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Energies 2018, 11(2), 310; https://doi.org/10.3390/en11020310

Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering

1
Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Tehran 1983969411, Iran
2
Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Kurdistan 6617715177, Iran
3
Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
4
Faculty of Environmental Management, Prince of Songkla University, Songkhla 90110, Thailand
5
Department of Electrical and Computer Engineering, Curtin University, Perth, WA 6845, Australia
*
Author to whom correspondence should be addressed.
Received: 29 December 2017 / Revised: 22 January 2018 / Accepted: 23 January 2018 / Published: 1 February 2018
(This article belongs to the Section Electrical Power and Energy System)
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Abstract

The ongoing study aims to establish a direct probabilistic load flow (PLF) for the analysis of wind integrated radial distribution systems. Because of the stochastic output power of wind farms, it is very important to find a method which can reduce the calculation burden significantly, without having compromising the accuracy of results. In the proposed approach, a K-means based data clustering algorithm is employed, in which all data points are bunched into desired clusters. In this regard, probable agents are selected to run the PLF algorithm. The clustered data are used to employ the Monte Carlo simulation (MCS) method. In this paper, the analysis is performed in terms of simulation run-time. Also, this research follows a two-fold aim. In the first stage, the superiority of data clustering-based MCS over the unsorted data MCS is demonstrated properly. Moreover, the impact of data clustering-based MCS and unsorted data-based MCS is investigated using an indirect probabilistic forward/backward sweep (PFBS) method. Thus, in the second stage, the simulation run-time comparison is carried out rigorously between the proposed direct PLF and the indirect PFBS method to examine the computational burden effects. Simulation results are exhibited on the IEEE 33-bus and 69-bus radial distribution systems. View Full-Text
Keywords: direct probabilistic load flow; wind-integrated radial distribution systems; K-means based data clustering; Monte Carlo simulation; indirect probabilistic forward/backward sweep load flow direct probabilistic load flow; wind-integrated radial distribution systems; K-means based data clustering; Monte Carlo simulation; indirect probabilistic forward/backward sweep load flow
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Oshnoei, A.; Khezri, R.; Tarafdar Hagh, M.; Techato, K.; Muyeen, S.; Sadeghian, O. Direct Probabilistic Load Flow in Radial Distribution Systems Including Wind Farms: An Approach Based on Data Clustering. Energies 2018, 11, 310.

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