IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i6p2144-d771632.html
   My bibliography  Save this article

Impact of Local Emergency Demand Response Programs on the Operation of Electricity and Gas Systems

Author

Listed:
  • Mohammad Mehdi Davari

    (Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran)

  • Hossein Ameli

    (Control and Power Group, Imperial College, London SW7 2AZ, UK)

  • Mohammad Taghi Ameli

    (Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran)

  • Goran Strbac

    (Control and Power Group, Imperial College, London SW7 2AZ, UK)

Abstract

With increasing attention to climate change, the penetration level of renewable energy sources (RES) in the electricity network is increasing. Due to the intermittency of RES, gas-fired power plants could play a significant role in backing up the RES in order to maintain the supply–demand balance. As a result, the interaction between gas and power networks are significantly increasing. On the other hand, due to the increase in peak demand (e.g., electrification of heat), network operators are willing to execute demand response programs (DRPs) to improve congestion management and reduce costs. In this context, modeling and optimal implementation of DRPs in proportion to the demand is one of the main issues for gas and power network operators. In this paper, an emergency demand response program (EDRP) is implemented locally to reduce the congestion of transmission lines and gas pipelines more efficiently. Additionally, the effects of optimal implementation of local emergency demand response program (LEDRP) in gas and power networks using linear and non-linear economic models (power, exponential and logarithmic) for EDRP in terms of cost and line congestion and risk of unserved demand are investigated. The most reliable demand response model is the approach that has the least difference between the estimated demand and the actual demand. Furthermore, the role of the LEDRP in the case of hydrogen injection instead of natural gas in the gas infrastructure is investigated. The optimal incentives for each bus or node are determined based on the power transfer distribution factor, gas transfer distribution factor, available electricity or gas transmission capability, and combination of unit commitment with the LEDRP in the integrated operation of these networks. According to the results, implementing the LEDRP in gas and power networks reduces the total operation cost up to 11% and could facilitate hydrogen injection to the network. The proposed hybrid model is implemented on a 24-bus IEEE electricity network and a 15-bus gas network to quantify the role and value of different LEDRP models.

Suggested Citation

  • Mohammad Mehdi Davari & Hossein Ameli & Mohammad Taghi Ameli & Goran Strbac, 2022. "Impact of Local Emergency Demand Response Programs on the Operation of Electricity and Gas Systems," Energies, MDPI, vol. 15(6), pages 1-20, March.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2144-:d:771632
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/6/2144/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/6/2144/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lun Yang & Xia Zhao & Xinyi Li & Wei Yan, 2018. "Probabilistic Steady-State Operation and Interaction Analysis of Integrated Electricity, Gas and Heating Systems," Energies, MDPI, vol. 11(4), pages 1-21, April.
    2. Hines, Paul & Apt, Jay & Talukdar, Sarosh, 2009. "Large blackouts in North America: Historical trends and policy implications," Energy Policy, Elsevier, vol. 37(12), pages 5249-5259, December.
    3. Wang, Fei & Ge, Xinxin & Yang, Peng & Li, Kangping & Mi, Zengqiang & Siano, Pierluigi & Duić, Neven, 2020. "Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing," Energy, Elsevier, vol. 213(C).
    4. Philip Tafarte & Annedore Kanngießer & Martin Dotzauer & Benedikt Meyer & Anna Grevé & Markus Millinger, 2020. "Interaction of Electrical Energy Storage, Flexible Bioenergy Plants and System-friendly Renewables in Wind- or Solar PV-dominated Regions," Energies, MDPI, vol. 13(5), pages 1-25, March.
    5. 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.
    6. Ali Mohammad Rostami & Hossein Ameli & Mohammad Taghi Ameli & Goran Strbac, 2020. "Secure Operation of Integrated Natural Gas and Electricity Transmission Networks," Energies, MDPI, vol. 13(18), pages 1-17, September.
    7. Claude Ziad El-Bayeh & Ursula Eicker & Khaled Alzaareer & Brahim Brahmi & Mohamed Zellagui, 2020. "A Novel Data-Energy Management Algorithm for Smart Transformers to Optimize the Total Load Demand in Smart Homes," Energies, MDPI, vol. 13(18), pages 1-22, September.
    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. Masoumeh Sharifpour & Mohammad Taghi Ameli & Hossein Ameli & Goran Strbac, 2023. "A Resilience-Oriented Approach for Microgrid Energy Management with Hydrogen Integration during Extreme Events," Energies, MDPI, vol. 16(24), pages 1-18, December.
    2. Spyros Giannelos & Stefan Borozan & Marko Aunedi & Xi Zhang & Hossein Ameli & Danny Pudjianto & Ioannis Konstantelos & Goran Strbac, 2023. "Modelling Smart Grid Technologies in Optimisation Problems for Electricity Grids," Energies, MDPI, vol. 16(13), pages 1-15, June.
    3. Yizheng Li & Yuan Zeng & Zhidong Wang & Lang Zhao & Yao Wang, 2023. "Optimal Configuration Analysis Method of Energy Storage System Based on “Equal Area Criterion”," Energies, MDPI, vol. 16(24), pages 1-29, December.
    4. Mohammad Mehdi Amiri & Mohammad Taghi Ameli & Goran Strbac & Danny Pudjianto & Hossein Ameli, 2024. "The Role of Flexibility in the Integrated Operation of Low-Carbon Gas and Electricity Systems: A Review," Energies, MDPI, vol. 17(9), pages 1-26, May.

