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      Fast network restoration by partitioning of parallel black start zones

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          Abstract

          The restoration of large electrical power systems after a blackout is often a challenging task. A typical restoration process includes the partitioning of the power systems into subsystems and the successive booting of large non-black start (NBS) units by black start (BS) units. A proper partitioning of the starting zone can reduce the restoration time significantly.

          This paper investigates a novel network partitioning algorithm to improve the restoration time and ratio of generation and load in each subsystem. The proposed algorithm consists of three stages. In the first stage, the number of subsystems is determined by the number of available BS units and their electrical distance. In the second stage, NBS units are assigned to each subsystem in the way that the rebooting time difference among subsystems is minimised. In the third stage, the substations are assigned to one of the subsystems to achieve the optimal ratio of generation and load in each subsystem.

          With the proposed algorithm, the switching transient and steady-state over-voltages at the receiving end of unload lines are kept within acceptable ranges and the self-excitation phenomenon does not occur in the subsystems. Furthermore, the start-up sequence of NBS units in each subsystem is determined simultaneously. The proposed algorithm is flexible and can be adjusted very easily according to the real status of the power system. The validity and performance of the proposed approach is demonstrated through simulations using a New England 39 Nodes network and a real network from south China.

          Most cited references18

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          Development of a Knowledge Based System for Power System Restoration

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            Power system restoration planning

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              From generic restoration actions to specific restoration strategies

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                Author and article information

                Contributors
                Journal
                JOE
                The Journal of Engineering
                J. Eng.
                The Institution of Engineering and Technology
                2051-3305
                August 2017
                19 May 2017
                21 August 2017
                : 2017
                : 8
                : 418-426
                Affiliations
                [1 ] Energy Management and Power System Operation Department, Kassel University , Wilhelmshoeher Allee 73, Kassel, Germany
                [2 ] Faculty for Electrical Engineering, Computer Science and Mathematics University of Paderborn , Warburger Str.100, Paderborn, Germany
                [3 ] Department Distribution System Operation, Fraunhofer IWES , Koenigstor 59, Kassel, Germany
                Article
                JOE.2017.0032 JOE.2017.0032
                10.1049/joe.2017.0032
                ac58eefa-0cb4-40c9-b211-be239cb0d988

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                History
                : 3 February 2017
                : 16 May 2017
                Funding
                Funded by: Deutscher Akademischer Austausch Dienst Kairo
                Award ID: A/12/94526
                Categories
                en-pea

                Computer science,Engineering,Artificial intelligence,Electrical engineering,Mechanical engineering,Renewable energy
                power system partitioning,self-excitation phenomenon,rebooting time difference,switching transients,power generation reliability,network partitioning algorithm,steady-state overvoltage,power system restoration,BS units,switching transient,parallel start zone partitioning,overvoltage,fast network restoration,large electrical power system restoration,south China,NBS units,New England 39 nodes network

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