Power System Nonlinear Modal Analysis Using Computationally Reduced Normal Form Method
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Arts et Métiers Institute of Technology, Université de Lille, Centrale Lille, HEI, EA 2697, L2EP—Laboratoire d’Electrotechnique et d’Electronique de Puissance, F-59000 Lille, France
2
Electrical/Electronic Engineering department, AE- FUNAI, P.M.B. 1010, Abakaliki 480214, Nigeria
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Ecole Centrale de Nantes—Laboratoire des Sciences du Numérique de Nantes (LS2N), F-44000 Nantes, France
4
Arts et Metiers Institute of Technology—Laboratoire d’Ingenierie des Systèmes Physiques et Numériques (LISPEN), F-59000 Lille, France
*
Author to whom correspondence should be addressed.
Energies 2020, 13(5), 1249; https://doi.org/10.3390/en13051249
Received: 15 January 2020 / Revised: 2 March 2020 / Accepted: 3 March 2020 / Published: 7 March 2020
(This article belongs to the Special Issue Monitoring and Control of Active Electrical Distribution Grids and Urban Energy Grids)
Increasing nonlinearity in today’s grid challenges the conventional small-signal (modal) analysis (SSA) tools. For instance, the interactions among modes, which are not captured by SSA, may play significant roles in a stressed power system. Consequently, alternative nonlinear modal analysis tools, notably Normal Form (NF) and Modal Series (MS) methods are being explored. However, they are computation-intensive due to numerous polynomial coefficients required. This paper proposes a fast NF technique for power system modal interaction investigation, which uses characteristics of system modes to carefully select relevant terms to be considered in the analysis. The Coefficients related to these terms are selectively computed and the resulting approximate model is computationally reduced compared to the one in which all the coefficients are computed. This leads to a very rapid nonlinear modal analysis of the power systems. The reduced model is used to study interactions of modes in a two-area power system where the tested scenarios give same results as the full model, with about 70% reduction in computation time.
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MDPI and ACS Style
Ugwuanyi, N.S.; Kestelyn, X.; Marinescu, B.; Thomas, O. Power System Nonlinear Modal Analysis Using Computationally Reduced Normal Form Method. Energies 2020, 13, 1249. https://doi.org/10.3390/en13051249
AMA Style
Ugwuanyi NS, Kestelyn X, Marinescu B, Thomas O. Power System Nonlinear Modal Analysis Using Computationally Reduced Normal Form Method. Energies. 2020; 13(5):1249. https://doi.org/10.3390/en13051249
Chicago/Turabian StyleUgwuanyi, Nnaemeka S.; Kestelyn, Xavier; Marinescu, Bogdan; Thomas, Olivier. 2020. "Power System Nonlinear Modal Analysis Using Computationally Reduced Normal Form Method" Energies 13, no. 5: 1249. https://doi.org/10.3390/en13051249
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