Distribution Network Oriented Demand Response

Chapter
Part of the Power Systems book series (POWSYS)

Abstract

This chapter reviews promising concepts for distribution network oriented demand response. Current demand response (DR) programs are designed for wholesale markets and utility level issues, neglecting local challenges that distribution network operators (DNOs) face in daily operation. Deployment of DR to specific parts of distribution networks can enable additional services and benefits. The literature hosts promising concepts and methods that gain popularity. However, there is a number of conflicting cases that require particular consideration. This chapter presents insight into use of DR in distribution network planning and operation with special focus on promising service opportunities, developing concepts and integration of local DR programs with utility-driven DR programs.

Keywords

Electric power distribution Demand response Distribution networks Incentive-based programs Price-based programs 

References

  1. 1.
    U.S. Energy Information Administration, Today in Energy—Demand response saves electricity during times of high demand (2016) [Online], Available: https://www.eia.gov/todayinenergy/detail.php?id=24872
  2. 2.
    Bonneville Power Administration, Demand Response Technology Roadmap (2015) [Online], Available: https://www.bpa.gov/Doing%20Business/TechnologyInnovation/Documents/DR-Technology-Roadmap.pdf
  3. 3.
    Ontario Energy Board, Time-of-Use Electricity Prices (2013) [Online], Available: https://www.oeb.ca/oeb/_Documents/Consumer%20Brochures/brochure_02_Time-of-use%20prices%20for%20electricity.pdf
  4. 4.
    ComEd, ComEd’s Hourly Pricing Program—Pricing Dashboard (2016) [Online] Available: https://hourlypricing.comed.com/live-prices/
  5. 5.
    P. Cappers, J. MacDonald, J. Page, J. Potter, E. Stewart, Future Opportunities and Challenges with Using Demand Response as a Resource in Distribution System Operation and Planning Activities (2016) [Online], Available: https://emp.lbl.gov/sites/all/files/lbnl-1003951.pdf
  6. 6.
    T. Mukai, K. Nishio, H. Komatsu, T. Uchida, K. Ishida, Evaluating a behavioral demand response trial in Japan: evidence from the summer of 2013. Energ. Effi. 9(4), 911–924 (2016)CrossRefGoogle Scholar
  7. 7.
    M.H. Albadi, E.F. El-Saaddany, A summary of demand response in electricity markets. Electr. Power Syst. Res. 78(11), 1989–1996 (2008)CrossRefGoogle Scholar
  8. 8.
    F. Pilo, S. Jupe, F. Silvestro, C. Abbey, A. Baitch, B. Bak-Jensen et al., Planning and optimization methods for active distribution systems, in CIGRÉ C6 Study Committee (Distribution Systems and Dispersed Generation), (2014)Google Scholar
  9. 9.
    M. Vallés, J. Reneses, P. Frías, C. Mateo, Economic benefits of integrating active demand in distribution network planning: a Spanish case study. Electr. Power Syst. Res. 136, 331–340 (2016)CrossRefGoogle Scholar
  10. 10.
    E.A.M. Ceseña, P. Mancarella, Distribution network reinforcement planning considering demand response support, in Power Systems Computation Conference (2014), pp. 1–7Google Scholar
  11. 11.
    J.A. Schachter, P. Mancarella, J. Moriarity, R. Shaw, Flexible investment under uncertainty in smart distribution networks with demand side response: assessment framework and practical implementation. Energy Policy 97, 439–449 (2016)CrossRefGoogle Scholar
  12. 12.
    G. Mokryani, Active distribution networks planning with integration of demand response. Sol. Energy 122, 1362–1370 (2015)CrossRefGoogle Scholar
  13. 13.
    E.A.M. Ceseña, P. Mancarella, Practical recursive algorithms and flexible open-source applications for planning of smart distribution networks with demand response. Sustain. Energy Grids Netw. 7, 104–116 (2016)CrossRefGoogle Scholar
  14. 14.
    B. Gwisdorf, S. Stepanescu, C. Rehtanz, Effects of demand side management on the planning and operation of distribution grids, in IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe) (2010), pp. 1–5Google Scholar
  15. 15.
    R. Hledik, J. Lazar, L. Schwartz, Distribution System Pricing with Distributed Energy Resources (2016) [Online], Available: https://emp.lbl.gov/sites/all/files/feur_4_20160518_fin-links2.pdf
  16. 16.
    S. Sekizaki, I. Nishizaki, T. Hayashida, Electricity retail market model with flexible price settings and elastic price-based demand responses by consumers in distribution network. Electr. Power Energy Syst. 81, 371–386 (2016)CrossRefGoogle Scholar
  17. 17.
    F. Sahriatzadeh, P. Nirbhavane, A.K. Srivastava, Locational marginal price for distribution system considering demand response, in North American Power Symposium (2012), pp. 1–5Google Scholar
  18. 18.
    P. Siano, D. Sarno, Assessing the benefits of residential demand response in a real time distribution energy market. Appl. Energy 161, 533–551 (2016)CrossRefGoogle Scholar
