Stability Assessment of Stochastic Differential-Algebraic Systems via Lyapunov Exponents with an Application to Power Systems

[EN] In this paper, we discuss stochastic differential-algebraic equations (SDAEs) and the asymptotic stability assessment for such systems via Lyapunov exponents (LEs). We focus on index-1 SDAEs and their reformulation as ordinary stochastic differential equations (SDEs). Via ergodic theory, it is then feasible to analyze the LEs via the random dynamical system generated by the underlying SDEs. Once the existence of well-defined LEs is guaranteed, we proceed to the use of numerical simulation techniques to determine the LEs numerically. Discrete and continuous QR decomposition-based numerical methods are implemented to compute the fundamental solution matrix and to use it in the computation of the LEs. Important computational features of both methods are illustrated via numerical tests. Finally, the methods are applied to two applications from power systems engineering, including the single-machine infinite-bus (SMIB) power system model.A.G.-Z. was supported by Secretaria Nacional de Ciencia y Tecnologia SENESCYT (Ecuador), through the scholarship "Becas de Fomento al Talento Humano", and Deutsche Forschungsgemeinschaft through Collaborative Research Centre Transregio. SFB TRR 154. P.F.-d.-C. was partially supported by grant no. RTI2018-102256-B-I00 (Spain). J.-C.C. acknowledges the support by the Spanish Ministerio de Economia, Industria y Competitividad (MINECO), the Agencia Estatal de Investigacion (AEI), and Fondo Europeo de Desarrollo Regional (FEDER UE) grant MTM2017-89664-P. V.M. was partially supported by Deutsche Forschungsgemeinschaft through the Excellence Cluster Math+ in Berlin, and Priority Program 1984 "Hybride und multimodale Energiesysteme: Systemtheoretische Methoden fur die Transformation und den Betrieb komplexer Netze".González-Zumba, A.; Fernández De Córdoba, P.; Cortés, J.; Mehrmann, V. (2020). Stability Assessment of Stochastic Differential-Algebraic Systems via Lyapunov Exponents with an Application to Power Systems. Mathematics. 8(9):1-26. https://doi.org/10.3390/math8091393S12689Schein, O., & Denk, G. (1998). Numerical solution of stochastic differential-algebraic equations with applications to transient noise simulation of microelectronic circuits. Journal of Computational and Applied Mathematics, 100(1), 77-92. doi:10.1016/s0377-0427(98)00138-1Winkler, R. (2004). Stochastic differential algebraic equations of index 1 and applications in circuit simulation. 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On the Compuation of Lyapunov Exponents for Continuous Dynamical Systems. SIAM Journal on Numerical Analysis, 34(1), 402-423. doi:10.1137/s0036142993247311Talay, D. (1990). Second-order discretization schemes of stochastic differential systems for the computation of the invariant law. Stochastics and Stochastic Reports, 29(1), 13-36. doi:10.1080/17442509008833606Dieci, L., Russell, R. D., & Van Vleck, E. S. (1994). Unitary Integrators and Applications to Continuous Orthonormalization Techniques. SIAM Journal on Numerical Analysis, 31(1), 261-281. doi:10.1137/0731014YU. RYAGIN, M., & RYASHKO, L. B. (2004). THE ANALYSIS OF THE STOCHASTICALLY FORCED PERIODIC ATTRACTORS FOR CHUA’S CIRCUIT. International Journal of Bifurcation and Chaos, 14(11), 3981-3987. doi:10.1142/s0218127404011600Definition and Classification of Power System Stability IEEE/CIGRE Joint Task Force on Stability Terms and Definitions. (2004). IEEE Transactions on Power Systems, 19(3), 1387-1401. doi:10.1109/tpwrs.2004.825981Verdejo, H., Vargas, L., & Kliemann, W. (2012). Stability of linear stochastic systems via Lyapunov exponents and applications to power systems. Applied Mathematics and Computation, 218(22), 11021-11032. doi:10.1016/j.amc.2012.04.063Verdejo, H., Escudero, W., Kliemann, W., Awerkin, A., Becker, C., & Vargas, L. (2016). Impact of wind power generation on a large scale power system using stochastic linear stability. Applied Mathematical Modelling, 40(17-18), 7977-7987. doi:10.1016/j.apm.2016.04.020Wadduwage, D. P., Wu, C. Q., & Annakkage, U. D. (2013). Power system transient stability analysis via the concept of Lyapunov Exponents. Electric Power Systems Research, 104, 183-192. doi:10.1016/j.epsr.2013.06.011Milano, F., & Zarate-Minano, R. (2013). A Systematic Method to Model Power Systems as Stochastic Differential Algebraic Equations. 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Dynamic Modeling and Stability Analysis of Stochastic Multi-Physical Systems Applied to Electric Power Systems

