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Artificial Neural Network (ANN) in Network Reconfiguration for Improvement of Voltage Stability

Artificial Neural Network (ANN) in Network Reconfiguration for Improvement of Voltage Stability
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Author(s): Dipu Sarkar (National Institute of Technology, Nagaland, India)and Joyanta Kumar Roy (MCKV Institute of Engineering, West Bengal, India)
Copyright: 2020
Pages: 25
Source title: Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-0414-7.ch012

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Abstract

Issues related to power system voltage levels have become increasingly important issue during last two and half decades. In power networks, low voltage situations may result in the loss of stability, voltage collapse and eventually to cascading power outages. Large number of incidents of voltage collapse has been reported in different countries across the globe. A simple indicator that has the potential in real time, i.e. L indicator has been used to find voltage profile at different switching condition and simulated using ANN in network reconfiguration for the improvement of voltage stability. A method for improving voltage stability in a power network comprising of multiple lines and switches has been suggested in this chapter based on system reconfiguration approach. ANN based fast and efficient methodology has been developed to obtain the optimum switching combination to achieve best voltage stability. The proposed scheme has been tested on an IEEE 14-bus system.

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