An analytical methodology for assessment of smart monitoring impact on future electric power distribution system reliability. Issue 1 (14th May 2014)

• Record Type: Journal Article
• Authors: Ahadi, Amir; Ghadimi, Noradin; Mirabbasi, Davar
• Is Part Of: Complexity. Volume 21:Issue 1(2015)
• Page Start: 99
• Page End: 113
• Publication Date: 2014-05-14
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1002/cplx.21546
• Languages: English
• ISSNs: 1076-2787

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Smart grid is referred to a modernized power grid which can mitigate fault detection and allow self‐healing of the system without the intervention of operators. This article proposes an innovative analytical formulation using Markov method to evaluate electric power distribution system reliability in smart grids, which incorporates the impact of smart monitoring on the overall system reliability. An accurate reliability model of the main network components and the communication infrastructure have been also considered in the methodology. The proposed approach was applied to a well‐known test bed (Roy Billinton Test System) and various reliability case studies with monitoring provision and monitoring deficiency are analyzed. This article involves the developing possibilities of communication technologies and next‐generation control systems of the entire smart network based on the real‐time monitoring and modern control system to achieve a reliable, economical, safe, and high efficiency of electricity. The implementations indicate that using an appropriate set of the smart grid monitoring devices for power system components can virtually influence all the reliability indices although the amount of improvement varies between techniques. The proposed approach determined that smart monitoring for which components of the electric power distribution systems are tailored and deduce to major economical benefits. The described approach also reveals which reliability indices drastically influenced using monitoring. © 2014 Wiley Periodicals, Inc. Complexity 21: 99–113, 2015</p> </abstract>