[ES] La naturaleza aleatoria que caracteriza algunos fenómenos en sistemas físicos reales (e.g., ingeniería, biología, economía, finanzas, epidemiología y otros) nos ha planteado el desafío de un cambio de paradigma del modelado matemático y el análisis de sistemas dinámicos, y a tratar los fenómenos aleatorios como variables aleatorias o procesos estocásticos. Este enfoque novedoso ha traído como consecuencia nuevas especificidades que la teoría clásica del modelado y análisis de sistemas dinámicos deterministas no ha podido cubrir. Afortunadamente, maravillosas contribuciones, realizadas sobre todo en el último siglo, desde el campo de las matemáticas por científicos como Kolmogorov, Langevin, Lévy, Itô, Stratonovich, sólo por nombrar algunos; han abierto las puertas para un estudio bien fundamentado de la dinámica de sistemas físicos perturbados por ruido. En la presente tesis se discute el uso de ecuaciones diferenciales algebraicas estocásticas (EDAEs) para el modelado de sistemas multifísicos en red afectados por perturbaciones estocásticas, así como la evaluación de su estabilidad asintótica a través de exponentes de Lyapunov (ELs). El estudio está enfocado en EDAEs d-index-1 y su reformulación como ecuaciones diferenciales estocásticas ordinarias (EDEs). Fundamentados en la teoría ergódica, es factible analizar los ELs a través de sistemas dinámicos aleatorios (SDAs) generados por EDEs subyacentes. Una vez garantizada la existencia de ELs bien definidas, hemos procedido al uso de técnicas de simulación numérica para determinar los ELs numéricamente. Hemos implementado métodos numéricos basados en descomposición QR discreta y continua para el cómputo de la matriz de solución fundamental y su uso en el cálculo de los ELs. Las características numéricas y computacionales más relevantes de ambos métodos se ilustran mediante pruebas numéricas. Toda esta investigación sobre el modelado de sistemas con EDAEs y evaluación de su estabilidad a través de ELs calculados numéricamente, tiene una interesante aplicación en ingeniería. Esta es la evaluación de la estabilidad dinámica de sistemas eléctricos de potencia. En el presente trabajo de investigación, implementamos nuestros métodos numéricos basados en descomposición QR para el test de estabilidad dinámica en dos modelos de sistemas eléctricos de potencia de una-máquina bus-infinito (OMBI) afectados por diferentes perturbaciones ruidosas. El análisis en pequeña-señal evidencia el potencial de las técnicas propuestas en aplicaciones de ingeniería.[CA] La naturalesa aleatòria que caracteritza alguns fenòmens en sistemes físics reals (e.g., enginyeria, biologia, economia, finances, epidemiologia i uns altres) ens ha plantejat el desafiament d'un canvi de paradigma del modelatge matemàtic i l'anàlisi de sistemes dinàmics, i a tractar els fenòmens aleatoris com a variables aleatòries o processos estocàstics. Aquest enfocament nou ha portat com a conseqüència noves especificitats que la teoria clàssica del modelatge i anàlisi de sistemes dinàmics deterministes no ha pogut cobrir. Afortunadament, meravelloses contribucions, realitzades sobretot en l'últim segle, des del camp de les matemàtiques per científics com Kolmogorov, Langevin, Lévy, Itô, Stratonovich, només per nomenar alguns; han obert les portes per a un estudi ben fonamentat de la dinàmica de sistemes físics pertorbats per soroll. En la present tesi es discuteix l'ús d'equacions diferencials algebraiques estocàstiques (EDAEs) per al modelatge de sistemes multifísicos en xarxa afectats per pertorbacions estocàstiques, així