access icon free Stability analysis of power system with multiple operating conditions considering the stochastic characteristic of wind speed

A new method to analyze the stability of power system with multiple operating conditions considering the stochastic characteristic of wind speed is proposed in this study. First, the parameter Weibull model is used to do fitting prediction of the wind speed variation trend in the short term. Second, the wind speed is divided into different intervals, and the probability density matrix of the conditional featured wind speed in each interval is calculated. Then, the system operating conditions are determined according to the conditional featured wind speed. On this basis, the continuous Markov power system model with multiple operating conditions considering the stochastic characteristic of wind speed is established, and the Lyapunov functional containing the continuous Markov power system model is constructed. Then, by applying the Dynkin Lemma to the weak infinitesimal operators of the functional, the robust stochastic stability linear matrix inequality (LMI) which satisfies the disturbance attenuation degree is derived. Finally, transform the robust stochastic stability LMI to the feasibility problem, so that the stability of power system could be identified. Time-domain simulation tests verify that the proposed method could identify the stability of power system with multiple operating conditions quickly and efficiently.

Inspec keywords: power system stability; linear matrix inequalities; Markov processes; time-domain analysis; Weibull distribution

Other keywords: power system stability analysis; probability density matrix; parameter Weibull model; identification efficiency; power system toolbox; Lyapunov functional; time-domain simulation tests; IEEE 4-machine 11-bus system; Dynkin Lemma; continuous Markov power system model; robust stochastic stability LMI; robust stochastic stability linear matrix inequality; disturbance attenuation degree; wind speed variation; fitting prediction; infinitesimal operators; wind speed stochastic characteristic; IEEE 16-machine 68-bus system

Subjects: Power system control; Algebra; Markov processes

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