Research Methods for Power System Stability Using Adaptive Neural Fuzzy Inference Systems
Phan Xuan Le,
Nguyen Le Thai,
Nguyen Le Minh Tri
Issue:
Volume 3, Issue 6, November 2014
Pages:
101-106
Received:
23 October 2014
Accepted:
4 November 2014
Published:
10 November 2014
DOI:
10.11648/j.epes.20140306.11
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Abstract: The performance of the Automatic Voltage Regulate (AVR) and the Power System Stability (PSS) methods may be degraded stability of the power system. This paper presents an Adaptive Neural Fuzzy Inference Systems (ANFIS) algorithm for stability of the power system, we use an Adaptive Network based Fuzzy Interference System architecture extended to response with multivariable systems. By using a hybrid learning method, the suggested ANFIS can setting structure diagram input - output based on both human knowledge and stipulated input-output data pairs. Simulation results present the convergence of the algorithm is improved.
Abstract: The performance of the Automatic Voltage Regulate (AVR) and the Power System Stability (PSS) methods may be degraded stability of the power system. This paper presents an Adaptive Neural Fuzzy Inference Systems (ANFIS) algorithm for stability of the power system, we use an Adaptive Network based Fuzzy Interference System architecture extended to re...
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Decomposition-Coordination Model and Algorithm for Parallel Calculation of Power System State Estimation Problem
Issue:
Volume 3, Issue 6, November 2014
Pages:
107-118
Received:
16 November 2014
Accepted:
4 December 2014
Published:
8 December 2014
DOI:
10.11648/j.epes.20140306.12
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Abstract: Power system state estimation is the process of computing a reliable estimate of the system state vector composed of bus voltages’ magnitudes and angles from telemetered measurements on the system. This estimate of the state vector provides the description of the system necessary for operation, security monitoring and control. Many methods are described in literature for solving the state estimation problem, the most important of which are the classical weighted least squares and the non-quadratic method. However, both showed drawbacks when it comes to application to large-scale power system networks. In this paper, a new method in the name of decomposition-coordination approach using the weighted least squares is introduced in solving the large-scale power system state estimation problem. The estimation criterion is reformulated; voltage measurement, real and reactive power injections, real and reactive power flows, and real and reactive power flows in tie-line models of a decomposed system are developed. Two level structure of solving the estimation problem is introduced. The first level solves the sub-problem using gradient procedure methods while the second level determines the interconnection variables using predictive method. The positive characteristic of the method is that the coordinator has little work of predicting interconnection variables instead of solving the state estimation problem. The method can be used to solve a multi-area state estimation using parallel or distributed processing architectures.
Abstract: Power system state estimation is the process of computing a reliable estimate of the system state vector composed of bus voltages’ magnitudes and angles from telemetered measurements on the system. This estimate of the state vector provides the description of the system necessary for operation, security monitoring and control. Many methods are desc...
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