Algorithms of Cause-and-effect Approach to Increase Service Net Efficiency
Alexey Anatolievitch Bezrodny,
Anatoliy Mikchailovitch Korolenok,
Aleksandr Fedorovitch Rezchikov
Issue:
Volume 5, Issue 2, April 2020
Pages:
34-40
Received:
22 July 2019
Accepted:
29 August 2019
Published:
23 March 2020
Abstract: Service nets distribute goods and services that is why their improvement is one of the important tasks of any production chain. There is many models related to the sphere however, in many of them it is possible to see some weaknesses. At the same time since the task mentioned is complicated and large scaled some systematical approach should be applied that needs to be modified taking into consideration presence in the systems objects, processes, events and phenomena of various nature and origin. As possible approach one consideres so called cause-and-effect one that provides a universal description of complex systems and possibility of descision making in undefined or under-defined situations. In the artcile below this approach is considered and informational logic diagrams and algorithms to increase service net efficiency are presented. Gas stations were taken as examples and sphere of practical application, that results are discussed.
Abstract: Service nets distribute goods and services that is why their improvement is one of the important tasks of any production chain. There is many models related to the sphere however, in many of them it is possible to see some weaknesses. At the same time since the task mentioned is complicated and large scaled some systematical approach should be appl...
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A Technique for Electrical Energy Theft Detection and Location in Low Voltage Power Distribution Systems
Olusegun Mayowa Komolafe,
Kingsley Monday Udofia
Issue:
Volume 5, Issue 2, April 2020
Pages:
41-49
Received:
15 March 2020
Accepted:
3 April 2020
Published:
17 April 2020
Abstract: In this work, we present a method for energy theft detection in power distribution networks—a problem in the Nigerian power system and an obstacle to national development—by network analysis. The focus was on radial systems with overhead distribution lines supported on poles. The power distribution network was modelled with typical parameters and consumer loads. In addition, a real network in Ekong Uko Street, Eket, Nigeria was surveyed and the physical structure modelled with simulated consumer and theft loads. The developed program was first initialized under conditions of no theft using the section line parameters and the actual voltage/current at each consumer node as would be reported by a smart tariff meter. The result of the initialization step is a matrix of consumer branch resistances which is stored for later use in the theft detection algorithm. Energy theft detection was achieved by comparing the actual voltages at each pole computed by propagation from all connected consumer nodes using the stored branch resistances. Differences were identified as indicators of theft and were further processed to estimate the power consumed. The result showed a dependence of detection accuracy on location of theft, relative magnitude of theft and network conditions. Minimum power theft that could be detected was between 10 W to 260 W and varied with the theft location. Accuracy in actual power consumed detection of 96% to 100% was obtained. Utility companies will find this work useful in detecting power theft in their secondary power distribution networks to arrest revenue loss.
Abstract: In this work, we present a method for energy theft detection in power distribution networks—a problem in the Nigerian power system and an obstacle to national development—by network analysis. The focus was on radial systems with overhead distribution lines supported on poles. The power distribution network was modelled with typical parameters and c...
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