IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i1p143-d194334.html
   My bibliography  Save this article

Demand-Side Management of Smart Distribution Grids Incorporating Renewable Energy Sources

Author

Listed:
  • Gerardo J. Osório

    (C-MAST, University of Beira Interior, Calcada Fonte Lameiro, 6201-001 Covilha, Portugal)

  • Miadreza Shafie-khah

    (INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Mohamed Lotfi

    (INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
    Faculty of Engineering, University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Bernardo J. M. Ferreira-Silva

    (Faculty of Engineering, University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • João P. S. Catalão

    (INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
    Faculty of Engineering, University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

Abstract

The integration of renewable energy resources (RES) (such as wind and photovoltaic (PV)) on large or small scales, in addition to small generation units, and individual producers, has led to a large variation in energy production, adding uncertainty to power systems (PS) due to the inherent stochasticity of natural resources. The implementation of demand-side management (DSM) in distribution grids (DGs), enabled by intelligent electrical devices and advanced communication infrastructures, ensures safer and more economical operation, giving more flexibility to the intelligent smart grid (SG), and consequently reducing pollutant emissions. Consumers play an active and key role in modern SG as small producers, using RES or through participation in demand response (DR) programs. In this work, the proposed DSM model follows a two-stage stochastic approach to deal with uncertainties associated with RES (wind and PV) together with demand response aggregators (DRA). Three types of DR strategies offered to consumers are compared. Nine test cases are modeled, simulated, and compared in order to analyze the effects of the different DR strategies. The purpose of this work is to minimize DG operating costs from the Distribution System Operator (DSO) point-of-view, through the analysis of different levels of DRA presence, DR strategies, and price variations.

Suggested Citation

  • Gerardo J. Osório & Miadreza Shafie-khah & Mohamed Lotfi & Bernardo J. M. Ferreira-Silva & João P. S. Catalão, 2019. "Demand-Side Management of Smart Distribution Grids Incorporating Renewable Energy Sources," Energies, MDPI, vol. 12(1), pages 1-23, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:1:p:143-:d:194334
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/1/143/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/1/143/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Amrollahi, Mohammad Hossein & Bathaee, Seyyed Mohammad Taghi, 2017. "Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response," Applied Energy, Elsevier, vol. 202(C), pages 66-77.
    2. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    3. Wei Fan & Nian Liu & Jianhua Zhang, 2016. "An Event-Triggered Online Energy Management Algorithm of Smart Home: Lyapunov Optimization Approach," Energies, MDPI, vol. 9(5), pages 1-24, May.
    4. Selin Kocaman, Ayse & Abad, Carlos & Troy, Tara J. & Tim Huh, Woonghee & Modi, Vijay, 2016. "A stochastic model for a macroscale hybrid renewable energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 688-703.
    5. Foster, Edward & Contestabile, Marcello & Blazquez, Jorge & Manzano, Baltasar & Workman, Mark & Shah, Nilay, 2017. "The unstudied barriers to widespread renewable energy deployment: Fossil fuel price responses," Energy Policy, Elsevier, vol. 103(C), pages 258-264.
    6. Ghaderi, A. & Parsa Moghaddam, M. & Sheikh-El-Eslami, M.K., 2014. "Energy efficiency resource modeling in generation expansion planning," Energy, Elsevier, vol. 68(C), pages 529-537.
    7. Aghajani, G.R. & Shayanfar, H.A. & Shayeghi, H., 2017. "Demand side management in a smart micro-grid in the presence of renewable generation and demand response," Energy, Elsevier, vol. 126(C), pages 622-637.
    8. Siano, Pierluigi & Sarno, Debora, 2016. "Assessing the benefits of residential demand response in a real time distribution energy market," Applied Energy, Elsevier, vol. 161(C), pages 533-551.
    9. Thakur, Jagruti & Chakraborty, Basab, 2016. "Demand side management in developing nations: A mitigating tool for energy imbalance and peak load management," Energy, Elsevier, vol. 114(C), pages 895-912.
    10. Hu, Zheng & Kim, Jin-ho & Wang, Jianhui & Byrne, John, 2015. "Review of dynamic pricing programs in the U.S. and Europe: Status quo and policy recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 743-751.
    11. Hepbasli, Arif, 2008. "A key review on exergetic analysis and assessment of renewable energy resources for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(3), pages 593-661, April.
    12. Nolan, Sheila & O’Malley, Mark, 2015. "Challenges and barriers to demand response deployment and evaluation," Applied Energy, Elsevier, vol. 152(C), pages 1-10.
    13. Hossain, M.S. & Madlool, N.A. & Rahim, N.A. & Selvaraj, J. & Pandey, A.K. & Khan, Abdul Faheem, 2016. "Role of smart grid in renewable energy: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1168-1184.
    14. 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.
    15. Muhammad Babar & Jakub Grela & Andrzej Ożadowicz & Phuong H. Nguyen & Zbigniew Hanzelka & I. G. Kamphuis, 2018. "Energy Flexometer: Transactive Energy-Based Internet of Things Technology," Energies, MDPI, vol. 11(3), pages 1-20, March.
    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. Sarker, Eity & Seyedmahmoudian, Mehdi & Jamei, Elmira & Horan, Ben & Stojcevski, Alex, 2020. "Optimal management of home loads with renewable energy integration and demand response strategy," Energy, Elsevier, vol. 210(C).
    2. 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).
    3. Elizaveta Gavrikova & Yegor Burda & Vladimir Gavrikov & Ruslan Sharafutdinov & Irina Volkova & Marina Rubleva & Daria Polosukhina, 2019. "Clean Energy Sources: Insights from Russia," Resources, MDPI, vol. 8(2), pages 1-25, May.

