IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v173y2016icp470-480.html
   My bibliography  Save this article

Provision of secondary frequency control via demand response activation on thermostatically controlled loads: Solutions and experiences from Denmark

Author

Listed:
  • Lakshmanan, Venkatachalam
  • Marinelli, Mattia
  • Hu, Junjie
  • Bindner, Henrik W.

Abstract

This paper studies the provision of secondary frequency control in electric power systems based on demand response (DR) activation on thermostatically controlled loads (TCLs) and quantifies the computation resource constraints for the control of large TCL population. Since TCLs are fast responsive loads, they represent a suitable alternative to conventional sources for providing such control. An experimental investigation with domestic fridges representing the TCLs was conducted in an islanded power system to evaluate the secondary frequency control. The investigation quantifies the flexibility of household fridge performance in terms of response time and ramp-up rate, as well as the impact on fridge temperature and behaviour after the control period. The experimental results show that TCLs are fast responsive loads for DR activation, with the average control signal response time of 24s and an equivalent ramping rate of 63% per minute, which could also comply with the requirements for primary frequency control.

Suggested Citation

  • Lakshmanan, Venkatachalam & Marinelli, Mattia & Hu, Junjie & Bindner, Henrik W., 2016. "Provision of secondary frequency control via demand response activation on thermostatically controlled loads: Solutions and experiences from Denmark," Applied Energy, Elsevier, vol. 173(C), pages 470-480.
    • Handle: RePEc:eee:appene:v:173:y:2016:i:c:p:470-480
    DOI: 10.1016/j.apenergy.2016.04.054
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916305128
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.04.054?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. Stadler, Ingo, 2008. "Power grid balancing of energy systems with high renewable energy penetration by demand response," Utilities Policy, Elsevier, vol. 16(2), pages 90-98, June.
    2. Zhong, Jin & He, Lina & Li, Canbing & Cao, Yijia & Wang, Jianhui & Fang, Baling & Zeng, Long & Xiao, Guoxuan, 2014. "Coordinated control for large-scale EV charging facilities and energy storage devices participating in frequency regulation," Applied Energy, Elsevier, vol. 123(C), pages 253-262.
    3. Pandey, Shashi Kant & Mohanty, Soumya R. & Kishor, Nand, 2013. "A literature survey on load–frequency control for conventional and distribution generation power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 318-334.
    4. Johnston, Lewis & Díaz-González, Francisco & Gomis-Bellmunt, Oriol & Corchero-García, Cristina & Cruz-Zambrano, Miguel, 2015. "Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants," Applied Energy, Elsevier, vol. 137(C), pages 660-669.
    5. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
    6. Xue, Xue & Wang, Shengwei & Yan, Chengchu & Cui, Borui, 2015. "A fast chiller power demand response control strategy for buildings connected to smart grid," Applied Energy, Elsevier, vol. 137(C), pages 77-87.
    7. Kwon, Pil Seok & Østergaard, Poul, 2014. "Assessment and evaluation of flexible demand in a Danish future energy scenario," Applied Energy, Elsevier, vol. 134(C), pages 309-320.
    8. Soares, Ana & Antunes, Carlos Henggeler & Oliveira, Carlos & Gomes, Álvaro, 2014. "A multi-objective genetic approach to domestic load scheduling in an energy management system," Energy, Elsevier, vol. 77(C), pages 144-152.
    9. Shafie-khah, Miadreza & Parsa Moghaddam, Mohsen & Sheikh-El-Eslami, Mohamad Kazem & Rahmani-Andebili, Mehdi, 2012. "Modeling of interactions between market regulations and behavior of plug-in electric vehicle aggregators in a virtual power market environment," Energy, Elsevier, vol. 40(1), pages 139-150.
    10. Ericson, Torgeir, 2009. "Direct load control of residential water heaters," Energy Policy, Elsevier, vol. 37(9), pages 3502-3512, September.
    11. Yan, Ruifeng & Saha, Tapan Kumar & Modi, Nilesh & Masood, Nahid-Al & Mosadeghy, Mehdi, 2015. "The combined effects of high penetration of wind and PV on power system frequency response," Applied Energy, Elsevier, vol. 145(C), pages 320-330.
    12. Greening, Lorna A., 2010. "Demand response resources: Who is responsible for implementation in a deregulated market?," Energy, Elsevier, vol. 35(4), pages 1518-1525.
    13. Kriett, Phillip Oliver & Salani, Matteo, 2012. "Optimal control of a residential microgrid," Energy, Elsevier, vol. 42(1), pages 321-330.
