IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v202y2017icp125-137.html
   My bibliography  Save this article

Impact of behavior-driven demand response on supply adequacy in smart distribution systems

Author

Listed:
  • Zeng, Bo
  • Wu, Geng
  • Wang, Jianhui
  • Zhang, Jianhua
  • Zeng, Ming

Abstract

As an integral feature of a future smart grid, demand response (DR) provides utility companies an emerging alternative to boost the reliability performance (e.g., supply adequacy) of power systems. Unlike for physical devices, the availability of DR is not only dependent on the operations of electric appliances on the demand side but can be affected by customers’ behaviors. Thus, how or to what extent DR actions can affect power system reliability becomes an important issue for utilities. In this paper, a new approach for assessing the contribution of incentive-based DR to the supply adequacy of smart distribution systems (SDS) is presented. Compared with existing methods, our method explicitly captures the varying availability of customer DR capabilities. We introduce a behavior-reinforcement procedure to model the correlation of users’ participation willingness with their historical DR profitability. Then, a strategic DR dispatch strategy can be developed to optimize users’ DR availability bids in the market. In addition, the interdependency between a communication system and DR operation has also been considered. A hybrid algorithm based on sequential Monte-Carlo simulation and an optimal load dispatch method is employed to evaluate the system reliability in this context. The proposed approach is illustrated using both a small-scale test case and a real regional distribution grid in China. The results demonstrate the effectiveness of the presented method.

Suggested Citation

  • Zeng, Bo & Wu, Geng & Wang, Jianhui & Zhang, Jianhua & Zeng, Ming, 2017. "Impact of behavior-driven demand response on supply adequacy in smart distribution systems," Applied Energy, Elsevier, vol. 202(C), pages 125-137.
    • Handle: RePEc:eee:appene:v:202:y:2017:i:c:p:125-137
    DOI: 10.1016/j.apenergy.2017.05.098
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917306025
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.05.098?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. Rious, Vincent & Perez, Yannick & Roques, Fabien, 2015. "Which electricity market design to encourage the development of demand response?," Economic Analysis and Policy, Elsevier, vol. 48(C), pages 128-138.
    2. Paliwal, Priyanka & Patidar, N.P. & Nema, R.K., 2014. "Planning of grid integrated distributed generators: A review of technology, objectives and techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 557-570.
    3. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    4. Feijóo, Andrés & Villanueva, Daniel, 2016. "Assessing wind speed simulation methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 473-483.
    5. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
    6. Kwag, Hyung-Geun & Kim, Jin-O, 2014. "Reliability modeling of demand response considering uncertainty of customer behavior," Applied Energy, Elsevier, vol. 122(C), pages 24-33.
    7. Nistor, Silviu & Wu, Jianzhong & Sooriyabandara, Mahesh & Ekanayake, Janaka, 2015. "Capability of smart appliances to provide reserve services," Applied Energy, Elsevier, vol. 138(C), pages 590-597.
    8. Li, Gengfeng & Bie, Zhaohong & Xie, Haipeng & Lin, Yanling, 2016. "Customer satisfaction based reliability evaluation of active distribution networks," Applied Energy, Elsevier, vol. 162(C), pages 1571-1578.
    9. Nolan, Sheila & O’Malley, Mark, 2015. "Challenges and barriers to demand response deployment and evaluation," Applied Energy, Elsevier, vol. 152(C), pages 1-10.
    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. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
    2. Song, Chunhe & Jing, Wei & Zeng, Peng & Yu, Haibin & Rosenberg, Catherine, 2018. "Energy consumption analysis of residential swimming pools for peak load shaving," Applied Energy, Elsevier, vol. 220(C), pages 176-191.
    3. Escalera, Alberto & Hayes, Barry & Prodanović, Milan, 2018. "A survey of reliability assessment techniques for modern distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 344-357.
    4. Adefarati, T. & Bansal, R.C., 2017. "Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources," Applied Energy, Elsevier, vol. 206(C), pages 911-933.
    5. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    6. Arabzadeh, Vahid & Miettinen, Panu & Kotilainen, Titta & Herranen, Pasi & Karakoc, Alp & Kummu, Matti & Rautkari, Lauri, 2023. "Urban vertical farming with a large wind power share and optimised electricity costs," Applied Energy, Elsevier, vol. 331(C).
    7. Viana, Matheus Sabino & Manassero, Giovanni & Udaeta, Miguel E.M., 2018. "Analysis of demand response and photovoltaic distributed generation as resources for power utility planning," Applied Energy, Elsevier, vol. 217(C), pages 456-466.
    8. Zeng, Yuan & Zhang, Ruiwen & Wang, Dong & Mu, Yunfei & Jia, Hongjie, 2019. "A regional power grid operation and planning method considering renewable energy generation and load control," Applied Energy, Elsevier, vol. 237(C), pages 304-313.
    9. Lu, Qing & Yu, Hao & Zhao, Kangli & Leng, Yajun & Hou, Jianchao & Xie, Pinjie, 2019. "Residential demand response considering distributed PV consumption: A model based on China's PV policy," Energy, Elsevier, vol. 172(C), pages 443-456.
    10. 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.
    11. Majed A. Alotaibi & Ali M. Eltamaly, 2022. "Upgrading Conventional Power System for Accommodating Electric Vehicle through Demand Side Management and V2G Concepts," Energies, MDPI, vol. 15(18), pages 1-27, September.
    12. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
    13. Vallés, Mercedes & Bello, Antonio & Reneses, Javier & Frías, Pablo, 2018. "Probabilistic characterization of electricity consumer responsiveness to economic incentives," Applied Energy, Elsevier, vol. 216(C), pages 296-310.
    14. Zeng, Bo & Zhao, Dongbo & Singh, Chanan & Wang, Jianhui & Chen, Chen, 2019. "Holistic modeling framework of demand response considering multi-timescale uncertainties for capacity value estimation," Applied Energy, Elsevier, vol. 247(C), pages 692-702.
    15. 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.
    16. Ponce de Leon Barido, Diego & Suffian, Stephen & Kammen, Daniel M. & Callaway, Duncan, 2018. "Opportunities for behavioral energy efficiency and flexible demand in data-limited low-carbon resource constrained environments," Applied Energy, Elsevier, vol. 228(C), pages 512-523.

