IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v35y2010i9p3883-3890.html
   My bibliography  Save this article

Optimal reserve capacity allocation with consideration of customer reliability requirements

Author

Listed:
  • Najafi, M.
  • Ehsan, M.
  • Fotuhi-Firuzabad, M.
  • Akhavein, A.
  • Afshar, K.

Abstract

An algorithm for determining optimal reserve capacity in a power market is presented in this paper. Optimization process in the proposed algorithm is based on the cost-benefit trade off. Market clearance is executed with consideration of uncertainties of power system components in an aggregated environment. It is assumed that both generating units and interruptible loads participate in the reserve market. In addition, customers’ reliability requirements are considered as constraints for decision making process of ISO. The rendered method considers random outages of generating units and transmission lines and determined outage of interruptible loads and employs Monte Carlo Simulation (MCS) for scenarios generation. Unlike previous methods in which a constant value is assumed for cost of the energy not supplied, a flexible value for this parameter is applied which shows an important effect in the evaluation results. The performance of the proposed method has been examined on the IEEE-Reliability Test System (IEEE-RTS).

Suggested Citation

  • Najafi, M. & Ehsan, M. & Fotuhi-Firuzabad, M. & Akhavein, A. & Afshar, K., 2010. "Optimal reserve capacity allocation with consideration of customer reliability requirements," Energy, Elsevier, vol. 35(9), pages 3883-3890.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:9:p:3883-3890
    DOI: 10.1016/j.energy.2010.05.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544210003142
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2010.05.044?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. Walawalkar, Rahul & Fernands, Stephen & Thakur, Netra & Chevva, Konda Reddy, 2010. "Evolution and current status of demand response (DR) in electricity markets: Insights from PJM and NYISO," Energy, Elsevier, vol. 35(4), pages 1553-1560.
    2. Aghaei, J. & Shayanfar, H.A. & Amjady, N., 2009. "Joint market clearing in a stochastic framework considering power system security," Applied Energy, Elsevier, vol. 86(9), pages 1675-1682, September.
    3. Zarnikau, Jay W., 2010. "Demand participation in the restructured Electric Reliability Council of Texas market," Energy, Elsevier, vol. 35(4), pages 1536-1543.
    4. Shayesteh, E. & Yousefi, A. & Parsa Moghaddam, M., 2010. "A probabilistic risk-based approach for spinning reserve provision using day-ahead demand response program," Energy, Elsevier, vol. 35(5), pages 1908-1915.
    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. Partovi, Farzad & Nikzad, Mehdi & Mozafari, Babak & Ranjbar, Ali Mohamad, 2011. "A stochastic security approach to energy and spinning reserve scheduling considering demand response program," Energy, Elsevier, vol. 36(5), pages 3130-3137.
    2. Jun Dong & Anyuan Fu & Yao Liu & Shilin Nie & Peiwen Yang & Linpeng Nie, 2019. "Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption," Sustainability, MDPI, vol. 11(24), pages 1-22, December.
    3. Scholtens, Bert & Wagenaar, Robert, 2011. "Revisions of international firms’ energy reserves and the reaction of the stock market," Energy, Elsevier, vol. 36(5), pages 3541-3546.

    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. Partovi, Farzad & Nikzad, Mehdi & Mozafari, Babak & Ranjbar, Ali Mohamad, 2011. "A stochastic security approach to energy and spinning reserve scheduling considering demand response program," Energy, Elsevier, vol. 36(5), pages 3130-3137.
    2. Liu, Yingqi, 2017. "Demand response and energy efficiency in the capacity resource procurement: Case studies of forward capacity markets in ISO New England, PJM and Great Britain," Energy Policy, Elsevier, vol. 100(C), pages 271-282.
    3. Peter Warren, 2018. "Demand-side policy: Global evidence base and implementation patterns," Energy & Environment, , vol. 29(5), pages 706-731, August.
    4. Nikzad, Mehdi & Mozafari, Babak & Bashirvand, Mahdi & Solaymani, Soodabeh & Ranjbar, Ali Mohamad, 2012. "Designing time-of-use program based on stochastic security constrained unit commitment considering reliability index," Energy, Elsevier, vol. 41(1), pages 541-548.
    5. Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2011. "Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market," Applied Energy, Elsevier, vol. 88(7), pages 2548-2558, July.
    6. Olmos, Luis & Ruester, Sophia & Liong, Siok-Jen & Glachant, Jean-Michel, 2011. "Energy efficiency actions related to the rollout of smart meters for small consumers, application to the Austrian system," Energy, Elsevier, vol. 36(7), pages 4396-4409.
    7. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    8. Zhou, Kaile & Yang, Shanlin, 2015. "Demand side management in China: The context of China’s power industry reform," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 954-965.
    9. Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2012. "Integrating the cold load pickup effect of reserve supplying demand response resource in social cost minimization based system scheduling," Energy, Elsevier, vol. 45(1), pages 1034-1041.
    10. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    11. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    12. Keon Baek & Woong Ko & Jinho Kim, 2019. "Optimal Scheduling of Distributed Energy Resources in Residential Building under the Demand Response Commitment Contract," Energies, MDPI, vol. 12(14), pages 1-19, July.
    13. 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.
    14. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    15. Siler-Evans, Kyle & Morgan, M. Granger & Azevedo, Inês Lima, 2012. "Distributed cogeneration for commercial buildings: Can we make the economics work?," Energy Policy, Elsevier, vol. 42(C), pages 580-590.
    16. Eric L. Prentis, 2014. "Deregulation & Privatization: Texas Electric Power Market Evidence," Review of Business and Finance Studies, The Institute for Business and Finance Research, vol. 5(2), pages 117-126.
    17. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    18. Ying-Yi Hong & Gerard Francesco DG. Apolinario, 2021. "Uncertainty in Unit Commitment in Power Systems: A Review of Models, Methods, and Applications," Energies, MDPI, vol. 14(20), pages 1-47, October.
    19. 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.
    20. Cao, M.F. & Huang, G.H. & Lin, Q.G., 2010. "Integer programming with random-boundary intervals for planning municipal power systems," Applied Energy, Elsevier, vol. 87(8), pages 2506-2516, August.

    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:energy:v:35:y:2010:i:9:p:3883-3890. 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.journals.elsevier.com/energy .

    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.