Electricity distribution clustering and configuration study using KM-MST

Enrico Laoh; Isti Surjandari Prajitno; Arian Dhini

doi:10.1109/ICSITech.2017.8257099

Electricity distribution clustering and configuration study using KM-MST

Enrico Laoh, Isti Surjandari Prajitno, Arian Dhini

Department of Industrial Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

One of the most concerned things on the power system is how to build an optimum distribution configuration. Several techniques are developed in order to get the minimum number of distribution cost and also reduce total loss along the distribution system. Minimizing total cable spanning distance is the best way to achieve those objectives. Minimum spanning tree is appropriate to find the best configuration because of its ability to connect all nodes with minimum cost. The problem is, in this case study, the configuration must be deal with sub-system constrain. To deal with that, this study attempts to build the electricity configuration using KM-MST (K Means-Minimum Spanning Tree). By using KM-MST, the best number of cluster that can be built is 5 clusters with error 0.0958. Furthermore, as the final result, the optimal configuration for each sub-system in the whole system is achieved with total distance cost of 7.11222.

Original language	English
Title of host publication	Proceeding - 2017 3rd International Conference on Science in Information Technology
Subtitle of host publication	Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Editors	Rafal Drezewski, Goutam Chakraborty, Shah Nazir, Lala Septem Riza, Ummi Raba'ah Hashim, Aji Prasetyo Wibawa, Yaya Wihardi, Andri Pranolo, Enjun Junaeti, Shi-Jinn Horng, Heui Seok Lim, Leonel Hernandez
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	138-143
Number of pages	6
ISBN (Electronic)	9781509058662
DOIs	https://doi.org/10.1109/ICSITech.2017.8257099
Publication status	Published - 12 Jan 2018
Event	3rd International Conference on Science in Information Technology, ICSITech 2017 - Bandung, Indonesia Duration: 25 Oct 2017 → 26 Oct 2017

Publication series

Name	Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Volume	2018-January

Conference

Conference	3rd International Conference on Science in Information Technology, ICSITech 2017
Country/Territory	Indonesia
City	Bandung
Period	25/10/17 → 26/10/17

Keywords

clustering
distribution configuration
graph optimization
K-means
minimum spanning tree

Access to Document

10.1109/ICSITech.2017.8257099

Cite this

Laoh, E., Prajitno, I. S., & Dhini, A. (2018). Electricity distribution clustering and configuration study using KM-MST. In R. Drezewski, G. Chakraborty, S. Nazir, L. S. Riza, U. R. Hashim, A. P. Wibawa, Y. Wihardi, A. Pranolo, E. Junaeti, S.-J. Horng, H. S. Lim, & L. Hernandez (Eds.), Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017 (pp. 138-143). (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSITech.2017.8257099

Laoh, Enrico ; Prajitno, Isti Surjandari ; Dhini, Arian. / Electricity distribution clustering and configuration study using KM-MST. Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. editor / Rafal Drezewski ; Goutam Chakraborty ; Shah Nazir ; Lala Septem Riza ; Ummi Raba'ah Hashim ; Aji Prasetyo Wibawa ; Yaya Wihardi ; Andri Pranolo ; Enjun Junaeti ; Shi-Jinn Horng ; Heui Seok Lim ; Leonel Hernandez. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 138-143 (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017).

@inproceedings{a3eb149e6df34b6392788be7f224bbeb,

title = "Electricity distribution clustering and configuration study using KM-MST",

abstract = "One of the most concerned things on the power system is how to build an optimum distribution configuration. Several techniques are developed in order to get the minimum number of distribution cost and also reduce total loss along the distribution system. Minimizing total cable spanning distance is the best way to achieve those objectives. Minimum spanning tree is appropriate to find the best configuration because of its ability to connect all nodes with minimum cost. The problem is, in this case study, the configuration must be deal with sub-system constrain. To deal with that, this study attempts to build the electricity configuration using KM-MST (K Means-Minimum Spanning Tree). By using KM-MST, the best number of cluster that can be built is 5 clusters with error 0.0958. Furthermore, as the final result, the optimal configuration for each sub-system in the whole system is achieved with total distance cost of 7.11222.",

keywords = "clustering, distribution configuration, graph optimization, K-means, minimum spanning tree",

author = "Enrico Laoh and Prajitno, {Isti Surjandari} and Arian Dhini",

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doi = "10.1109/ICSITech.2017.8257099",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "138--143",

editor = "Rafal Drezewski and Goutam Chakraborty and Shah Nazir and Riza, {Lala Septem} and Hashim, {Ummi Raba'ah} and Wibawa, {Aji Prasetyo} and Yaya Wihardi and Andri Pranolo and Enjun Junaeti and Shi-Jinn Horng and Lim, {Heui Seok} and Leonel Hernandez",

booktitle = "Proceeding - 2017 3rd International Conference on Science in Information Technology",