    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, Li & Gao, Yan & Zhu, Hongbo & Tao, Li, 2022. "Bi-level stochastic real-time pricing model in multi-energy generation system: A reinforcement learning approach," Energy, Elsevier, vol. 239(PA).
    2. Chen, J.J. & Qi, B.X. & Rong, Z.K. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement," Energy, Elsevier, vol. 217(C).
    3. Ali Mohammad Rostami & Hossein Ameli & Mohammad Taghi Ameli & Goran Strbac, 2020. "Secure Operation of Integrated Natural Gas and Electricity Transmission Networks," Energies, MDPI, vol. 13(18), pages 1-17, September.
    4. Dunn, Laurel N. & Sohn, Michael D. & LaCommare, Kristina Hamachi & Eto, Joseph H., 2019. "Exploratory analysis of high-resolution power interruption data reveals spatial and temporal heterogeneity in electric grid reliability," Energy Policy, Elsevier, vol. 129(C), pages 206-214.
    5. Seong-Hyeon Cha & Sun-Hyeok Kwak & Woong Ko, 2023. "A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market," Energies, MDPI, vol. 16(20), pages 1-27, October.
    6. Nikolai Voropai, 2020. "Electric Power System Transformations: A Review of Main Prospects and Challenges," Energies, MDPI, vol. 13(21), pages 1-16, October.
    7. Moroni, Stefano & Antoniucci, Valentina & Bisello, Adriano, 2016. "Energy sprawl, land taking and distributed generation: towards a multi-layered density," Energy Policy, Elsevier, vol. 98(C), pages 266-273.
    8. Johansson, Bengt, 2013. "A broadened typology on energy and security," Energy, Elsevier, vol. 53(C), pages 199-205.
    9. Guoqiang Sun & Wenxue Wang & Yi Wu & Wei Hu & Zijun Yang & Zhinong Wei & Haixiang Zang & Sheng Chen, 2019. "A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network," Energies, MDPI, vol. 12(7), pages 1-20, March.
    10. Vivian Do & Heather McBrien & Nina M. Flores & Alexander J. Northrop & Jeffrey Schlegelmilch & Mathew V. Kiang & Joan A. Casey, 2023. "Spatiotemporal distribution of power outages with climate events and social vulnerability in the USA," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    11. Künneke, Rolf & Groenewegen, John & Ménard, Claude, 2010. "Aligning modes of organization with technology: Critical transactions in the reform of infrastructures," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 494-505, September.
    12. Meier, Alan & Ueno, Tsuyoshi & Pritoni, Marco, 2019. "Using data from connected thermostats to track large power outages in the United States," Applied Energy, Elsevier, vol. 256(C).
    13. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Xu, Wenya & Wang, Zixuan, 2022. "Operational performance and grid-support assessment of distributed flexibility practices among residential prosumers under high PV penetration," Energy, Elsevier, vol. 238(PB).
    14. Oleh Lukianykhin & Tetiana Bogodorova, 2021. "Voltage Control-Based Ancillary Service Using Deep Reinforcement Learning," Energies, MDPI, vol. 14(8), pages 1-22, April.
    15. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    16. Carmine Cancro & Camelia Delcea & Salvatore Fabozzi & Gabriella Ferruzzi & Giorgio Graditi & Valeria Palladino & Maria Valenti, 2022. "A Profitability Analysis for an Aggregator in the Ancillary Services Market: An Italian Case Study," Energies, MDPI, vol. 15(9), pages 1-26, April.
    17. Shield, Stephen A. & Quiring, Steven M. & Pino, Jordan V. & Buckstaff, Ken, 2021. "Major impacts of weather events on the electrical power delivery system in the United States," Energy, Elsevier, vol. 218(C).
    18. Handriyanti Diah Puspitarini & Baptiste François & Marco Baratieri & Casey Brown & Mattia Zaramella & Marco Borga, 2020. "Complementarity between Combined Heat and Power Systems, Solar PV and Hydropower at a District Level: Sensitivity to Climate Characteristics along an Alpine Transect," Energies, MDPI, vol. 13(16), pages 1-19, August.
    19. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao & Tang, Bowen, 2017. "Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system," Applied Energy, Elsevier, vol. 190(C), pages 1126-1137.
    20. Mudasser, Muhammad & Yiridoe, Emmanuel K. & Corscadden, Kenneth, 2015. "Cost-benefit analysis of grid-connected wind–biogas hybrid energy production, by turbine capacity and site," Renewable Energy, Elsevier, vol. 80(C), pages 573-582.

    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:gam:jeners:v:15:y:2022:i:6:p:2144-:d:771632. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.