com l'avaluació de la seua estabilitat asimptòtica a través d'exponents de Lyapunov (ELs). L'estudi està enfocat en EDAEs d-index-1 i la seua reformulació com a equacions diferencials estocàstiques ordinàries (EDEs). Fonamentats en la teoria ergòdica, és factible analitzar els ELs a través de sistemes dinàmics aleatoris (SDAs) generats per EDEs subjacents. Una vegada garantida l'existència d'ELs ben definides, hem procedit a l'ús de tècniques de simulació numèrica per a determinar els ELs numèricament. Hem implementat mètodes numèrics basats en descomposició QR discreta i contínua per al còmput de la matriu de solució fonamental i el seu ús en el càlcul dels ELs. Les característiques numèriques i computacionals més rellevants de tots dos mètodes s'illustren mitjançant proves numèriques. Tota aquesta investigació sobre el modelatge de sistemes amb EDAEs i avaluació de la seua estabilitat a través d'ELs calculats numèricament, té una interessant aplicació en enginyeria. Aquesta és l'avaluació de l'estabilitat dinàmica de sistemes elèctrics de potència. En el present treball de recerca, implementem els nostres mètodes numèrics basats en descomposició QR per al test d'estabilitat dinàmica en dos models de sistemes elèctrics de potència d'una-màquina bus-infinit (OMBI) afectats per diferents pertorbacions sorolloses. L'anàlisi en xicotet-senyal evidencia el potencial de les tècniques proposades en aplicacions d'enginyeria.[EN] The random nature that characterizes some phenomena in the real-world physical systems (e.g., engineering, biology, economics, finance, epidemiology, and others) has posed the challenge of changing the modeling and analysis paradigm and treat these phenomena as random variables or stochastic processes. Consequently, this novel approach has brought new specificities that the classical theory of modeling and analysis for deterministic dynamical systems cannot cover. Fortunately, stunning contributions made overall in the last century from the mathematics field by scientists such as Kolmogorov, Langevin, Lévy, Itô, Stratonovich, to name a few; have opened avenues for a well-founded study of the dynamics in physical systems perturbed by noise. In the present thesis, we discuss stochastic differential-algebraic equations (SDAEs) for modeling multi-physical network systems under stochastic disturbances, and their asymptotic stability assessment via Lyapunov exponents (LEs). We focus on d-index-1 SDAEs and their reformulation as ordinary stochastic differential equations (SDEs). Supported by the ergodic theory, it is feasible to analyze the LEs via the random dynamical system (RDSs) generated by the underlying SDEs. Once the existence of well-defined LEs is guaranteed, we proceed to the use of numerical simulation techniques to determine the LEs numerically. Discrete and continuous QR decomposition-based numerical methods are implemented to compute the fundamental solution matrix and use it in the computation of the LEs. Important numerical and computational features of both methods are illustrated through numerical tests. All this investigation concerning systems modeling through SDAEs and their stability assessment via computed LEs finds an appealing engineering application in the dynamic stability assessment of power systems. In this research work, we implement our QR-based numerical methods for testing the dynamic stability in two types of single-machine infinite-bus (SMIB) power system models perturbed by different noisy disturbances. The analysis in small-signal evidences the potential of the proposed techniques in engineering applications.Mi agradecimiento al estado ecuatoriano que, a través del Programa de Becas para el Fortalecimiento y Desarrollo del Talento Humano en Ciencia y Tecnología 2012 de la Secretaría Nacional de Educación Superior, Ciencia y Tecnología (SENESCYT), han financiado mis estudios de doctorado.González Zumba, JA. (2020). Dynamic Modeling and Stability Analysis of Stochastic Multi-Physical Systems Applied to Electric Power Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/158558TESI