IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v185y2019icp274-285.html
   My bibliography  Save this article

A hybrid price-based demand response program for the residential micro-grid

Author

Listed:
  • Monfared, Houman Jamshidi
  • Ghasemi, Ahmad
  • Loni, Abdolah
  • Marzband, Mousa

Abstract

During the past two decades, providing solutions to enhance the efficiency of power systems, like optimal consumption management has been attracting a good deal of attention. Demand Response (DR) programs, have always been among the appropriate ways to persuade consumers to alter consumption patterns. In the main, the implementation of DR programs is carried out by price-based and incentive-based strategies. In this paper, first, a brief overview of the smart grid principles on retail electricity pricing is presented. Then, a hybrid price-based demand response (HPDR) is proposed, which is more adaptable to pricing principles compared to other existing strategies. This strategy is implemented in day-ahead scheduling of a residential microgrid. Moreover, to increase the accuracy of the proposed model, the uncertainty regarding decision variables and parameters including the generation units, load dispatch in the Micro-grid is considered. Finally, the results of numerical studies show the effectiveness of the proposed retail pricing strategy, and demonstrate a decrease in Peak-to-Valley (PtV) index and Coefficient of Variation Percentage (CVP) by almost 12% and 25% as well as an increase in social welfare indicator, power sale at peak times, respectively, by approximately 18%, 24%, and 25% in comparison with other methods.

Suggested Citation

  • Monfared, Houman Jamshidi & Ghasemi, Ahmad & Loni, Abdolah & Marzband, Mousa, 2019. "A hybrid price-based demand response program for the residential micro-grid," Energy, Elsevier, vol. 185(C), pages 274-285.
  • Handle: RePEc:eee:energy:v:185:y:2019:i:c:p:274-285
    DOI: 10.1016/j.energy.2019.07.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219313726
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.07.045?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. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
    2. Lijesen, Mark G., 2007. "The real-time price elasticity of electricity," Energy Economics, Elsevier, vol. 29(2), pages 249-258, March.
    3. Ghasemi, Ahmad & Mortazavi, Seyed Saeidollah & Mashhour, Elaheh, 2015. "Integration of nodal hourly pricing in day-ahead SDC (smart distribution company) optimization framework to effectively activate demand response," Energy, Elsevier, vol. 86(C), pages 649-660.
    4. Ghadikolaei, Hadi Moghimi & Tajik, Elham & Aghaei, Jamshid & Charwand, Mansour, 2012. "Integrated day-ahead and hour-ahead operation model of discos in retail electricity markets considering DGs and CO2 emission penalty cost," Applied Energy, Elsevier, vol. 95(C), pages 174-185.
    5. Aryani, Morteza & Ahmadian, Mohammad & Sheikh-El-Eslami, Mohammad-Kazem, 2018. "A two-stage robust investment model for a risk-averse price-maker power producer," Energy, Elsevier, vol. 143(C), pages 980-994.
    6. Vishnupriyan, J. & Manoharan, P.S., 2017. "Demand side management approach to rural electrification of different climate zones in Indian state of Tamil Nadu," Energy, Elsevier, vol. 138(C), pages 799-815.
    7. Dupont, B. & De Jonghe, C. & Olmos, L. & Belmans, R., 2014. "Demand response with locational dynamic pricing to support the integration of renewables," Energy Policy, Elsevier, vol. 67(C), pages 344-354.
    8. Faruqui, Ahmad & Malko, J.Robert, 1983. "The residential demand for electricity by time-of-use: A survey of twelve experiments with peak load pricing," Energy, Elsevier, vol. 8(10), pages 781-795.
    9. Winters, Tobey, 2001. "Retail Electricity Markets Require Marginal Cost Real-Time Pricing," The Electricity Journal, Elsevier, vol. 14(9), pages 74-81, November.
    10. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    Full references (including those not matched with items on IDEAS)

