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Contribution of emergency demand response programs in power system reliability

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  • Aghaei, Jamshid
  • Alizadeh, Mohammad-Iman
  • Siano, Pierluigi
  • Heidari, Alireza

Abstract

Nowadays, demand response has become one of the essential components of recent deregulated power systems as it can offer many distinguished features, such as availability, quickness, and applicability. DRPs (Demand response programs), announced by the federal energy regulatory commission, are among the most accepted and practical features of demand side management. DRPs not only can contribute in mitigating the intermittent effects of renewable energy resources but also can be used either to lower high energy prices, occurred in wholesale electricity markets, or when the security of power systems is at risk. In this paper, the influence of emergency demand response programs in improving reliability in case of failure of generation units is investigated. In the proposed reliability based optimization approach, the generation failure is modeled based on its forced outage rate. The proposed method can help independent system operators to schedule day-ahead generating units in a more reliable manner and can facilitate the participation of consumers to increase the total social welfare in the case of an emergency. Moreover, the mixed integer programming formulation allows implementing the proposed method by using available tractable linear solvers. Eventually, the applicability of the proposed model is tested on the IEEE 24-bus reliability test system and its effects on the value of lost load and the expected load not served are discussed.

Suggested Citation

  • Aghaei, Jamshid & Alizadeh, Mohammad-Iman & Siano, Pierluigi & Heidari, Alireza, 2016. "Contribution of emergency demand response programs in power system reliability," Energy, Elsevier, vol. 103(C), pages 688-696.
  • Handle: RePEc:eee:energy:v:103:y:2016:i:c:p:688-696
    DOI: 10.1016/j.energy.2016.03.031
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    1. Ampimah, Benjamin Chris & Sun, Mei & Han, Dun & Wang, Xueyin, 2018. "Optimizing sheddable and shiftable residential electricity consumption by incentivized peak and off-peak credit function approach," Applied Energy, Elsevier, vol. 210(C), pages 1299-1309.
    2. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Prosumer integration into the Brazilian energy sector: An overview of innovative business models and regulatory challenges," Energy Policy, Elsevier, vol. 161(C).
    3. Abdin, Islam & Li, Yan-Fu & Zio, Enrico, 2017. "Risk assessment of power transmission network failures in a uniform pricing electricity market environment," Energy, Elsevier, vol. 138(C), pages 1042-1055.
    4. Aftab Ahmed Almani & Xueshan Han, 2023. "Real-Time Pricing-Enabled Demand Response Using Long Short-Time Memory Deep Learning," Energies, MDPI, vol. 16(5), pages 1-13, March.
    5. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    6. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    7. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    8. Gong, Xuan & De Paola, Antonio & Angeli, David & Strbac, Goran, 2019. "A game-theoretic approach for price-based coordination of flexible devices operating in integrated energy-reserve markets," Energy, Elsevier, vol. 189(C).
    9. Mansourshoar, Paria & Yazdankhah, Ahmad Sadeghi & Vatanpour, Mohsen & Mohammadi-Ivatloo, Behnam, 2022. "Impact of implementing a price-based demand response program on the system reliability in security-constrained unit commitment problem coupled with wind farms in the presence of contingencies," Energy, Elsevier, vol. 255(C).
    10. Ashish Shrestha & Francisco Gonzalez-Longatt, 2021. "Frequency Stability Issues and Research Opportunities in Converter Dominated Power System," Energies, MDPI, vol. 14(14), pages 1-28, July.
    11. Otashu, Joannah I. & Baldea, Michael, 2018. "Grid-level “battery” operation of chemical processes and demand-side participation in short-term electricity markets," Applied Energy, Elsevier, vol. 220(C), pages 562-575.
    12. Salvatore Favuzza & Mariano Giuseppe Ippolito & Fabio Massaro & Rossano Musca & Eleonora Riva Sanseverino & Giuseppe Schillaci & Gaetano Zizzo, 2018. "Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks," Energies, MDPI, vol. 11(3), pages 1-15, March.
    13. 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.
    14. Ahmed Ismail & Mustafa Baysal, 2023. "Dynamic Pricing Based on Demand Response Using Actor–Critic Agent Reinforcement Learning," Energies, MDPI, vol. 16(14), pages 1-19, July.
    15. Imani, Mahmood Hosseini & Ghadi, M. Jabbari & Ghavidel, Sahand & Li, Li, 2018. "Demand Response Modeling in Microgrid Operation: a Review and Application for Incentive-Based and Time-Based Programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 486-499.
    16. Zeng, Bo & Zhao, Dongbo & Singh, Chanan & Wang, Jianhui & Chen, Chen, 2019. "Holistic modeling framework of demand response considering multi-timescale uncertainties for capacity value estimation," Applied Energy, Elsevier, vol. 247(C), pages 692-702.
    17. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    18. Mahmood Hosseini Imani & Shaghayegh Zalzar & Amir Mosavi & Shahaboddin Shamshirband, 2018. "Strategic Behavior of Retailers for Risk Reduction and Profit Increment via Distributed Generators and Demand Response Programs," Energies, MDPI, vol. 11(6), pages 1-24, June.
    19. Gao, Jianwei & Ma, Zeyang & Guo, Fengjia, 2019. "The influence of demand response on wind-integrated power system considering participation of the demand side," Energy, Elsevier, vol. 178(C), pages 723-738.
    20. Neda Hajibandeh & Miadreza Shafie-khah & Sobhan Badakhshan & Jamshid Aghaei & Sílvio J. P. S. Mariano & João P. S. Catalão, 2019. "Multi-Objective Market Clearing Model with an Autonomous Demand Response Scheme," Energies, MDPI, vol. 12(7), pages 1-16, April.

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