IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v192y2017icp360-369.html
   My bibliography  Save this article

Benefits of demand-side response in combined gas and electricity networks

Author

Listed:
  • Qadrdan, Meysam
  • Cheng, Meng
  • Wu, Jianzhong
  • Jenkins, Nick

Abstract

Active demand side response (DSR) will provide a significant opportunity to enhance the power system flexibility in the Great Britain (GB). Although electricity peak shaving has a clear reduction on required investments in the power system, the benefits on the gas supply network have not been examined. Using a Combined Gas and Electricity Networks expansion model (CGEN+), the impact of DSR on the electricity and gas supply systems in GB was investigated for the time horizon from 2010 to 2050s. The results showed a significant reduction in the capacity of new gas-fired power plants, caused by electricity peak shaving. The reduction of gas-fired power plants achieved through DSR consequently reduced the requirements for gas import capacity up to 90 million cubic meter per day by 2050. The cost savings resulted from the deployment of DSR over a 50-year time horizon from 2010 was estimated to be around £60 billion for the GB power system. Although, the cost saving achieved in the gas network was not significant, it was shown that the DSR will have a crucial role to play in the improvement of security of gas supply.

Suggested Citation

  • Qadrdan, Meysam & Cheng, Meng & Wu, Jianzhong & Jenkins, Nick, 2017. "Benefits of demand-side response in combined gas and electricity networks," Applied Energy, Elsevier, vol. 192(C), pages 360-369.
    • Handle: RePEc:eee:appene:v:192:y:2017:i:c:p:360-369
    DOI: 10.1016/j.apenergy.2016.10.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916314866
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.10.047?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. Chaudry, Modassar & Jenkins, Nick & Qadrdan, Meysam & Wu, Jianzhong, 2014. "Combined gas and electricity network expansion planning," Applied Energy, Elsevier, vol. 113(C), pages 1171-1187.
    2. Siano, Pierluigi & Sarno, Debora, 2016. "Assessing the benefits of residential demand response in a real time distribution energy market," Applied Energy, Elsevier, vol. 161(C), pages 533-551.
    3. I, Sahadudheen, 2012. "Long run demand for money in India: A co-integration approach," MPRA Paper 65563, University Library of Munich, Germany, revised 2012.
    4. Yin, Rongxin & Kara, Emre C. & Li, Yaping & DeForest, Nicholas & Wang, Ke & Yong, Taiyou & Stadler, Michael, 2016. "Quantifying flexibility of commercial and residential loads for demand response using setpoint changes," Applied Energy, Elsevier, vol. 177(C), pages 149-164.
    5. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    6. Lau, E.T. & Yang, Q. & Stokes, L. & Taylor, G.A. & Forbes, A.B. & Clarkson, P. & Wright, P.S. & Livina, V.N., 2015. "Carbon savings in the UK demand side response programmes," Applied Energy, Elsevier, vol. 159(C), pages 478-489.
    7. Joung, Manho & Kim, Jinho, 2013. "Assessing demand response and smart metering impacts on long-term electricity market prices and system reliability," Applied Energy, Elsevier, vol. 101(C), pages 441-448.
    8. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    9. 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.
    10. Cui, Hantao & Li, Fangxing & Hu, Qinran & Bai, Linquan & Fang, Xin, 2016. "Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants," Applied Energy, Elsevier, vol. 176(C), pages 183-195.
    11. Qadrdan, Meysam & Chaudry, Modassar & Wu, Jianzhong & Jenkins, Nick & Ekanayake, Janaka, 2010. "Impact of a large penetration of wind generation on the GB gas network," Energy Policy, Elsevier, vol. 38(10), pages 5684-5695, October.
    12. Qadrdan, Meysam & Chaudry, Modassar & Jenkins, Nick & Baruah, Pranab & Eyre, Nick, 2015. "Impact of transition to a low carbon power system on the GB gas network," Applied Energy, Elsevier, vol. 151(C), pages 1-12.
    13. Harris, A.R. & Rogers, Michelle Marinich & Miller, Carol J. & McElmurry, Shawn P. & Wang, Caisheng, 2015. "Residential emissions reductions through variable timing of electricity consumption," Applied Energy, Elsevier, vol. 158(C), pages 484-489.
