Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/101973
Title: The use of Petri computing networks for optimization of the structure of distribution networks to minimize power losses
Authors: Asanov, M.
Kokin, S.
Asanova, S.
Satarkulov, K.
Dmitriev, S.
Safaraliev, M.
Issue Date: 2020
Publisher: Elsevier Ltd
Citation: The use of Petri computing networks for optimization of the structure of distribution networks to minimize power losses / M. Asanov, S. Kokin, S. Asanova, et al. — DOI 10.1016/j.egyr.2020.11.024 // Energy Reports. — 2020. — Vol. 6. — P. 1337-1343.
Abstract: The paper suggests a self-organizing multi-component computational algorithm as a solution to the problem of optimizing the structure of distribution electrical networks to minimize the loss of power. The suggested algorithm is consistent with the method of branches and borders and uses the apparatus of the Petri computer networks (PCN) apparatus. The PCN apparatus has a universal computational capability to process symbolic-numeric data, which along with the solution of calculating problems, provides for the structural and logical analysis of the systems and processes under study. The structure of the PCN based algorithm is similar to the studied system, which provides for better visualization and convenience of interpretation, modification, and implementation of this algorithm on one or more computers by paralleling computational processes for better system performance. Computing modules within the general text of the algorithm can be arranged in any given order and solve the problem by organizing themselves in the process of functioning. © 2020
Keywords: ALGORITHM
COMPUTATIONAL MODULES
DISTRIBUTION ELECTRICAL NETWORKS
GRAPH
LOSS OF ELECTRICITY
OPTIMIZATION OF NETWORK STRUCTURE
PETRI NETWORKS
ENERGY MANAGEMENT
ENERGY RESOURCES
COMPUTATIONAL ALGORITHM
COMPUTATIONAL CAPABILITY
COMPUTATIONAL PROCESS
ELECTRICAL NETWORKS
LOGICAL ANALYSIS
MULTICOMPONENTS
SYMBOLIC NUMERICS
SYSTEMS AND PROCESS
STRUCTURAL OPTIMIZATION
URI: http://hdl.handle.net/10995/101973
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 85098205345
PURE ID: 20413379
3f07a838-ad17-4987-864f-a47ac2e4bf23
ISSN: 23524847
DOI: 10.1016/j.egyr.2020.11.024
metadata.dc.description.sponsorship: The reported research was partly funded by Russian Foundation for Basic Research and the government of the Yamal region of the Russian Federation , grant No. 19-48-890001.
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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