Abstract
It is shown that the use of controlled shunt reactors enables, based on ultra-high voltage transmission lines, to create a controlled generation of new generation FACTS types that meet the requirements of modern power systems and combinations. Typical modes of operation of the high-voltage power line with installed controlled shunt reactors are analyzed. The efficiency of the use of controlled shunt reactors as measures of transverse compensation in ultrahigh voltage transmission lines is shown. The article shows that due to a smooth change in the consumption of excess reactive power of the transmission line, the normalization of the voltage values is achieved, and, accordingly, the total power losses are reduced. Ref. 9, fig. 3, tables 3.
References
Kundul S., Ghosh T., Maitra K., Acharjee; P. Thakur S.S Optimal Location of SVC Considering Techno-Economic and Environmental Aspect. 2018 ICEPE 2nd International Conference on Power, Energy and Environment: Towards Smart Technology 1-2 June 2018 Shillong, India. Pp. 15–19. DOI: https://doi.org/10.1109/EPETSG.2018.8658729
Tuhay Yu.I., Kuchansky V.V., Tuhay I.Yu. The Using Of Controlled Devices For The Compensation Of Charging Power On Ehv Power Lines In Electric Networks. Tekhnichna Elektrodynamika. 2021. No 1. Pp. 53–56. (Ukr) DOI: https://doi.org/10.15407/techned2021. 01.053
Lezhnyuk P.D., Kulik V.V., Netrebskiy V.V. The principle of the best action in the problems of optimization of power systems. Tekhnichna Elektrodynamika. 2006. No 3. Pp. 35–41.
Lezhnyuk P.D., Kulik V.V., Burykin A.B. Determination and analysis of power losses from transit flows in electrical networks of power systems using the linearization method. Electric networks and systems. 2006. No 1. Pp. 5–11.
Veprik Yu.N. Selecting the optimum installation locations of compensating devices in electric networks. Reporter of the National Technical University Kharkiv Polytechnic Institute. № 41. 2011. Рp. 36–41. (Rus)
Mohamed A. H. E. Artificial neural network for reactive power optimization. Neuromputing. Dec. 1998. Vol. 23. No. 1–3. Pp. 255–263. DOI: https://doi.org/10.1016/S0925-2312(98)00081-2
Lyubchenko V.Y. and Pavlyuchenko D.A. Reacive power and voltage control by genetic algorithm and artificial neural network. International Journal on Technical and Physical Problems of Engineering. Dec. 2009. Vol. 1. No 1. Pp. 23– 26.
Bhattacharya A. and Chattopadhyay P. K.. Solution of optimal reactive power flow using biogeography-based optimization. International Journal of Electrical and Electronics Engineering. 2010.
Liu C., Qin N., Xu Y. and Bak C. L. A hybrid optimization method for reactive power and voltage control considering power loss minimization. IEEE Eindhoven PowerTech. 2015. Pp. 1–6. DOI: https://doi.org/10.1109/PTC.2015.7232745.

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