Analytical FRTU deployment approach for reliability improvement of integrated cyber-physical distribution systems

The increasing of distributed generators and high demand of customer service quality of recent years keep challenging the design and operation of electric power distribution systems. The future smart distribution grid is envisioned to be a large complex cyber-physical distribution system (CPDS), whe...

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Vydáno v:IET generation, transmission & distribution Ročník 10; číslo 11; s. 2631 - 2639
Hlavní autoři: Wang, Shouxiang, Liang, Dong, Ge, Leijiao, Wang, Xudong
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 04.08.2016
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ISSN:1751-8687, 1751-8695
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Shrnutí:The increasing of distributed generators and high demand of customer service quality of recent years keep challenging the design and operation of electric power distribution systems. The future smart distribution grid is envisioned to be a large complex cyber-physical distribution system (CPDS), where physical grid components are monitored and controlled based on the interactions on the cyber space. As sensors and controllers, smart feeder remote terminal units (FRTUs) transfer necessary data to the control centre for situational awareness, and receive orders from the control centre for dynamic controlling. This study introduces an analytical FRTU deployment approach for the reliability improvement of integrated CPDSs. The FRTU deployment problem is modelled as a mixed-integer non-linear programming problem, which aims to minimise the total cost with the reliability index of average service available index as the constraint. Two kinds of distribution feeders (overhead and underground) are considered. The total cost includes the life cycle cost of FRTUs in addition to customer interruption cost. The proposed model can be solved by large-scale commercial solvers in an efficient manner. Test results of the RBTS-BUS4 distribution system and a China Southern Power Grid 62-bus distribution system validate the accuracy and effectiveness of the approach. Comparison with the genetic algorithm also shows its great efficiency.
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ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2015.1050