Authors:
Alexey L. Rutskov,Viktor L. Burkovsky,Evgeny V. Sidorenko,DOI NO:
https://doi.org/10.26782/jmcms.spl.8/2020.04.00020Keywords:
Optimization of power supply systems,energy efficiency,energy efficiency,distributed objects,fuzzy neural networks,adaptive control systems,Abstract
The article addresses optimization of power supply systems by using fuzzy neural networks to increase the accuracy of operational forecasts and implementactive control systems in the power supply grids. As a practical example, the article considers the optimization of parameters of the 220 kV Yuzhnaya Substation operated by the Regional Dispatching Office of the Voronezh Region Electric Power System (Voronezh, Russia). The obtained results indicate an increase in the energy efficiency of the studied equipment by 4.38% (in terms of real power loss),as compared to the existing control mode, through the use of fuzzy neural controllers that improve the accuracy of forecasts of the relevant technological parameters. The developed solutions can be used in electrical power systems and load nodes as a part of control modules. The economic effect is achieved by taking into account the poorly for malizablefactors and compensating for their impact on real power loss in the transformer equipment.Refference:
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