    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. Zeng, Bo & Zhao, Dongbo & Singh, Chanan & Wang, Jianhui & Chen, Chen, 2019. "Holistic modeling framework of demand response considering multi-timescale uncertainties for capacity value estimation," Applied Energy, Elsevier, vol. 247(C), pages 692-702.
    2. Zeng, Bo & Wei, Xuan & Zhao, Dongbo & Singh, Chanan & Zhang, Jianhua, 2018. "Hybrid probabilistic-possibilistic approach for capacity credit evaluation of demand response considering both exogenous and endogenous uncertainties," Applied Energy, Elsevier, vol. 229(C), pages 186-200.
    3. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    4. Cheng, Lin & Wan, Yuxiang & Tian, Liting & Zhang, Fang, 2019. "Evaluating energy supply service reliability for commercial air conditioning loads from the distribution network aspect," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Sergiu Hart & Andreu Mas-Colell, 2013. "Stochastic Uncoupled Dynamics And Nash Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 8, pages 165-189, World Scientific Publishing Co. Pte. Ltd..
    6. Fudenberg, Drew & Levine, David K., 1999. "Conditional Universal Consistency," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 104-130, October.
    7. Tom Johnston & Michael Savery & Alex Scott & Bassel Tarbush, 2023. "Game Connectivity and Adaptive Dynamics," Papers 2309.10609, arXiv.org, revised Oct 2024.
    8. Michael Kosfeld, 2002. "Stochastic strategy adjustment in coordination games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(2), pages 321-339.
    9. Sacha Bourgeois-Gironde, 2017. "How regret moves individual and collective choices towards rationality," Chapters, in: Morris Altman (ed.), Handbook of Behavioural Economics and Smart Decision-Making, chapter 11, pages 188-204, Edward Elgar Publishing.
    10. 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.
    11. Majdalani, Naim & Aelenei, Daniel & Lopes, Rui Amaral & Silva, Carlos Augusto Santo, 2020. "The potential of energy flexibility of space heating and cooling in Portugal," Utilities Policy, Elsevier, vol. 66(C).
    12. Benaïm, Michel & Hofbauer, Josef & Hopkins, Ed, 2009. "Learning in games with unstable equilibria," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1694-1709, July.
    13. Karl H. Schlag, 2007. "Distribution-Free Learning," Economics Working Papers ECO2007/01, European University Institute.
    14. Reza Nadimi & Masahito Takahashi & Koji Tokimatsu & Mika Goto, 2024. "The Reliability and Profitability of Virtual Power Plant with Short-Term Power Market Trading and Non-Spinning Reserve Diesel Generator," Energies, MDPI, vol. 17(9), pages 1-19, April.
    15. Chiara Scarampi & Richard Fairchild & Luca Fumarco & Alberto Palermo & Neal Hinvest, 2021. "Social Metacognition: A Correlational Device for Strategic Interactions," Working Papers 2111, Tulane University, Department of Economics.
    16. Ehud Lehrer & Eilon Solan, 2007. "Learning to play partially-specified equilibrium," Levine's Working Paper Archive 122247000000001436, David K. Levine.
    17. Lenzo, Justin & Sarver, Todd, 2006. "Correlated equilibrium in evolutionary models with subpopulations," Games and Economic Behavior, Elsevier, vol. 56(2), pages 271-284, August.
    18. Firouzmakan, Pouya & Hooshmand, Rahmat-Allah & Bornapour, Mosayeb & Khodabakhshian, Amin, 2019. "A comprehensive stochastic energy management system of micro-CHP units, renewable energy sources and storage systems in microgrids considering demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 355-368.
    19. Popović, Željko N. & KovaÄ ki, Neven V. & Popović, Dragan S., 2020. "Resilient distribution network planning under the severe windstorms using a risk-based approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    20. Kalai, Ehud & Lehrer, Ehud & Smorodinsky, Rann, 1999. "Calibrated Forecasting and Merging," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 151-169, October.

    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:appene:v:202:y:2017:i:c:p:125-137. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.