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A Review and Analysis of Trends Related to Demand Response

Author

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  • Luis Alejandro Arias

    (Universidad Autonoma de Colombia: Programa de Ingenieria Electromecánica, Bogotà D.C. 111166, Colombia
    Universidad Distrital Francisco Jose de Caldas: Doctorado en Ingenieria, Proyecto Curricular Ingenieria Eléctrica, Bogota 110211, Colombia)

  • Edwin Rivas

    (Universidad Distrital Francisco Jose de Caldas: Doctorado en Ingenieria, Proyecto Curricular Ingenieria Eléctrica, Bogota 110211, Colombia)

  • Francisco Santamaria

    (Universidad Distrital Francisco Jose de Caldas: Doctorado en Ingenieria, Proyecto Curricular Ingenieria Eléctrica, Bogota 110211, Colombia)

  • Victor Hernandez

    (Universidad Distrital Francisco Jose de Caldas: Doctorado en Ingenieria, Proyecto Curricular Ingenieria Eléctrica, Bogota 110211, Colombia)

Abstract

This paper provides a review and analysis of trends related to demand response (DR). The authors have considered six different topics for the analysis of DR trends: Users, Network Services, Markets, Complementary Programs and Distributed Energy Resources (DER). A brief summary of the consulted articles is included and the behavior of the different DR trend-related topics is shown up to the year 2017 and their projections for 2020. As a result, the characterization of the main DR topics is obtained as well as its current and future trends. Based on the results of the study, it is concluded that the topic of complementary programs is a trendsetter for current trends and it is expected that there is a future change of focus towards the users and new services.

Suggested Citation

  • Luis Alejandro Arias & Edwin Rivas & Francisco Santamaria & Victor Hernandez, 2018. "A Review and Analysis of Trends Related to Demand Response," Energies, MDPI, vol. 11(7), pages 1-24, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1617-:d:153544
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    1. Klaassen, E.A.M. & Kobus, C.B.A. & Frunt, J. & Slootweg, J.G., 2016. "Responsiveness of residential electricity demand to dynamic tariffs: Experiences from a large field test in the Netherlands," Applied Energy, Elsevier, vol. 183(C), pages 1065-1074.
    2. Wang, Qi & Zhang, Chunyu & Ding, Yi & Xydis, George & Wang, Jianhui & Østergaard, Jacob, 2015. "Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response," Applied Energy, Elsevier, vol. 138(C), pages 695-706.
    3. Kakran, Sandeep & Chanana, Saurabh, 2018. "Smart operations of smart grids integrated with distributed generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 524-535.
    4. Safamehr, Hossein & Rahimi-Kian, Ashkan, 2015. "A cost-efficient and reliable energy management of a micro-grid using intelligent demand-response program," Energy, Elsevier, vol. 91(C), pages 283-293.
    5. Basu, Ashoke Kumar & Chowdhury, S.P. & Chowdhury, S. & Paul, S., 2011. "Microgrids: Energy management by strategic deployment of DERs—A comprehensive survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4348-4356.
    6. Koliou, Elta & Eid, Cherrelle & Chaves-Ávila, José Pablo & Hakvoort, Rudi A., 2014. "Demand response in liberalized electricity markets: Analysis of aggregated load participation in the German balancing mechanism," Energy, Elsevier, vol. 71(C), pages 245-254.
    7. Pouria Sheikhahmadi & Ramyar Mafakheri & Salah Bahramara & Maziar Yazdani Damavandi & João P. S. Catalão, 2018. "Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs," Energies, MDPI, vol. 11(3), pages 1-17, March.
    8. Naus, Joeri & Spaargaren, Gert & van Vliet, Bas J.M. & van der Horst, Hilje M., 2014. "Smart grids, information flows and emerging domestic energy practices," Energy Policy, Elsevier, vol. 68(C), pages 436-446.
    9. Ruiz-Romero, Salvador & Colmenar-Santos, Antonio & Mur-Pérez, Francisco & López-Rey, África, 2014. "Integration of distributed generation in the power distribution network: The need for smart grid control systems, communication and equipment for a smart city — Use cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 223-234.
    10. Ou, Ting-Chia & Hong, Chih-Ming, 2014. "Dynamic operation and control of microgrid hybrid power systems," Energy, Elsevier, vol. 66(C), pages 314-323.
    11. Kai Ma & Congshan Wang & Jie Yang & Qiuxia Yang & Yazhou Yuan, 2017. "Economic Dispatch with Demand Response in Smart Grid: Bargaining Model and Solutions," Energies, MDPI, vol. 10(8), pages 1-17, August.
    12. Poudineh, Rahmatallah & Jamasb, Tooraj, 2014. "Distributed generation, storage, demand response and energy efficiency as alternatives to grid capacity enhancement," Energy Policy, Elsevier, vol. 67(C), pages 222-231.
    13. Faria, Pedro & Soares, Tiago & Vale, Zita & Morais, Hugo, 2014. "Distributed generation and demand response dispatch for a virtual power player energy and reserve provision," Renewable Energy, Elsevier, vol. 66(C), pages 686-695.
    14. Kumar, Kandasamy Nandha & Tseng, King Jet, 2016. "Impact of demand response management on chargeability of electric vehicles," Energy, Elsevier, vol. 111(C), pages 190-196.
    15. Klaassen, E.A.M. & van Gerwen, R.J.F. & Frunt, J. & Slootweg, J.G., 2017. "A methodology to assess demand response benefits from a system perspective: A Dutch case study," Utilities Policy, Elsevier, vol. 44(C), pages 25-37.
    16. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    17. Schachter, Jonathan A. & Mancarella, Pierluigi & Moriarty, John & Shaw, Rita, 2016. "Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation," Energy Policy, Elsevier, vol. 97(C), pages 439-449.
    18. Qian Liu & Rui Wang & Yan Zhang & Guohua Wu & Jianmai Shi, 2018. "An Optimal and Distributed Demand Response Strategy for Energy Internet Management," Energies, MDPI, vol. 11(1), pages 1-16, January.
    19. Van-Hai Bui & Akhtar Hussain & Hak-Man Kim, 2017. "Optimal Operation of Microgrids Considering Auto-Configuration Function Using Multiagent System," Energies, MDPI, vol. 10(10), pages 1-16, September.
    20. 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.
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