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AUTOMATIC RECONFIGURATION OF RADIAL DISTRIBUTION NETWORK FOR RELIABILITY ASSESSMENT USING THE CIRCUIT GRAPH

The problem of optimum restoration after occurrence the outages in a distribution network is an important issue in smart grids. In this kind of networks remote-controlled switches, alternative sources and grid-connected distributed generators (DG) are employed. Therefore, the reliability of the system (corresponding to the frequency of failures and the duration of interruptions) is improved by operating the switches to resupply a part of interrupted system during the repair time. To evaluate the reliability indices in smart grids, neglecting the restoration during the repair time causes the wrong assessment of the network. Thus, considering the rerouting the power during the interruptions seems necessary to calculate the reliability indices. The problem of restoration is formulated as a non-linear integer programming problem with the assistance of the network graph. The circuit graph method is also used to pre-evaluate the feasible interchanging operations to enhance the efficiency of the computations. The topological and operational constraints in this formulation can be found and resolved with the assistance of fundamental cut-set matrix. The optimum restoration schemes is obtained by considering the optimal islanded mode of operation of the DGs which implies maximizing the loading of DGs while not violating their generation capacities. The optimum restoration policies lead us to find the optimum number and location of those manual switches that should be upgraded to the remote-controlled switches. This is a multi-objective problem that contains the contribution of each restoration policy in the reliability improvement and the cost of those switching operations. The proposed algorithm is applied to different standard test systems and the results are compared to the results obtained from other methods and algorithms.

Identiferoai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:dissertations-2576
Date01 August 2018
CreatorsIsapour Chehardeh, Maziar
PublisherOpenSIUC
Source SetsSouthern Illinois University Carbondale
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceDissertations

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