    14. Lakshmanan, Venkatachalam & Marinelli, Mattia & Kosek, Anna M. & Nørgård, Per B. & Bindner, Henrik W., 2016. "Impact of thermostatically controlled loads' demand response activation on aggregated power: A field experiment," Energy, Elsevier, vol. 94(C), pages 705-714.
    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. Latif, Abdul & Hussain, S.M. Suhail & Das, Dulal Chandra & Ustun, Taha Selim, 2020. "State-of-the-art of controllers and soft computing techniques for regulated load frequency management of single/multi-area traditional and renewable energy based power systems," Applied Energy, Elsevier, vol. 266(C).
    2. Wang, Yu & Xu, Yan & Tang, Yi, 2019. "Distributed aggregation control of grid-interactive smart buildings for power system frequency support," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Krkoleva Mateska, Aleksandra & Borozan, Vesna & Krstevski, Petar & Taleski, Rubin, 2018. "Controllable load operation in microgrids using control scheme based on gossip algorithm," Applied Energy, Elsevier, vol. 210(C), pages 1336-1346.
    4. 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.
    5. Kleidaras, Alexandros & Kiprakis, Aristides E. & Thompson, John S., 2018. "Human in the loop heterogeneous modelling of thermostatically controlled loads for demand side management studies," Energy, Elsevier, vol. 145(C), pages 754-769.
    6. Winstead, Christopher & Bhandari, Mahabir & Nutaro, James & Kuruganti, Teja, 2020. "Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy," Applied Energy, Elsevier, vol. 277(C).
    7. 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.
    8. Song, Yuguang & Chen, Fangjian & Xia, Mingchao & Chen, Qifang, 2022. "The interactive dispatch strategy for thermostatically controlled loads based on the source–load collaborative evolution," Applied Energy, Elsevier, vol. 309(C).
    9. Xi, Lei & Yu, Tao & Yang, Bo & Zhang, Xiaoshun & Qiu, Xuanyu, 2016. "A wolf pack hunting strategy based virtual tribes control for automatic generation control of smart grid," Applied Energy, Elsevier, vol. 178(C), pages 198-211.
    10. Jiang, Bo & Muzhikyan, Aramazd & Farid, Amro M. & Youcef-Toumi, Kamal, 2017. "Demand side management in power grid enterprise control: A comparison of industrial & social welfare approaches," Applied Energy, Elsevier, vol. 187(C), pages 833-846.
    11. Tang, Yi & Li, Feng & Chen, Qian & Li, Mengya & Wang, Qi & Ni, Ming & Chen, Gang, 2018. "Frequency prediction method considering demand response aggregate characteristics and control effects," Applied Energy, Elsevier, vol. 229(C), pages 936-944.
    12. Chassin, David P. & Behboodi, Sahand & Shi, Yang & Djilali, Ned, 2017. "H2-optimal transactive control of electric power regulation from fast-acting demand response in the presence of high renewables," Applied Energy, Elsevier, vol. 205(C), pages 304-315.
    13. Bao, Yi & Xu, Jian & Feng, Wei & Sun, Yuanzhang & Liao, Siyang & Yin, Rongxin & Jiang, Yazhou & Jin, Ming & Marnay, Chris, 2019. "Provision of secondary frequency regulation by coordinated dispatch of industrial loads and thermal power plants," Applied Energy, Elsevier, vol. 241(C), pages 302-312.
    14. Xia, Mingchao & Song, Yuguang & Chen, Qifang, 2019. "Hierarchical control of thermostatically controlled loads oriented smart buildings," Applied Energy, Elsevier, vol. 254(C).
    15. Deepak Kumar Gupta & Amitkumar V. Jha & Bhargav Appasani & Avireni Srinivasulu & Nicu Bizon & Phatiphat Thounthong, 2021. "Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems," Energies, MDPI, vol. 14(6), pages 1-16, March.
    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. Tohid Harighi & Ramazan Bayindir & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Eklas Hossain, 2018. "An Overview of Energy Scenarios, Storage Systems and the Infrastructure for Vehicle-to-Grid Technology," Energies, MDPI, vol. 11(8), pages 1-18, August.
    18. 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.
    19. Malik, Anam & Ravishankar, Jayashri, 2018. "A hybrid control approach for regulating frequency through demand response," Applied Energy, Elsevier, vol. 210(C), pages 1347-1362.
    20. Sossan, Fabrizio, 2017. "Equivalent electricity storage capacity of domestic thermostatically controlled loads," Energy, Elsevier, vol. 122(C), pages 767-778.
    21. Yuan, Zhao & Hesamzadeh, Mohammad Reza, 2017. "Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources," Applied Energy, Elsevier, vol. 195(C), pages 600-615.
    22. Behboodi, Sahand & Chassin, David P. & Djilali, Ned & Crawford, Curran, 2017. "Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach," Applied Energy, Elsevier, vol. 189(C), pages 336-351.
    23. Liu, Hui & Wang, Bin & Wang, Ni & Wu, Qiuwei & Yang, Yude & Wei, Hua & Li, Canbing, 2018. "Enabling strategies of electric vehicles for under frequency load shedding," Applied Energy, Elsevier, vol. 228(C), pages 843-851.
