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Energies 2017, 10(5), 618;

A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks

Power Distribution Department, China Electric Power Research Institute, Beijing 100192, China
Author to whom correspondence should be addressed.
Academic Editor: Ying-Yi Hong
Received: 29 January 2017 / Revised: 25 April 2017 / Accepted: 26 April 2017 / Published: 2 May 2017
(This article belongs to the Special Issue Electric Power Systems Research 2017)
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This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG) allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO). Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA). In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible. View Full-Text
Keywords: distribution network reconfiguration; interval analysis; reliability; data uncertainty distribution network reconfiguration; interval analysis; reliability; data uncertainty

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Liu, K.-Y.; Sheng, W.; Liu, Y.; Meng, X. A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks. Energies 2017, 10, 618.

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