Slime Mold Inspired Distribution Network Initial Solution

Verner Püvi, Robert J. Millar, Eero Saarijärvi, Ken Hayami, Tahitoa Arbelot and Matti Lehtonen
Additional contact information
Verner Püvi: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Robert J. Millar: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Eero Saarijärvi: Trimble Solutions, 02130 Espoo, Finland
Ken Hayami: Principles of Informatics Research Division, National Institute of Informatics, Tokyo 101-8430, Japan
Tahitoa Arbelot: Ensimag-National School of Computer Science and Applied Mathematics, Grenoble Institute of Technology, 38402 Saint Martin D’Heres, France
Matti Lehtonen: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland

Energies, 2020, vol. 13, issue 23, 1-17

Abstract: Electricity distribution network optimisation has attracted attention in recent years due to the widespread penetration of distributed generation. A considerable portion of network optimisation algorithms rely on an initial solution that is supposed to bypass the time-consuming steps of optimisation routines. The aim of this paper is to present a nature inspired algorithm for initial network generation. Based on slime mold behaviour, the algorithm can generate a large-scale network in a reasonable computation time. A mathematical formulation and parameter exploration of the slime mold algorithm are presented. Slime mold networks resemble a relaxed minimum spanning tree with better balance between the investment and loss costs of a distribution network. Results indicate lower total costs for suburban and urban networks.

Keywords: distribution network planning; initial network; physarum polycephalum; slime mold (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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