Please use this identifier to cite or link to this item: http://eadnurt.diit.edu.ua/jspui/handle/123456789/11438
Title: Development of Methods for Optimizing Reactive Power Modes Based on Neural Network Technologies
Authors: Sayenko, Yuriy
Sychenko, Viktor
Liubartsev, Vadym
Keywords: forecasting
electrical network
compensating of reactive power
optimization
neural networks
modeling
reactive power
КІСЕ
Issue Date: 2019
Publisher: National Technical University of Ukraine "Igor Sikorsky Kiev Polytechnic Institute", Kiev
Citation: Sayenko, Yu. Development of Methods for Optimizing Reactive Power Modes Based on Neural Network Technologies / Yuriy Sayenko, Victor Sychenko, Vadym Liubartsev // 2019 IEEE 6th International Conference on Energy Smart Systems : conference proceedings, April 17–19, 2019, Kyiv, Ukraine / Igor Sikorsky Kyiv Polytechnic Institute. – Kyiv, 2019. – Р. 98–103. – doi: 10.1109/ESS.2019.8764220.
Abstract: EN: The high cost of electric power, as well as the considerable length and branching of electrical networks, necessitate reduce electric power consumption, and losses in electrical networks. One of solutions of this problem is optimizing the reactive power mode. Reducing the reactive power factor at the point of common coupling (PCC) to the economic level established by the power system is not taking into account that in a complex network, power flows with a non-optimal arrangement of compensating devices and improper determination of their power can reach large values, that resulting in an increase in losses in the network. A program has been developed that implements prediction algorithms using neural networks, as well as optimizing the reactive power mode.
Description: Y. Sayenko: ORCID: 0000-0001-9729-4700; V. Sychenko: ORCID: 0000-0002-9533-2897; V. Liubartsev: ORCID 0000-0003-1243-9101
URI: http://eadnurt.diit.edu.ua/jspui/handle/123456789/11438
Other Identifiers: doi: 10.1109/ESS.2019.8764220
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