Intelligent distributed smart grid network — Reconfiguration

Ng, Chong Hao, Logenthiran, Thillainathan and Woo, Wai Lok (2016) Intelligent distributed smart grid network — Reconfiguration. In: 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA). IEEE. ISBN 978-1-5090-1238-1

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/ISGT-Asia.2015.7387125

Abstract

Smart grid, modernization of electrical power system that is recognized globally as a vision to achieve a self-automated electrical network that is flexible, accessible, reliable and economical. With the integration of distributed and renewable generation into the transmission network, power system restoration faces new challenges. As the demand for power increases, the ability to perform restoration after any blackouts is vital. Smart grid aims to perform automated action in restoring power back to the transmission network. This feature of the system is also known as self-healing. Self-healing aims to perform self-adjustments during the normal operation state and performs self-restoration to the power system by identifying and reacting to interruption with minimal human intervention. The objective of self-healing is to supply electricity to users with no disturbances, making the system highly dependable and efficient. This paper presents an approach to perform power restoration on a mesh transmission network. In this approach, a knowledge based-environment was first created from performing case studies on a mesh network, a set of rules were developed after the environment and a search technique are than used in responding to the contingency observed and obtaining a restoration solution.

Item Type: Book Section
Uncontrolled Keywords: Smart grid, Self-healing, Reconfiguration, restoration, Rule-based system, Power system network
Subjects: G900 Others in Mathematical and Computing Sciences
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 05 Apr 2019 10:29
Last Modified: 05 Apr 2019 10:29
URI: http://nrl.northumbria.ac.uk/id/eprint/38785

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