    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. Ghasemi, Ahmad & Jamshidi Monfared, Houman & Loni, Abdolah & Marzband, Mousa, 2021. "CVaR-based retail electricity pricing in day-ahead scheduling of microgrids," Energy, Elsevier, vol. 227(C).
    2. Ghasemi, Ahmad & Mortazavi, Seyed Saeidollah & Mashhour, Elaheh, 2015. "Integration of nodal hourly pricing in day-ahead SDC (smart distribution company) optimization framework to effectively activate demand response," Energy, Elsevier, vol. 86(C), pages 649-660.
    3. Ahmadi, Abdollah & Charwand, Mansour & Siano, Pierluigi & Nezhad, Ali Esmaeel & Sarno, Debora & Gitizadeh, Mohsen & Raeisi, Fatima, 2016. "A novel two-stage stochastic programming model for uncertainty characterization in short-term optimal strategy for a distribution company," Energy, Elsevier, vol. 117(P1), pages 1-9.
    4. Davatgaran, Vahid & Saniei, Mohsen & Mortazavi, Seyed Saeidollah, 2019. "Smart distribution system management considering electrical and thermal demand response of energy hubs," Energy, Elsevier, vol. 169(C), pages 38-49.
    5. 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.
    6. 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.
    7. 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.
    8. Calver, Philippa & Simcock, Neil, 2021. "Demand response and energy justice: A critical overview of ethical risks and opportunities within digital, decentralised, and decarbonised futures," Energy Policy, Elsevier, vol. 151(C).
    9. Woo, C.K. & Li, R. & Shiu, A. & Horowitz, I., 2013. "Residential winter kWh responsiveness under optional time-varying pricing in British Columbia," Applied Energy, Elsevier, vol. 108(C), pages 288-297.
    10. Massimo, Filippini, 2011. "Short- and long-run time-of-use price elasticities in Swiss residential electricity demand," Energy Policy, Elsevier, vol. 39(10), pages 5811-5817, October.
    11. 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.
    12. Ibrahim Alotaibi & Mohammed A. Abido & Muhammad Khalid & Andrey V. Savkin, 2020. "A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources," Energies, MDPI, vol. 13(23), pages 1-41, November.
    13. Ghasemi, Ahmad & Mortazavi, Seyed Saeidollah & Mashhour, Elaheh, 2016. "Hourly demand response and battery energy storage for imbalance reduction of smart distribution company embedded with electric vehicles and wind farms," Renewable Energy, Elsevier, vol. 85(C), pages 124-136.
    14. Bae, Mungyu & Kim, Hwantae & Kim, Eugene & Chung, Albert Yongjoon & Kim, Hwangnam & Roh, Jae Hyung, 2014. "Toward electricity retail competition: Survey and case study on technical infrastructure for advanced electricity market system," Applied Energy, Elsevier, vol. 133(C), pages 252-273.
    15. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
    16. Laura Mørch Andersen & Lars Gårn Hansen & Carsten Lynge Jensen & Frank A. Wolak, 2019. "Can Incentives to Increase Electricity Use Reduce the Cost of Integrating Renewable Resources," NBER Working Papers 25615, National Bureau of Economic Research, Inc.
    17. Layer, Patrick & Feurer, Sven & Jochem, Patrick, 2017. "Perceived price complexity of dynamic energy tariffs: An investigation of antecedents and consequences," Energy Policy, Elsevier, vol. 106(C), pages 244-254.
    18. Jerzy Andruszkiewicz & Józef Lorenc & Agnieszka Weychan, 2021. "Price-Based Demand Side Response Programs and Their Effectiveness on the Example of TOU Electricity Tariff for Residential Consumers," Energies, MDPI, vol. 14(2), pages 1-21, January.
    19. Silva, Hendrigo Batista da & Santiago, Leonardo P., 2018. "On the trade-off between real-time pricing and the social acceptability costs of demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1513-1521.
    20. Kazutoshi Tsuda & Michinori Uwasu & Keishiro Hara & Yukari Fuchigami, 2017. "Approaches to induce behavioral changes with respect to electricity consumption," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 7(1), pages 30-38, March.

    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:energy:v:185:y:2019:i:c:p:274-285. 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.journals.elsevier.com/energy .

    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.