Power system probabilistic small signal stability analysis using two point estimation method
ABSTRACT A so-called two-point estimation (TPE) method is presented in this paper for power system probabilistic small signal stability (PSSS) analysis. With the development of power systems under open access environment, it is highly desired to investigate power system stability with uncertainties in both system parameters and operating conditions. Monte Carlo simulation (MCS) method has been widely used for this purpose. However, this method is very time-consuming. The TPE based method proposed in this paper provides a way to solve this problem to some extent. It estimate the statistical characteristics of random variables with less calculation requirement while keeping enough calculating precision. The TPE based method for the PSSS analysis is outlined. Then, the model as well as the stable indices for power system PSSS are presented. The effectiveness of the proposed method is verified by the simulation results on a 3- generator-9-node power system.
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ABSTRACT: This paper proposes a probabilistic small signal stability assessment (PSSSA) methodology based on the application of Monte Carlo approach for iterative evaluation, via modal analysis of small signal stability (SSS). Operation states represented by random values of generation and demand are analyzed. A probabilistic instability risk index based on cumulative probability distribution function of damping ratios of oscillatory modes is calculated, as well as a power system stabilizer (PSS) devices location index based on eigenvectors and participation factors, which are considered random variables. Moreover, the impact of long-distance power flows on oscillatory modes (OM) and how the damping of OM depends on the orientation and magnitude of power flows is investigated. Further, an additional index concerns qualitatively the determination of transfer capability as affected by small signal stability. PSSSA is tested on a reduced order model of New England-New York's interconnected system considering uncertainties around three different system conditions separately: highly loaded, fairly loaded, and lowly loaded. The results highlight the main advantages of PSSSA over deterministic SSS studies such as instability risk assessment, small signal stability enhancement through adequate PSS location, and the proposal of possible restrictions for transfer capability in order to avoid poorly damped oscillations in the face of the diversity in power system operation.IEEE Transactions on Power Systems 01/2009; 24:198 - 207. · 2.92 Impact Factor
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ABSTRACT: The probabilistic small signal stability analysis (PSSSA) considering uncertainty and randomness of wind generation is conducted in this paper. Firstly, the small signal model for wind farm with Doubly-fed Induction Generator (DFIG) type is presented. The stator flux-oriented vector control based method is utilized to implement stator active and reactive powers control in modelling rotor-side converter control strategy. Secondly, a probabilistic small signal stability analysis method based on Monte Carlo simulation is introduced to analyze the influence of uncertainties of wind generation. A case study is carried out on the IEEE New England test system to demonstrate the effectiveness and validity of the proposed model and method. Finally, some preliminary conclusions and comments were drawn based on the numerical results.Power and Energy Society General Meeting, 2010 IEEE; 08/2010