Introduction to Transient Stability Assessment Using Neural Networks Seminar Topic:

This paper discussed about the artificial neural network and how this approach applies to the transient stability assessment of a power system.  Neural networks were trained by back-propagation technique. Artificial neural networks are useful for computing critical cleaning time and transient energy margin for a machine infinite bus system. TSA using ANN approach always uses a single machine which connected to an infinite bus with a double circuit line. System is stable only if clearing time is greater than the actual fault clearing time otherwise system is considered as unstable. 


Numerical Integration, pattern recognition and second method of Lyapunov are few of the conventional approaches to the transient stability assessment of a power system. Simulation is the process in which transient stability analysis carried out under numerical integration method. In the second method of Lyapunov, stability criterion has replaced the integration off post fall system equation. In pattern recognition method the computational requirements are reduced to minimum by elaborating offline computations. If we using conventional approaches, the task like online stability assessment of a power system with the available techniques is one of the complex or difficult task. All the drawbacks of conventional approaches has overcome by artificial neural network approach applied to the transient stability assessment of a power system.  This technique is capable of producing faster transient stability assessment and also has the potential to meet online requirements by providing the online transient stability assessment.


A fast assessment can be achieved to the transient stability assessment of a machine infinite bus system with the help of neural network approach. Security of the power system can be improved by using neural network approach which in turn develops an on-line dynamic security package for energy management system. Researchers are still carrying out their study about the usage of ANN for TSA of multimachine system by considering all aspects like change in network topology, different loading conditions and fault clearing.

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