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A three-stage scheme for consumers' partitioning using hierarchical clustering algorithm

Nasiakou, Antonia and Alamaniotis, Miltiadis and Tsoukalas, Lefteri H. and Karagiannis, Georgios (2017) 'A three-stage scheme for consumers' partitioning using hierarchical clustering algorithm.', in 2017 8th International Conference on Information, Intelligence, Systems & Applications (IISA). .

Abstract

The clustering of any type of consumers (residential, commercial, industrial) is of great importance in the operation of Smart Grids. In this paper, we propose a three-stage hierarchical scheme for residential consumers' partitioning using the Hierarchical clustering algorithm. The aim of this study is to cluster the consumers in well-separated and compact clusters using information from the near past (almost real time). The usage of electricity from a resident to another varies and this information can be used from the system operator for improving the efficiency of the distribution network. The first stage corresponds to the consumers' clustering of the distribution grid using data driven every three minutes (simulation time) from the meter of each residency. The procedure of the second stage takes part every a specific number of hours, called h, that is defined by the user. The average value of each of the k*20 clusters formed the last h hours is used as input for the hierarchical algorithm. In the third stage and in the end of each h hours, the average value of the data in each cluster is calculated and each consumer is reassigned to the cluster where the a distance metric is minimized. The results of the second stage provide deeper information about the load patterns existing each hour in the distribution grid. This information can be used from suppliers to design the energy tariffs for suiting better to the consumers' needs. This approach is tested using the IEEE-13 test feeder. The data are driven from 56 residencies.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1109/IISA.2017.8316375
Publisher statement:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Date accepted:15 March 2017
Date deposited:18 January 2021
Date of first online publication:15 March 2018
Date first made open access:18 January 2021

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