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Symmetric AC fuzzy power flow model

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  • Gouveia, Eduardo M.
  • Matos, Manuel A.

Abstract

Power flow calculations are one of the most important computational tools for planning and operating electric power systems. After the stabilization of the deterministic power flow calculation methods, the need to capture uncertainty in load definition lead first to the development of probabilistic models, and later to fuzzy approaches able to deal with qualitative declarations and other non-probabilistic information about the value of the loads. Present fuzzy power flow (FPF) calculations use typically incremental techniques, in order to obtain a good approximation of the fuzzy state variables. However, these models and procedures are not entirely satisfactory for the evaluation of the adequacy of the electric transmission system, since they are not completely symmetric. In this paper, we show how to perform the detailed calculation of the state variables of the FPF problem in an exact and symmetrical way, by means of solving multiple optimization problems. The procedure is illustrated using the IEEE 118 test system.

Suggested Citation

  • Gouveia, Eduardo M. & Matos, Manuel A., 2009. "Symmetric AC fuzzy power flow model," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1012-1018, September.
    • Handle: RePEc:eee:ejores:v:197:y:2009:i:3:p:1012-1018
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    Cited by:

    1. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    2. Sansavini, G. & Piccinelli, R. & Golea, L.R. & Zio, E., 2014. "A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation," Renewable Energy, Elsevier, vol. 64(C), pages 71-81.
    3. Pinheiro, Ricardo B.N.M. & Lage, Guilherme G. & da Costa, Geraldo R.M., 2019. "A primal-dual integrated nonlinear rescaling approach applied to the optimal reactive dispatch problem," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1137-1153.
    4. Zio, Enrico & Aven, Terje, 2011. "Uncertainties in smart grids behavior and modeling: What are the risks and vulnerabilities? How to analyze them?," Energy Policy, Elsevier, vol. 39(10), pages 6308-6320, October.
    5. Soroudi, Alireza & Ehsan, Mehdi, 2011. "A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks--A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 794-800, January.

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