  19. 19.
    R. Palma-Behnke, J.L. Cerda, L.S. Vargas, A. Jofré, A distribution company energy acquisition market model with integration of distributed generation and load curtailment options. IEEE Trans. Power Syst. 20(4), 1718–1727 (2005)Google Scholar
  20. 20.
    A. Colmenar-Santos, C. Reino-Rio, D. Borge-Diez, E. Collado-Fernández, Distributed generation: a review of factors that can contribute most to achieve a scenario of DG units embedded in the new distribution networks. Renew. Sustain. Energy Rev. 59, 1130–1148 (2016)CrossRefGoogle Scholar
  21. 21.
    M. Stadler, G. Carodo, S. Mashayekh, T. Forget, N. DeForest, A. Agarwal et al., Value streams in microgrids: a literature review. Appl. Energy 162, 980–989 (2016)CrossRefGoogle Scholar
  22. 22.
    M.A. Zehir, A. Batman, M. Bagriyanik, Review and comparison of demand response options for more effective use of renewable energy at consumer level. Renew. Sustain. Energy Rev. 56, 631–642 (2016)CrossRefGoogle Scholar
  23. 23.
    P.S. Moura, A.T. Almeida, The role of demand-side management in the grid integration of wind power. Appl. Energy 87(8), 2581–2588 (2010)CrossRefGoogle Scholar
  24. 24.
    M.A. Mahmud, M.J. Hossain, H.R. Pota, Voltage variation of distribution networks with distributed generation: worst case scenario. IEEE Syst. J. 8(4), 1096–1103 (2014)CrossRefGoogle Scholar
  25. 25.
    T. Ackermann, E.M. Carlini, B. Ernst, F. Groome, A. Orths, J. O’Sullivan et al., Integrating variable renewables in Europe. IEEE Power Energy Mag. 13(6), 67–77 (2015)Google Scholar
  26. 26.
    I. Stadler, Power grid balancing of energy systems with high renewable energy penetration by demand response. Utilities Policy 16(2), 90–98 (2008)CrossRefGoogle Scholar
  27. 27.
    International Energy Agency, High Penetration of PV in Local Distribution Grids Subtask 2: Case-Study Collection (2014) [Online], Available: https://nachhaltigwirtschaften.at/resources/iea_pdf/reports/iea_pvps_ task14_report_2014_high_penetration_of_pv_in_local_distribution_grids.pdf
  28. 28.
    M.A. Zehir, A. Batman, M.A. Sonmez, A. Font, D. Tsiamitros, D. Stimoniaris et. al., Impacts of microgrids with renewables on secondary distribution networks. Applied Energy, in press, corrected proof, (2017)Google Scholar
  29. 29.
    A.D. Peacock, M. Newborough, Controlling micro-CHP systems to modulate electrical load profiles. Energy 32(7), 1093–1103 (2007)CrossRefGoogle Scholar
  30. 30.
    N. Mahmud, A. Zahedi, Review of control strategies for voltage regulation of the smart distribution network with high penetration of renewable distributed generation. Renew. Sustain. Energy Rev. 64, 582–595 (2016)CrossRefGoogle Scholar
  31. 31.
    A. Soroudi, A. Rabieem, A. Keane, Distribution networks’ energy losses versus hosting capacity of wind power in the presence of demand flexibility. Renew. Energy 102(B), 316–325 (2017)Google Scholar
  32. 32.
    R. Perez, K.R. Rábago, M. Trahan, L. Rawling, B. Norris, T. Hoff et al., Achieving very high PV penetration—the need for an effective electricity remuneration framework and a central role for grid operators. Energy Policy 96, 27–35 (2016)CrossRefGoogle Scholar
  33. 33.
    J. Medina, N. Muller, I. Roytelman, Demand response and distribution grid operations: opportunities and challenges. IEEE Trans. Smart Grid 1(2), 193–198 (2010)CrossRefGoogle Scholar
  34. 34.
    W. Shi, N. Li, X. Xie, C. Chu, R. Gadh, Optimal residential demand response in distribution networks. IEEE J. Sel. Areas Commun. 32(7), 1441–1450 (2014)CrossRefGoogle Scholar
  35. 35.
    R.S. Balog, W. Weaver, P.T. Krein, Low-voltage dc distribution system for commercial power systems with sensitive electronic loads. IEEE Trans. Power Deliv. 22(3), 1620–1627 (2007)CrossRefGoogle Scholar
  36. 36.
    BBOXX, Impact (2017) [Online], Available: http://www.bboxx.co.uk/customers/
  37. 37.
    SOLshare, In the News (2017) [Online], Available: https://www.me-solshare.com/in-the-news/
  38. 38.
    H. Mohsenian-Rad, A. Davoudi, Demand Response in DC Distribution Networks, in IEEE SmartGridComm Symposium (2013), pp. 564–569Google Scholar
  39. 39.
    H. Mohsenian-Rad, A. Davoudi, Towards building an optimal demand response framework for DC distribution networks. IEEE Trans. Smart Grid 5(5), 2626–2634 (2014)CrossRefGoogle Scholar
  40. 40.
    T.R. de Oliveira, P.F. Donoso-Garcia, Perspectives for DC distribution adoption in Brazil, in IEEE First International Conference on DC Microgrids (2015), pp. 359–364Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Electrical Engineering, Faculty of Electrical and Electronics EngineeringIstanbul Technical UniversityIstanbulTurkey

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