IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v217y2018icp166-177.html
   My bibliography  Save this article

An algorithm for optimal management of aggregated HVAC power demand using smart thermostats

Author

Listed:
  • Adhikari, Rajendra
  • Pipattanasomporn, M.
  • Rahman, S.

Abstract

This paper presents an algorithm for optimal management of aggregated power demand of a group of heating, ventilating and air-conditioning (HVAC) units. The algorithm provides an advanced direct load control mechanism for HVACs that leverages the availability of smart thermostats, which are remotely programmable and controllable. The paper provides a theoretical basis and an optimal solution to the problem of cycling a large number of HVAC units while respecting customer-chosen temperature limits for the purpose of maximum load reduction. The problem is presented in a new light by transforming it into a job scheduling problem and is solved using a combination of a novel greedy algorithm and a binary search algorithm. By leveraging widespread availability of smart internet-based (also referred to as IoT-based) thermostats in today’s environment, the proposed approach can be readily applied to residential buildings without additional electrical/IT infrastructure changes.

Suggested Citation

  • Adhikari, Rajendra & Pipattanasomporn, M. & Rahman, S., 2018. "An algorithm for optimal management of aggregated HVAC power demand using smart thermostats," Applied Energy, Elsevier, vol. 217(C), pages 166-177.
    • Handle: RePEc:eee:appene:v:217:y:2018:i:c:p:166-177
    DOI: 10.1016/j.apenergy.2018.02.085
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918302101
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.02.085?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. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    2. Chassin, David P. & Rondeau, Daniel, 2016. "Aggregate modeling of fast-acting demand response and control under real-time pricing," Applied Energy, Elsevier, vol. 181(C), pages 288-298.
    3. Zhou, Yue & Wang, Chengshan & Wu, Jianzhong & Wang, Jidong & Cheng, Meng & Li, Gen, 2017. "Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market," Applied Energy, Elsevier, vol. 188(C), pages 456-465.
    4. Behboodi, Sahand & Chassin, David P. & Djilali, Ned & Crawford, Curran, 2018. "Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets," Applied Energy, Elsevier, vol. 210(C), pages 1310-1320.
    5. Gillingham, Kenneth & Newell, Richard G. & Palmer, Karen L., 2004. "Retrospective Examination of Demand-Side Energy Efficiency Policies," Discussion Papers 10477, Resources for the Future.
    6. Reihani, Ehsan & Sepasi, Saeed & Ghorbani, Reza, 2016. "Scheduling of price-sensitive residential storage devices and loads with thermal inertia in distribution grid," Applied Energy, Elsevier, vol. 183(C), pages 636-644.
    7. Nan, Sibo & Zhou, Ming & Li, Gengyin, 2018. "Optimal residential community demand response scheduling in smart grid," Applied Energy, Elsevier, vol. 210(C), pages 1280-1289.
    8. Spees, Kathleen & Lave, Lester B., 2007. "Demand Response and Electricity Market Efficiency," The Electricity Journal, Elsevier, vol. 20(3), pages 69-85, April.
    9. Cole, Wesley J. & Rhodes, Joshua D. & Gorman, William & Perez, Krystian X. & Webber, Michael E. & Edgar, Thomas F., 2014. "Community-scale residential air conditioning control for effective grid management," Applied Energy, Elsevier, vol. 130(C), pages 428-436.
    10. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
    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. Png, Ethan & Srinivasan, Seshadhri & Bekiroglu, Korkut & Chaoyang, Jiang & Su, Rong & Poolla, Kameshwar, 2019. "An internet of things upgrade for smart and scalable heating, ventilation and air-conditioning control in commercial buildings," Applied Energy, Elsevier, vol. 239(C), pages 408-424.
    2. Pedro Macieira & Luis Gomes & Zita Vale, 2021. "Energy Management Model for HVAC Control Supported by Reinforcement Learning," Energies, MDPI, vol. 14(24), pages 1-14, December.
    3. Greve, Thomas & Teng, Fei & Pollitt, Michael G. & Strbac, Goran, 2018. "A system operator’s utility function for the frequency response market," Applied Energy, Elsevier, vol. 231(C), pages 562-569.
    4. Salgado, Marcelo & Negrete-Pincetic, Matias & Lorca, Álvaro & Olivares, Daniel, 2021. "A low-complexity decision model for home energy management systems," Applied Energy, Elsevier, vol. 294(C).
