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Determining reserve requirements in DK1 area of Nord Pool using a probabilistic approach

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  • Saez-Gallego, Javier
  • Morales, Juan M.
  • Madsen, Henrik
  • Jónsson, Tryggvi

Abstract

Allocation of electricity reserves is the main tool for transmission system operators to guarantee a reliable and safe real-time operation of the power system. Traditionally, a deterministic criterion is used to establish the level of reserve. Alternative criteria are given in this paper by using a probabilistic framework where the reserve requirements are computed based on scenarios of wind power forecast error, load forecast errors and power plant outages. Our approach is first motivated by the increasing wind power penetration in power systems worldwide as well as the current market design of the DK1 area of Nord Pool, where reserves are scheduled prior to the closure of the day-ahead market. The risk of the solution under the resulting reserve schedule is controlled by two measures: the LOLP (Loss-of-Load Probability) and the CVaR (Conditional Value at Risk). Results show that during the case study period, the LOLP methodology produces more costly and less reliable reserve schedules, whereas the solution from the CVaR-method increases the safety of the overall system while decreasing the associated reserve costs, with respect to the method currently used by the Danish TSO (Transmission System Operator).

Suggested Citation

  • Saez-Gallego, Javier & Morales, Juan M. & Madsen, Henrik & Jónsson, Tryggvi, 2014. "Determining reserve requirements in DK1 area of Nord Pool using a probabilistic approach," Energy, Elsevier, vol. 74(C), pages 682-693.
    • Handle: RePEc:eee:energy:v:74:y:2014:i:c:p:682-693
    DOI: 10.1016/j.energy.2014.07.034
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    References listed on IDEAS

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    1. Leahy, Eimear & Tol, Richard S.J., 2011. "An estimate of the value of lost load for Ireland," Energy Policy, Elsevier, vol. 39(3), pages 1514-1520, March.
    2. 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.
    3. 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.
    4. Amjady, N. & Aghaei, J. & Shayanfar, H.A., 2009. "Market clearing of joint energy and reserves auctions using augmented payment minimization," Energy, Elsevier, vol. 34(10), pages 1552-1559.
    5. Moller, Jan Kloppenborg & Nielsen, Henrik Aalborg & Madsen, Henrik, 2008. "Time-adaptive quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1292-1303, January.
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    1. Shayesteh, E. & Amelin, M. & Soder, L., 2015. "Area equivalents for spinning reserve determination in interconnected power systems," Energy, Elsevier, vol. 88(C), pages 907-916.
    2. Goudarzi, Arman & Viray, Z.N.C. & Siano, Pierluigi & Swanson, Andrew G. & Coller, John V. & Kazemi, Mehdi, 2017. "A probabilistic determination of required reserve levels in an energy and reserve co-optimized electricity market with variable generation," Energy, Elsevier, vol. 130(C), pages 258-275.
    3. Insu Do & Siyoung Lee & Gab-Su Seo & Sungsoo Kim, 2023. "An Analysis of the Effects of Renewable Energy Intermittency on the 2030 Korean Electricity Market," Energies, MDPI, vol. 16(10), pages 1-19, May.
    4. Krishna, Attoti Bharath & Abhyankar, Abhijit R., 2023. "Time-coupled day-ahead wind power scenario generation: A combined regular vine copula and variance reduction method," Energy, Elsevier, vol. 265(C).
    5. Kyung-bin Kwon & Hyeongon Park & Jae-Kun Lyu & Jong-Keun Park, 2016. "Cost Analysis Method for Estimating Dynamic Reserve Considering Uncertainties in Supply and Demand," Energies, MDPI, vol. 9(10), pages 1-16, October.

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