This paper proposes an ANN based adaptive damping control scheme for the unified power flow controller (UPFC) to damp the low frequency electromechanical power oscillations. In this paper a novel damping control strategy based on the time‐domain analysis of system transient energy function (TEF) is proposed and implemented by using well tuned conventional PI controllers to obtain the preliminary training data for the design of the proposed controllers. The multi‐layered feed forward neural network with error back‐propagation training algorithm is employed in this study. Models of UPFC and ANN controllers suitable for incorporating with the transient simulation programs are derived and tested on a revised IEEE nine‐bus test system. Comprehensive simulation results demonstrate the great potential of using UPFC in damping control and the excellent performance of the proposed control scheme.
Article navigation
1 September 2000
Technical Paper|
September 01 2000
A robust UPFC damping control scheme using PI and ANN based adaptive controllers
Tsao‐Tsung Ma;
Tsao‐Tsung Ma
Department of Electrical Engineering, National Lien‐Ho Institute of Technology, Miaoli, Taiwan
Search for other works by this author on:
Kwok Lun Lo;
Kwok Lun Lo
Power Systems Research Group, University of Strathclyde, UK, and
Search for other works by this author on:
Mehmet Tumay
Mehmet Tumay
Department of Electrical Engineering, Gaziantep University, Turkey
Search for other works by this author on:
Publisher: Emerald Publishing
Online ISSN: 2054-5606
Print ISSN: 0332-1649
© MCB UP Limited
2000
COMPEL (2000) 19 (3): 878–902.
Citation
Ma T, Lun Lo K, Tumay M (2000), "A robust UPFC damping control scheme using PI and ANN based adaptive controllers". COMPEL, Vol. 19 No. 3 pp. 878–902, doi: https://doi.org/10.1108/03321640010334659
Download citation file:
New and popular articles
Suggested Reading
Immunocomputing: Principles and Applications
Kybernetes (September,2004)
Globalized service providers’ perspective for facility management outsourcing relationships: Artificial neural networks
Management Decision (September,2020)
ANN‐based automatic contingency selection for electric power system
COMPEL (June,2002)
Optimal combinations of face and fusible interlining fabrics
International Journal of Clothing Science and Technology (October,2001)
Artificial neural networks: a tool for understanding green consumer behavior
Marketing Intelligence & Planning (August,2014)
Related Chapters
Artificial Neural Networks (ANN) for Stock Price Prediction: A Financial Machine Learning Analysis
Augmenting Retail Reality, Part B: Blockchain, AR, VR, and AI
A Review of Managing Water Resources in Malaysia with Big Data Approaches
Water Management and Sustainability in Asia
Mapping the Intellectual Structure of Artificial Neural Network Research in Business Domain: A Retrospective Overview Using Bibliometric Review
Exploring the Latest Trends in Management Literature
Recommended for you
These recommendations are informed by your reading behaviors and indicated interests.
