Algorithm of voltage and reactive power regulation based on the particle swarm method

• Autorzy: Alexey Vasilev , Ufa Ruslan

Identyfikatory

DOI

10.15199/48.2020.03.24

Warianty tytułu

PL

Metoda sterowania mocą bierną bzazująca na algorytmach rojowych

• Języki publikacji: EN

Abstrakty

EN

In this paper the results of the development of voltage and reactive power regulation algorithm based on the particle swarm method, optimizing the electric power system mode by the level of losses, are presented. To provide an integration of this algorithm into a real system of an automated dispatching control system, the algorithm is implemented using programs, which are used in the System Operator of the Unified Power System of Russia, as well as standard communication protocols and a software platform. The analysis and comparison of the optimization results obtained by the particle swarm method and standard optimization method (gradient descent method), realized in RastrWin, confirm the correctness and reliability of the obtained results and the developed algorithm. At the same time, the algorithm does not depend on the initial conditions (setpoints), set on the control objects, which allows it to be used to optimize the modes of complex power network, finding the balance in which is a time-consuming task. In the future, it is planned to develop an algorithm for optimizing the mode, taking into account the increased stability of the electric power system.

PL

W artykule przedstawiono metodę sterowania napięciem I moca bierną bazującą na algorytmach rojowych. Algorytm zaadaptowano do rzeczywistych warunków sieci dystrybucyjnej w Rosji. Sprawdzono praće algorytmu badając stabilność I niezawodność systemu. W dalszym etapie planuje się zastosowanie metody do optymalizacji sieci zasilania.

Słowa kluczowe

EN

electric power system; voltage and reactive power regulation; algorithm; particle swarm method

PL

sterowanie mocą bierną; sterowanie napięciem w sieci zasilającej; algorytm genetyczny

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 3
• Strony: 107--110
• Opis fizyczny: Bibliogr. 15 poz., rys., tab.

Twórcy

autor

Alexey Vasilev

• Tomsk Polytechnic University, 30, Lenin Avenue, Tomsk, Russia

autor

Ufa Ruslan

• Tomsk Polytechnic University, 30, Lenin Avenue, Tomsk, Russia

Bibliografia

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• [2] Brenna M., Berardinis E., Carpini L.D., Foiadelli F, Paulon P., Petroni P., Sapienza G., Scrosati G., Zaninelli D. Distributed Voltage Control Algorithm in Smart Grids Applications. IEEE Transactions on Smart Grid, 4 (2013), No. 2, pp. 877 - 885.
• [3] Larki F., Joorabian M., Meshgin Kelk H., Pishvaei M. Voltage Stability Evaluation of The Khouzestan Power System in Iran Using CPF Method and Modal Analysis. Asia-Pacific Power and Energy Engineering Conference, 28-31 March 2010, Chengdu, China, P. 1-5.
• [4] Xue Y., Manjrekar M., Lin C., Tamayo M., Jiang J.N. Voltage stability and sensitivity analysis of grid-connected photovoltaic systems. IEEE Power and Energy Society General Meeting, 24-28 July 2011, Detroit, MI, USA, P. 1-7.
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• [6] Modarresi J., Gholipour E., Khodabakhshian A. A comprehensive review of the voltage stability indices. Renewable and Sustainable Energy Reviews, 63 (2016), pp. 1- 12.
• [7] Farhoodnea M., Mohamed A., Shareef H., Zayandehroodi H. A Comprehensive Review of Optimization Techniques Applied for Placement and Sizing of Custom Power Devices in Distribution Networks. Przeglad Elektrotechniczny, 88 (2012), No. 11, pp. 261-265.
• [8] Gerbex S., Cherkaoui R., Germond A.J. Optimal location of multi type FACTS devices in a power system by means of genetic algorithms. IEEE Trans. On Power Systems, 16 (2001), No.3, pp. 537-544.
• [9] Jiang H., Jia M., Lin L. Adaptive Ant Colony Algorithm based Global Optimization Control of Voltage/Reactive Power in the Substation. Fourth International Conference on Natural Computation, 18-20 Oct. 2008, Jinan, China, pp. 466-470.
• [10] Sreejaya P., Rejitha R. Reactive power and Voltage Control in Kerala Gridand Optimization of Control Variables Using Genetic Algorithm. Joint International Conference on Power System Technology and IEEE Power India Conference, 12-15 Oct. 2008, New Delhi, India, P. 1-4.
• [11] Pavleka J., Nikolovski S., Stojkov M. Finding Optimal Location of FACTS device for dynamic Reactive Power compensation using Genetic Algorithm and Particle Swarm Optimisation (PSO). Przeglad Elektrotechniczny, 95 (2019), No. 8, pp. 86- 91.
• [12] Kennedy J., Eberhart R. Particle Swarm Optimization. Proceedings of IEEE International Conference on Neural Networks IV, 27 Nov.-1 Dec. 1995, Perth, WA, Australia, pp.1942-1948
• [13] Aurasopon A., Takeang Ch. Hybrid Algorithm combining Lambda Iteration and Bee Colony Optimization to Solve an Economic Dispatch Problem with Prohibited Operating Zones. Przeglad Elektrotechniczny, 95 (2019), No. 10, pp. 12-17.
• [14] Babayigit B., Ozdemir R. A modified artificial bee colony algorithm for numerical function optimization. IEEE Symposium on Computers and Communications (ISCC), 1-4 July 2012, Cappadocia, Turkey, pp. 245-249.
• [15] Rastrwin.ru, Software packages RastrWin, Bars, Lincor, Rustab, RastrKZ, RastrMDP, 2018. [Online]. Available: http://www.rastrwin.ru/.[Accessed: 08-Oct-2019].

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).