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

Arman Oshnoei, Rahmat Khezri, Mehrdad Tarafdar Hagh, Kuaanan Techato, Muyeen Sm and Omid Sadeghian
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Arman Oshnoei: Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Tehran 1983969411, Iran
Rahmat Khezri: Department of Electrical and Computer Engineering, University of Kurdistan, Sanandaj, Kurdistan 6617715177, Iran
Mehrdad Tarafdar Hagh: Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran
Kuaanan Techato: Faculty of Environmental Management, Prince of Songkla University, Songkhla 90110, Thailand
Muyeen Sm: Department of Electrical and Computer Engineering, Curtin University, Perth, WA 6845, Australia
Omid Sadeghian: Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 5166616471, Iran

Energies, 2018, vol. 11, issue 2, 1-19

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.

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 (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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