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A probabilistic determination of required reserve levels in an energy and reserve co-optimized electricity market with variable generation

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  • Goudarzi, Arman
  • Viray, Z.N.C.
  • Siano, Pierluigi
  • Swanson, Andrew G.
  • Coller, John V.
  • Kazemi, Mehdi

Abstract

The determination of the required reserve levels due to the incremental trend of injecting wind energy into the power grid with a high level of wind energy penetration is complicated because of the variability of wind energy. This study proposes a method, based on the logarithmic barrier interior point method for optimal power flow and Monte Carlo analysis, to evaluate the required reserve levels for a grid with variable generation. A Gaussian distribution was used to model the dynamic load demand, while a unique linearized least-square approximation was used to model the wind turbines. In order to demonstrate the capability of the proposed algorithm, the methodology was applied to a modified IEEE 30-bus system with two wind-farms. The simulation results showed that the determined reserve requirement was considerably reduced compared with that obtained with classical approaches. The proposed method also satisfies all the considered constraints and maintains system reliability.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:130:y:2017:i:c:p:258-275
    DOI: 10.1016/j.energy.2017.04.145
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    References listed on IDEAS

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    1. 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.
    2. Goudarzi, Arman & Swanson, Andrew G. & Van Coller, John & Siano, Pierluigi, 2017. "Smart real-time scheduling of generating units in an electricity market considering environmental aspects and physical constraints of generators," Applied Energy, Elsevier, vol. 189(C), pages 667-696.
    3. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "Reserve constrained dynamic optimal power flow subject to valve-point effects, prohibited zones and multi-fuel constraints," Energy, Elsevier, vol. 47(1), pages 451-464.
    4. 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.
    5. Hu, Jianming & Wang, Jianzhou, 2015. "Short-term wind speed prediction using empirical wavelet transform and Gaussian process regression," Energy, Elsevier, vol. 93(P2), pages 1456-1466.
    6. Quan, Hao & Srinivasan, Dipti & Khosravi, Abbas, 2016. "Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study," Energy, Elsevier, vol. 103(C), pages 735-745.
    7. Pousinho, H.M.I. & Silva, H. & Mendes, V.M.F. & Collares-Pereira, M. & Pereira Cabrita, C., 2014. "Self-scheduling for energy and spinning reserve of wind/CSP plants by a MILP approach," Energy, Elsevier, vol. 78(C), pages 524-534.
    8. Frew, Bethany A. & Becker, Sarah & Dvorak, Michael J. & Andresen, Gorm B. & Jacobson, Mark Z., 2016. "Flexibility mechanisms and pathways to a highly renewable US electricity future," Energy, Elsevier, vol. 101(C), pages 65-78.
    9. Kazemi, Mehdi & Siano, Pierluigi & Sarno, Debora & Goudarzi, Arman, 2016. "Evaluating the impact of sub-hourly unit commitment method on spinning reserve in presence of intermittent generators," Energy, Elsevier, vol. 113(C), pages 338-354.
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    1. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).

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