    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. Jun Dong & Rong Li & Hui Huang, 2018. "Performance Evaluation of Residential Demand Response Based on a Modified Fuzzy VIKOR and Scalable Computing Method," Energies, MDPI, vol. 11(5), pages 1-27, April.
    2. Hu, Maomao & Xiao, Fu & Wang, Lingshi, 2017. "Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model," Applied Energy, Elsevier, vol. 207(C), pages 324-335.
    3. Sadeghianpourhamami, N. & Demeester, T. & Benoit, D.F. & Strobbe, M. & Develder, C., 2016. "Modeling and analysis of residential flexibility: Timing of white good usage," Applied Energy, Elsevier, vol. 179(C), pages 790-805.
    4. Morteza Zare Oskouei & Ayşe Aybike Şeker & Süleyman Tunçel & Emin Demirbaş & Tuba Gözel & Mehmet Hakan Hocaoğlu & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "A Critical Review on the Impacts of Energy Storage Systems and Demand-Side Management Strategies in the Economic Operation of Renewable-Based Distribution Network," Sustainability, MDPI, vol. 14(4), pages 1-34, February.
    5. 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.
    6. Nezamoddini, Nasim & Wang, Yong, 2017. "Real-time electricity pricing for industrial customers: Survey and case studies in the United States," Applied Energy, Elsevier, vol. 195(C), pages 1023-1037.
    7. Cortés-Arcos, Tomás & Bernal-Agustín, José L. & Dufo-López, Rodolfo & Lujano-Rojas, Juan M. & Contreras, Javier, 2017. "Multi-objective demand response to real-time prices (RTP) using a task scheduling methodology," Energy, Elsevier, vol. 138(C), pages 19-31.
    8. Kowalska-Pyzalska, Anna, 2018. "What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3570-3581.
    9. Jun Dong & Huijuan Huo & Dongran Liu & Rong Li, 2017. "Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach," Sustainability, MDPI, vol. 9(8), pages 1-32, July.
    10. 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).
    11. Sharifi, R. & Fathi, S.H. & Vahidinasab, V., 2017. "A review on Demand-side tools in electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 565-572.
    12. Javed, Muhammad Shahzad & Jurasz, Jakub & McPherson, Madeleine & Dai, Yanjun & Ma, Tao, 2022. "Quantitative evaluation of renewable-energy-based remote microgrids: curtailment, load shifting, and reliability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    13. 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.
    14. Astriani, Yuli & Shafiullah, GM & Shahnia, Farhad, 2021. "Incentive determination of a demand response program for microgrids," Applied Energy, Elsevier, vol. 292(C).
    15. Ray, Manojit & Chakraborty, Basab, 2019. "Impact of evolving technology on collaborative energy access scaling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 13-27.
    16. Cai, Qiran & Xu, Qingyang & Qing, Jing & Shi, Gang & Liang, Qiao-Mei, 2022. "Promoting wind and photovoltaics renewable energy integration through demand response: Dynamic pricing mechanism design and economic analysis for smart residential communities," Energy, Elsevier, vol. 261(PB).
    17. Kocaman, Ayse Selin & Ozyoruk, Emin & Taneja, Shantanu & Modi, Vijay, 2020. "A stochastic framework to evaluate the impact of agricultural load flexibility on the sizing of renewable energy systems," Renewable Energy, Elsevier, vol. 152(C), pages 1067-1078.
    18. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    19. de la Hoz, Jordi & Martín, Helena & Alonso, Alex & Carolina Luna, Adriana & Matas, José & Vasquez, Juan C. & Guerrero, Josep M., 2019. "Regulatory-framework-embedded energy management system for microgrids: The case study of the Spanish self-consumption scheme," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    20. Schreiber, Michael & Wainstein, Martin E. & Hochloff, Patrick & Dargaville, Roger, 2015. "Flexible electricity tariffs: Power and energy price signals designed for a smarter grid," Energy, Elsevier, vol. 93(P2), pages 2568-2581.

    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:gam:jeners:v:12:y:2019:i:1:p:143-:d:194334. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.