IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v206y2017icp991-1008.html
   My bibliography  Save this article

Distributed demand-side energy management scheme in residential smart grids: An ordinal state-based potential game approach

Author

Listed:
  • Liang, Yile
  • Liu, Feng
  • Wang, Cheng
  • Mei, Shengwei

Abstract

This paper proposes a distributed demand-side energy management scheme in residential smart grids based on ordinal state-based potential game (SPG) with various kinds of household electrical appliances. Involving the total electricity costs, the supply capacity limits incurred by the distribution infrastructures and the required energy demands for individual appliances, the optimal energy management (OEM) of demand-side users, i.e., homes, turns out to be a complicated optimization problem associated with a coupled objective function subject to spatially and temporally coupled constraints. Such a problem is difficult to solve in a distributed fashion. In this paper, we formulate it as an ordinal SPG, devising a distributed algorithm to achieve the optimum of the original centralized OEM with no need of any central coordinator during the process of execution. Our scheme does not require any private information of individual users to be shared, while both the optimality and convergence are obtained. We also show the scheme is robust to unreliable communications. And the proposed scheme is illustrated and verified by simulations.

Suggested Citation

  • Liang, Yile & Liu, Feng & Wang, Cheng & Mei, Shengwei, 2017. "Distributed demand-side energy management scheme in residential smart grids: An ordinal state-based potential game approach," Applied Energy, Elsevier, vol. 206(C), pages 991-1008.
    • Handle: RePEc:eee:appene:v:206:y:2017:i:c:p:991-1008
    DOI: 10.1016/j.apenergy.2017.08.123
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917311467
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.08.123?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. Kobus, Charlotte B.A. & Klaassen, Elke A.M. & Mugge, Ruth & Schoormans, Jan P.L., 2015. "A real-life assessment on the effect of smart appliances for shifting households’ electricity demand," Applied Energy, Elsevier, vol. 147(C), pages 335-343.
    2. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    3. Dupont, B. & Dietrich, K. & De Jonghe, C. & Ramos, A. & Belmans, R., 2014. "Impact of residential demand response on power system operation: A Belgian case study," Applied Energy, Elsevier, vol. 122(C), pages 1-10.
    4. Greening, Lorna A., 2010. "Demand response resources: Who is responsible for implementation in a deregulated market?," Energy, Elsevier, vol. 35(4), pages 1518-1525.
    5. Widén, Joakim & Wäckelgård, Ewa, 2010. "A high-resolution stochastic model of domestic activity patterns and electricity demand," Applied Energy, Elsevier, vol. 87(6), pages 1880-1892, June.
    6. Maojiao Ye & Guoqiang Hu, 2015. "Game Design and Analysis for Price based Demand Response: An Aggregate Game Approach," Papers 1508.02636, arXiv.org, revised Feb 2016.
    7. Shen, Bo & Ghatikar, Girish & Lei, Zeng & Li, Jinkai & Wikler, Greg & Martin, Phil, 2014. "The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges," Applied Energy, Elsevier, vol. 130(C), pages 814-823.
    8. Sheikhi, Aras & Bahrami, Shahab & Ranjbar, Ali Mohammad, 2015. "An autonomous demand response program for electricity and natural gas networks in smart energy hubs," Energy, Elsevier, vol. 89(C), pages 490-499.
    9. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    10. Anees, Amir & Chen, Yi-Ping Phoebe, 2016. "True real time pricing and combined power scheduling of electric appliances in residential energy management system," Applied Energy, Elsevier, vol. 165(C), pages 592-600.
    11. Wang, Jianxiao & Zhong, Haiwang & Lai, Xiaowen & Xia, Qing & Shu, Chang & Kang, Chongqing, 2017. "Distributed real-time demand response based on Lagrangian multiplier optimal selection approach," Applied Energy, Elsevier, vol. 190(C), pages 949-959.
    12. Monderer, Dov & Shapley, Lloyd S., 1996. "Potential Games," Games and Economic Behavior, Elsevier, vol. 14(1), pages 124-143, May.
    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. Noussan, Michel, 2018. "Performance based approach for electricity generation in smart grids," Applied Energy, Elsevier, vol. 220(C), pages 231-241.
    2. Yongxiu He & Wei Xiong & Binyou Yang & Hai-yan Yang & Jiu-fang Zhou & Ming-li Cui & Yan Li, 2022. "Combined game model and investment decision making of power grid-distributed energy system," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8667-8690, June.
    3. Liu, Guodong & Jiang, Tao & Ollis, Thomas B. & Zhang, Xiaohu & Tomsovic, Kevin, 2019. "Distributed energy management for community microgrids considering network operational constraints and building thermal dynamics," Applied Energy, Elsevier, vol. 239(C), pages 83-95.
    4. Lai, Kexing & Illindala, Mahesh S., 2018. "A distributed energy management strategy for resilient shipboard power system," Applied Energy, Elsevier, vol. 228(C), pages 821-832.
    5. Kaijun Lin & Junyong Wu & Di Liu & Dezhi Li & Taorong Gong, 2018. "Energy Management of Combined Cooling, Heating and Power Micro Energy Grid Based on Leader-Follower Game Theory," Energies, MDPI, vol. 11(3), pages 1-21, March.
    6. Luciana Marques & Wadaed Uturbey & Miguel Heleno, 2021. "An Integer Non-Cooperative Game Approach for the Transactive Control of Thermal Appliances in Energy Communities," Energies, MDPI, vol. 14(21), pages 1-22, October.
    7. Nian Liu & Bin Guo & Zifa Liu & Yongli Wang, 2018. "Distributed Energy Sharing for PVT-HP Prosumers in Community Energy Internet: A Consensus Approach," Energies, MDPI, vol. 11(7), pages 1-18, July.