    5. Francesco Mancini & Sabrina Romano & Gianluigi Lo Basso & Jacopo Cimaglia & Livio de Santoli, 2020. "How the Italian Residential Sector Could Contribute to Load Flexibility in Demand Response Activities: A Methodology for Residential Clustering and Developing a Flexibility Strategy," Energies, MDPI, vol. 13(13), pages 1-25, July.
    6. Zhou, Bin & Cao, Yingping & Li, Canbing & Wu, Qiuwei & Liu, Nian & Huang, Sheng & Wang, Huaizhi, 2020. "Many-criteria optimality of coordinated demand response with heterogeneous households," Energy, Elsevier, vol. 207(C).
    7. Nizami, Sohrab & Tushar, Wayes & Hossain, M.J. & Yuen, Chau & Saha, Tapan & Poor, H. Vincent, 2022. "Transactive energy for low voltage residential networks: A review," Applied Energy, Elsevier, vol. 323(C).
    8. Wang, Andong & Li, Rongling & You, Shi, 2018. "Development of a data driven approach to explore the energy flexibility potential of building clusters," Applied Energy, Elsevier, vol. 232(C), pages 89-100.
    9. Ding, Yi & Cui, Wenqi & Zhang, Shujun & Hui, Hongxun & Qiu, Yiwei & Song, Yonghua, 2019. "Multi-state operating reserve model of aggregate thermostatically-controlled-loads for power system short-term reliability evaluation," Applied Energy, Elsevier, vol. 241(C), pages 46-58.
    10. Su, Bing & Wang, Shengwei, 2020. "An agent-based distributed real-time optimal control strategy for building HVAC systems for applications in the context of future IoT-based smart sensor networks," Applied Energy, Elsevier, vol. 274(C).
    11. Tang, Hong & Wang, Shengwei & Li, Hangxin, 2021. "Flexibility categorization, sources, capabilities and technologies for energy-flexible and grid-responsive buildings: State-of-the-art and future perspective," Energy, Elsevier, vol. 219(C).
    12. Pallonetto, Fabiano & De Rosa, Mattia & D’Ettorre, Francesco & Finn, Donal P., 2020. "On the assessment and control optimisation of demand response programs in residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    13. Baldi, Simone & Korkas, Christos D. & Lv, Maolong & Kosmatopoulos, Elias B., 2018. "Automating occupant-building interaction via smart zoning of thermostatic loads: A switched self-tuning approach," Applied Energy, Elsevier, vol. 231(C), pages 1246-1258.
    14. Henggeler Antunes, Carlos & Alves, Maria João & Soares, Inês, 2022. "A comprehensive and modular set of appliance operation MILP models for demand response optimization," Applied Energy, Elsevier, vol. 320(C).
    15. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
    16. 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.
    17. Xiao, Xiangsheng & Wang, JianXiao & Hill, David J., 2022. "Impact of Large-scale concentrated solar power on energy and auxiliary markets," Applied Energy, Elsevier, vol. 318(C).
    18. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    19. Ding, Yan & Wang, Qiaochu & Kong, Xiangfei & Yang, Kun, 2019. "Multi-objective optimisation approach for campus energy plant operation based on building heating load scenarios," Applied Energy, Elsevier, vol. 250(C), pages 1600-1617.
    20. Cai, Mengmeng & Pipattanasomporn, Manisa & Rahman, Saifur, 2019. "Day-ahead building-level load forecasts using deep learning vs. traditional time-series techniques," Applied Energy, Elsevier, vol. 236(C), pages 1078-1088.
    21. Iria, José & Soares, Filipe & Matos, Manuel, 2019. "Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets," Applied Energy, Elsevier, vol. 238(C), pages 1361-1372.
    22. Lankeshwara, Gayan & Sharma, Rahul & Yan, Ruifeng & Saha, Tapan K., 2022. "Control algorithms to mitigate the effect of uncertainties in residential demand management," Applied Energy, Elsevier, vol. 306(PA).
    23. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Zhang, Zhen, 2018. "Coordination optimization of multiple thermostatically controlled load groups in distribution network with renewable energy," Applied Energy, Elsevier, vol. 231(C), pages 456-467.
    24. Dong, Zihang & Zhang, Xi & Li, Yijun & Strbac, Goran, 2023. "Values of coordinated residential space heating in demand response provision," Applied Energy, Elsevier, vol. 330(PB).
    25. Rafsanjani, Hamed Nabizadeh & Ghahramani, Ali & Nabizadeh, Amir Hossein, 2020. "iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings," Applied Energy, Elsevier, vol. 266(C).

