Corrective action planning using RBF neural network

Authors:
Daya Ram;Laxmi Srivastava;Manjaree Pandit;Jaydev Sharma
Affiliations:
Indian Railways, Bilaspur, India;Electrical Engineering Department, MITS, Gwalior, India;Electrical Engineering Department, MITS, Gwalior, India;Electrical Engineering Department, IIT Roorkee, India
Venue:
Applied Soft Computing
Year:
2007

Citing 2
Cited 4

Alleviation of transmission system overloads using fuzzy reasoning

Fuzzy Sets and Systems - Special issue on applications of fuzzy theory in electronic power systems
Neural Networks in Computer Intelligence

Neural Networks in Computer Intelligence

A Hybrid MPSO-BP-RBFN Model for Reservoir Lateral Prediction

ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
RBF neural network optimized by particle swarm optimization for forecasting urban traffic flow

IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
Radial basis function networks with hybrid learning for system identification with outliers

Applied Soft Computing
Cascade BPN based transmission line overload prediction and preventive action by generation rescheduling

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In recent years, voltage limit violation and power system load-generation imbalance, i.e., line loading limit violation have been responsible for several incidents of major network collapses leading to partial or even complete blackouts. Alleviation of line overloads is the suitable corrective action in this regard. The control action strategies to limit the line loading to the security limits are generation rescheduling/load shedding. In this paper, an approach based on radial basis function neural network (RBFN) is presented for corrective action planning to alleviate line overloading in an efficient manner. Effectiveness of the proposed method is demonstrated for overloading alleviation under different loading/contingency conditions in 6-bus system and 24-bus RTS system.