    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. Zhang, Chonghui & Wang, Zhen & Su, Weihua & Dalia, Streimikiene, 2024. "Differentiated power rationing or seasonal power price? Optimal power allocation solution for Chinese industrial enterprises based on the CSW-DEA model," Applied Energy, Elsevier, vol. 353(PB).
    2. Zhao, Xueyuan & Gao, Weijun & Qian, Fanyue & Ge, Jian, 2021. "Electricity cost comparison of dynamic pricing model based on load forecasting in home energy management system," Energy, Elsevier, vol. 229(C).
    3. Arteconi, Alessia & Patteeuw, Dieter & Bruninx, Kenneth & Delarue, Erik & D’haeseleer, William & Helsen, Lieve, 2016. "Active demand response with electric heating systems: Impact of market penetration," Applied Energy, Elsevier, vol. 177(C), pages 636-648.
    4. Behl, Madhur & Smarra, Francesco & Mangharam, Rahul, 2016. "DR-Advisor: A data-driven demand response recommender system," Applied Energy, Elsevier, vol. 170(C), pages 30-46.
    5. 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.
    6. 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.
    7. Rodríguez-García, Javier & Álvarez-Bel, Carlos & Carbonell-Carretero, José-Francisco & Alcázar-Ortega, Manuel & Peñalvo-López, Elisa, 2016. "A novel tool for the evaluation and assessment of demand response activities in the industrial sector," Energy, Elsevier, vol. 113(C), pages 1136-1146.
    8. Xu, Bing & Nayak, Amar & Gray, David & Ouenniche, Jamal, 2016. "Assessing energy business cases implemented in the North Sea Region and strategy recommendations," Applied Energy, Elsevier, vol. 172(C), pages 360-371.
    9. Curtis, John & Brazil, William & Harold, Jason, 2019. "Understanding preference heterogeneity in electricity services: the case of domestic appliance curtailment contracts," Papers WP638, Economic and Social Research Institute (ESRI).
    10. Yamaguchi, Yohei & Chen, Chien-fei & Shimoda, Yoshiyuki & Yagita, Yoshie & Iwafune, Yumiko & Ishii, Hideo & Hayashi, Yasuhiro, 2020. "An integrated approach of estimating demand response flexibility of domestic laundry appliances based on household heterogeneity and activities," Energy Policy, Elsevier, vol. 142(C).
    11. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    12. Tuballa, Maria Lorena & Abundo, Michael Lochinvar, 2016. "A review of the development of Smart Grid technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 710-725.
    13. Bing Wang & Qiran Cai & Zhenming Sun, 2020. "Determinants of Willingness to Participate in Urban Incentive-Based Energy Demand-Side Response: An Empirical Micro-Data Analysis," Sustainability, MDPI, vol. 12(19), pages 1-18, September.
    14. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    15. Lu, Qing & Lü, Shuaikang & Leng, Yajun & Zhang, Zhixin, 2020. "Optimal household energy management based on smart residential energy hub considering uncertain behaviors," Energy, Elsevier, vol. 195(C).
    16. Reihani, Ehsan & Motalleb, Mahdi & Thornton, Matsu & Ghorbani, Reza, 2016. "A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture," Applied Energy, Elsevier, vol. 183(C), pages 445-455.
    17. 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).
    18. Jin, Ming & Feng, Wei & Liu, Ping & Marnay, Chris & Spanos, Costas, 2017. "MOD-DR: Microgrid optimal dispatch with demand response," Applied Energy, Elsevier, vol. 187(C), pages 758-776.
    19. Yu, Xinran & Ergan, Semiha, 2022. "Estimating power demand shaving capacity of buildings on an urban scale using extracted demand response profiles through machine learning models," Applied Energy, Elsevier, vol. 310(C).
    20. Flavio Martins & Maria Fatima Almeida & Rodrigo Calili & Agatha Oliveira, 2020. "Design Thinking Applied to Smart Home Projects: A User-Centric and Sustainable Perspective," Sustainability, MDPI, vol. 12(23), pages 1-27, December.

    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:206:y:2017:i:c:p:991-1008. 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.