12. Voulis, Nina & van Etten, Max J.J. & Chappin, Émile J.L. & Warnier, Martijn & Brazier, Frances M.T., 2019. "Rethinking European energy taxation to incentivise consumer demand response participation," Energy Policy, Elsevier, vol. 124(C), pages 156-168.
    13. Neves, Diana & Pina, André & Silva, Carlos A., 2018. "Assessment of the potential use of demand response in DHW systems on isolated microgrids," Renewable Energy, Elsevier, vol. 115(C), pages 989-998.
    14. Bagheri, Mehdi & Delbari, Seyed Hamid & Pakzadmanesh, Mina & Kennedy, Christopher A., 2019. "City-integrated renewable energy design for low-carbon and climate-resilient communities," Applied Energy, Elsevier, vol. 239(C), pages 1212-1225.
    15. Bhagya Nathali Silva & Murad Khan & Kijun Han, 2020. "Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities," Sustainability, MDPI, vol. 12(14), pages 1-23, July.

    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. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    2. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    3. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
    4. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2018. "Large-scale demand response and its implications for spot prices, load and policies: Insights from the German-Austrian electricity market," Applied Energy, Elsevier, vol. 210(C), pages 1290-1298.
    5. Kim, Jin-Ho & Shcherbakova, Anastasia, 2011. "Common failures of demand response," Energy, Elsevier, vol. 36(2), pages 873-880.
    6. Zarnikau, Jay & Thal, Dan, 2013. "The response of large industrial energy consumers to four coincident peak (4CP) transmission charges in the Texas (ERCOT) market," Utilities Policy, Elsevier, vol. 26(C), pages 1-6.
    7. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    8. Yang, Changhui & Meng, Chen & Zhou, Kaile, 2018. "Residential electricity pricing in China: The context of price-based demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2870-2878.
    9. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
    10. Kim, Min-Jeong, 2017. "A field study using an adaptive in-house pricing model for commercial and industrial customers in Korea," Energy Policy, Elsevier, vol. 102(C), pages 189-198.
    11. Zhou, Yang & Ma, Rong & Su, Yun & Wu, Libo, 2019. "Too big to change: How heterogeneous firms respond to time-of-use electricity price," China Economic Review, Elsevier, vol. 58(C).
    12. He, Yongxiu & Wang, Bing & Wang, Jianhui & Xiong, Wei & Xia, Tian, 2012. "Residential demand response behavior analysis based on Monte Carlo simulation: The case of Yinchuan in China," Energy, Elsevier, vol. 47(1), pages 230-236.
    13. Leinauer, Christina & Schott, Paul & Fridgen, Gilbert & Keller, Robert & Ollig, Philipp & Weibelzahl, Martin, 2022. "Obstacles to demand response: Why industrial companies do not adapt their power consumption to volatile power generation," Energy Policy, Elsevier, vol. 165(C).
    14. Katz, Jonas, 2014. "Linking meters and markets: Roles and incentives to support a flexible demand side," Utilities Policy, Elsevier, vol. 31(C), pages 74-84.
    15. Eid, Cherrelle & Koliou, Elta & Valles, Mercedes & Reneses, Javier & Hakvoort, Rudi, 2016. "Time-based pricing and electricity demand response: Existing barriers and next steps," Utilities Policy, Elsevier, vol. 40(C), pages 15-25.
    16. Pascal Courty & Mario Pagliero, 2011. "Does responsive pricing smooth demand shocks?," Applied Economics, Taylor & Francis Journals, vol. 43(30), pages 4707-4721.
    17. Jieyi Kang & David Reiner, 2021. "Machine Learning on residential electricity consumption: Which households are more responsive to weather?," Working Papers EPRG2113, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    18. Derya Eryilmaz, Timothy M. Smith, and Frances R. Homans, 2017. "Price Responsiveness in Electricity Markets: Implications for Demand Response in the Midwest," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    19. Cl'emence Alasseur & Ivar Ekeland & Romuald Elie & Nicol'as Hern'andez Santib'a~nez & Dylan Possamai, 2017. "An adverse selection approach to power pricing," Papers 1706.01934, arXiv.org, revised Sep 2019.
    20. Katz, Jonas & Andersen, Frits Møller & Morthorst, Poul Erik, 2016. "Load-shift incentives for household demand response: Evaluation of hourly dynamic pricing and rebate schemes in a wind-based electricity system," Energy, Elsevier, vol. 115(P3), pages 1602-1616.

    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:88:y:2016:i:c:p:11-26. 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.