    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. Bomela, Walter & Zlotnik, Anatoly & Li, Jr-Shin, 2018. "A phase model approach for thermostatically controlled load demand response," Applied Energy, Elsevier, vol. 228(C), pages 667-680.
    2. Nizami, Sohrab & Tushar, Wayes & Hossain, M.J. & Yuen, Chau & Saha, Tapan & Poor, H. Vincent, 2022. "Transactive energy for low voltage residential networks: A review," Applied Energy, Elsevier, vol. 323(C).
    3. 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.
    4. 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.
    5. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    6. Dehnavi, Ehsan & Abdi, Hamdi, 2016. "Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem," Energy, Elsevier, vol. 109(C), pages 1086-1094.
    7. Nizami, M.S.H. & Hossain, M.J. & Amin, B.M. Ruhul & Fernandez, Edstan, 2020. "A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading," Applied Energy, Elsevier, vol. 261(C).
    8. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    9. Derakhshan, Ghasem & Shayanfar, Heidar Ali & Kazemi, Ahad, 2016. "The optimization of demand response programs in smart grids," Energy Policy, Elsevier, vol. 94(C), pages 295-306.
    10. Shaukat, N. & Ali, S.M. & Mehmood, C.A. & Khan, B. & Jawad, M. & Farid, U. & Ullah, Z. & Anwar, S.M. & Majid, M., 2018. "A survey on consumers empowerment, communication technologies, and renewable generation penetration within Smart Grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1453-1475.
    11. 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.
    12. Andruszkiewicz, Jerzy & Lorenc, Józef & Weychan, Agnieszka, 2020. "Seasonal variability of price elasticity of demand of households using zonal tariffs and its impact on hourly load of the power system," Energy, Elsevier, vol. 196(C).
    13. Xia, Mingchao & Song, Yuguang & Chen, Qifang, 2019. "Hierarchical control of thermostatically controlled loads oriented smart buildings," Applied Energy, Elsevier, vol. 254(C).
    14. 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.
    15. Kai Ma & Chenliang Yuan & Jie Yang & Zhixin Liu & Xinping Guan, 2017. "Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response in Smart Grids," Energies, MDPI, vol. 10(7), pages 1-18, July.
    16. 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.
    17. Jerzy Andruszkiewicz & Józef Lorenc & Agnieszka Weychan, 2019. "Demand Price Elasticity of Residential Electricity Consumers with Zonal Tariff Settlement Based on Their Load Profiles," Energies, MDPI, vol. 12(22), pages 1-22, November.
    18. Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
    19. Shahryari, E. & Shayeghi, H. & Mohammadi-ivatloo, B. & Moradzadeh, M., 2018. "An improved incentive-based demand response program in day-ahead and intra-day electricity markets," Energy, Elsevier, vol. 155(C), pages 205-214.
    20. Talari, Saber & Shafie-khah, Miadreza & Osório, Gerardo J. & Aghaei, Jamshid & Catalão, João P.S., 2018. "Stochastic modelling of renewable energy sources from operators' point-of-view: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1953-1965.

    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:217:y:2018:i:c:p:166-177. 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.