    24. Dong, Zhe & Liu, Miao & Zhang, Zuoyi & Dong, Yujie & Huang, Xiaojin, 2019. "Automatic generation control for the flexible operation of multimodular high temperature gas-cooled reactor plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 11-31.
    25. Oshnoei, Arman & Kheradmandi, Morteza & Blaabjerg, Frede & Hatziargyriou, Nikos D. & Muyeen, S.M. & Anvari-Moghaddam, Amjad, 2022. "Coordinated control scheme for provision of frequency regulation service by virtual power plants," Applied Energy, Elsevier, vol. 325(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. Hong, Seung Ho & Yu, Mengmeng & Huang, Xuefei, 2015. "A real-time demand response algorithm for heterogeneous devices in buildings and homes," Energy, Elsevier, vol. 80(C), pages 123-132.
    2. Poolla, Chaitanya & Ishihara, Abraham K. & Milito, Rodolfo, 2019. "Designing near-optimal policies for energy management in a stochastic environment," Applied Energy, Elsevier, vol. 242(C), pages 1725-1737.
    3. Wang, Ge & Zhang, Qi & Li, Hailong & McLellan, Benjamin C. & Chen, Siyuan & Li, Yan & Tian, Yulu, 2017. "Study on the promotion impact of demand response on distributed PV penetration by using non-cooperative game theoretical analysis," Applied Energy, Elsevier, vol. 185(P2), pages 1869-1878.
    4. Huda, A.S.N. & Živanović, R., 2017. "Large-scale integration of distributed generation into distribution networks: Study objectives, review of models and computational tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 974-988.
    5. Jia, Hongjie & Li, Xiaomeng & Mu, Yunfei & Xu, Chen & Jiang, Yilang & Yu, Xiaodan & Wu, Jianzhong & Dong, Chaoyu, 2018. "Coordinated control for EV aggregators and power plants in frequency regulation considering time-varying delays," Applied Energy, Elsevier, vol. 210(C), pages 1363-1376.
    6. Batas Bjelić, Ilija & Rajaković, Nikola & Krajačić, Goran & Duić, Neven, 2016. "Two methods for decreasing the flexibility gap in national energy systems," Energy, Elsevier, vol. 115(P3), pages 1701-1709.
    7. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    8. Gomes, A. & Antunes, C. Henggeler & Martinho, J., 2013. "A physically-based model for simulating inverter type air conditioners/heat pumps," Energy, Elsevier, vol. 50(C), pages 110-119.
    9. Lešić, Vinko & Martinčević, Anita & Vašak, Mario, 2017. "Modular energy cost optimization for buildings with integrated microgrid," Applied Energy, Elsevier, vol. 197(C), pages 14-28.
    10. Neves, Diana & Pina, André & Silva, Carlos A., 2015. "Demand response modeling: A comparison between tools," Applied Energy, Elsevier, vol. 146(C), pages 288-297.
    11. Fontenot, Hannah & Dong, Bing, 2019. "Modeling and control of building-integrated microgrids for optimal energy management – A review," Applied Energy, Elsevier, vol. 254(C).
    12. Shirazi, Elham & Jadid, Shahram, 2017. "Cost reduction and peak shaving through domestic load shifting and DERs," Energy, Elsevier, vol. 124(C), pages 146-159.
    13. Arslan, Okan & Karasan, Oya Ekin, 2013. "Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks," Energy, Elsevier, vol. 60(C), pages 116-124.
    14. Zahra Pooranian & Jemal H. Abawajy & Vinod P & Mauro Conti, 2018. "Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters," Energies, MDPI, vol. 11(6), pages 1-17, May.
    15. Shang-Guan, Xingchen & He, Yong & Zhang, Chuanke & Jiang, Lin & Spencer, Joseph William & Wu, Min, 2020. "Sampled-data based discrete and fast load frequency control for power systems with wind power," Applied Energy, Elsevier, vol. 259(C).
    16. Li, Bosong & Shen, Jingshuang & Wang, Xu & Jiang, Chuanwen, 2016. "From controllable loads to generalized demand-side resources: A review on developments of demand-side resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 936-944.
    17. Meng, Jian & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qu, Bo, 2016. "Dynamic frequency response from electric vehicles considering travelling behavior in the Great Britain power system," Applied Energy, Elsevier, vol. 162(C), pages 966-979.
    18. Yasuaki Miyazato & Hayato Tahara & Kosuke Uchida & Cirio Celestino Muarapaz & Abdul Motin Howlader & Tomonobu Senjyu, 2016. "Multi-Objective Optimization for Smart House Applied Real Time Pricing Systems," Sustainability, MDPI, vol. 8(12), pages 1-22, December.
    19. 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.
    20. Li, Zhengshuo & Guo, Qinglai & Sun, Hongbin & Wang, Jianhui, 2015. "Storage-like devices in load leveling: Complementarity constraints and a new and exact relaxation method," Applied Energy, Elsevier, vol. 151(C), pages 13-22.

    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:173:y:2016:i:c:p:470-480. 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.