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note = "3rd International Conference on Science in Information Technology, ICSITech 2017 ; Conference date: 25-10-2017 Through 26-10-2017",

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Laoh, E, Prajitno, IS & Dhini, A 2018, Electricity distribution clustering and configuration study using KM-MST. in R Drezewski, G Chakraborty, S Nazir, LS Riza, UR Hashim, AP Wibawa, Y Wihardi, A Pranolo, E Junaeti, S-J Horng, HS Lim & L Hernandez (eds), Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 138-143, 3rd International Conference on Science in Information Technology, ICSITech 2017, Bandung, Indonesia, 25/10/17. https://doi.org/10.1109/ICSITech.2017.8257099

Electricity distribution clustering and configuration study using KM-MST. / Laoh, Enrico; Prajitno, Isti Surjandari ; Dhini, Arian.
Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. ed. / Rafal Drezewski; Goutam Chakraborty; Shah Nazir; Lala Septem Riza; Ummi Raba'ah Hashim; Aji Prasetyo Wibawa; Yaya Wihardi; Andri Pranolo; Enjun Junaeti; Shi-Jinn Horng; Heui Seok Lim; Leonel Hernandez. Institute of Electrical and Electronics Engineers Inc., 2018. p. 138-143 (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Electricity distribution clustering and configuration study using KM-MST

AU - Laoh, Enrico

AU - Prajitno, Isti Surjandari

AU - Dhini, Arian

PY - 2018/1/12

Y1 - 2018/1/12

N2 - One of the most concerned things on the power system is how to build an optimum distribution configuration. Several techniques are developed in order to get the minimum number of distribution cost and also reduce total loss along the distribution system. Minimizing total cable spanning distance is the best way to achieve those objectives. Minimum spanning tree is appropriate to find the best configuration because of its ability to connect all nodes with minimum cost. The problem is, in this case study, the configuration must be deal with sub-system constrain. To deal with that, this study attempts to build the electricity configuration using KM-MST (K Means-Minimum Spanning Tree). By using KM-MST, the best number of cluster that can be built is 5 clusters with error 0.0958. Furthermore, as the final result, the optimal configuration for each sub-system in the whole system is achieved with total distance cost of 7.11222.

AB - One of the most concerned things on the power system is how to build an optimum distribution configuration. Several techniques are developed in order to get the minimum number of distribution cost and also reduce total loss along the distribution system. Minimizing total cable spanning distance is the best way to achieve those objectives. Minimum spanning tree is appropriate to find the best configuration because of its ability to connect all nodes with minimum cost. The problem is, in this case study, the configuration must be deal with sub-system constrain. To deal with that, this study attempts to build the electricity configuration using KM-MST (K Means-Minimum Spanning Tree). By using KM-MST, the best number of cluster that can be built is 5 clusters with error 0.0958. Furthermore, as the final result, the optimal configuration for each sub-system in the whole system is achieved with total distance cost of 7.11222.

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KW - distribution configuration

KW - graph optimization

KW - K-means

KW - minimum spanning tree

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U2 - 10.1109/ICSITech.2017.8257099

DO - 10.1109/ICSITech.2017.8257099

M3 - Conference contribution

T3 - Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017

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BT - Proceeding - 2017 3rd International Conference on Science in Information Technology

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A2 - Wihardi, Yaya

A2 - Pranolo, Andri

A2 - Junaeti, Enjun

A2 - Horng, Shi-Jinn

A2 - Lim, Heui Seok

A2 - Hernandez, Leonel

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Science in Information Technology, ICSITech 2017

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Laoh E, Prajitno IS , Dhini A. Electricity distribution clustering and configuration study using KM-MST. In Drezewski R, Chakraborty G, Nazir S, Riza LS, Hashim UR, Wibawa AP, Wihardi Y, Pranolo A, Junaeti E, Horng SJ, Lim HS, Hernandez L, editors, Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 138-143. (Proceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017). doi: 10.1109/ICSITech.2017.8257099

Electricity distribution clustering and configuration study using KM-MST

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