    14. Drysdale, Brian & Wu, Jianzhong & Jenkins, Nick, 2015. "Flexible demand in the GB domestic electricity sector in 2030," Applied Energy, Elsevier, vol. 139(C), pages 281-290.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Fei & Xu, Hanchen & Xu, Ti & Li, Kangping & Shafie-khah, Miadreza & Catalão, João. P.S., 2017. "The values of market-based demand response on improving power system reliability under extreme circumstances," Applied Energy, Elsevier, vol. 193(C), pages 220-231.
    2. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Li, Xiaojing, 2017. "Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process," Applied Energy, Elsevier, vol. 194(C), pages 696-704.
    3. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    4. Qiao, Zheng & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Liu, Yuquan & Xiong, Wen, 2017. "An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power," Applied Energy, Elsevier, vol. 201(C), pages 343-353.
    5. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    6. Daniel Scamman & Baltazar Solano-Rodríguez & Steve Pye & Lai Fong Chiu & Andrew Z. P. Smith & Tiziano Gallo Cassarino & Mark Barrett & Robert Lowe, 2020. "Heat Decarbonisation Modelling Approaches in the UK: An Energy System Architecture Perspective," Energies, MDPI, vol. 13(8), pages 1-28, April.
    7. Hui, Hongxun & Ding, Yi & Shi, Qingxin & Li, Fangxing & Song, Yonghua & Yan, Jinyue, 2020. "5G network-based Internet of Things for demand response in smart grid: A survey on application potential," Applied Energy, Elsevier, vol. 257(C).
    8. Devlin, Joseph & Li, Kang & Higgins, Paraic & Foley, Aoife, 2017. "A multi vector energy analysis for interconnected power and gas systems," Applied Energy, Elsevier, vol. 192(C), pages 315-328.
    9. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    10. Aunedi, Marko & Pantaleo, Antonio Marco & Kuriyan, Kamal & Strbac, Goran & Shah, Nilay, 2020. "Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems," Applied Energy, Elsevier, vol. 276(C).
    11. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    12. Pellegrino, Sandro & Lanzini, Andrea & Leone, Pierluigi, 2017. "Greening the gas network – The need for modelling the distributed injection of alternative fuels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 266-286.
    13. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Ke, Deping & Zhang, Zhen & Wang, Jing, 2018. "A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy," Applied Energy, Elsevier, vol. 224(C), pages 659-670.
    14. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Liao, Siyang & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao, 2018. "Coordinated operation of gas-electricity integrated distribution system with multi-CCHP and distributed renewable energy sources," Applied Energy, Elsevier, vol. 211(C), pages 237-248.
    15. Sharma, A. & Bhakar, R. & Tiwari, H.P. & Li, R. & Li, F., 2017. "A novel hierarchical contribution factor based model for distribution use-of-system charges," Applied Energy, Elsevier, vol. 208(C), pages 996-1006.
    16. Li, Pei-Hao & Pye, Steve, 2018. "Assessing the benefits of demand-side flexibility in residential and transport sectors from an integrated energy systems perspective," Applied Energy, Elsevier, vol. 228(C), pages 965-979.
    17. Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic–multiobjective market equilibrium analysis of a demand response program in energy market under uncertainty," Applied Energy, Elsevier, vol. 182(C), pages 500-506.
    18. Bertsch, Valentin & Harold, Jason & Fell, Harrison, 2019. "Consumer preferences for end-use specific curtailable electricity contracts on household appliances during peak load hours," Papers WP632, Economic and Social Research Institute (ESRI).
    19. Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.
    20. Antenucci, Andrea & Sansavini, Giovanni, 2019. "Extensive CO2 recycling in power systems via Power-to-Gas and network storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 33-43.

    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:192:y:2017:i:c:p:360-369. 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.