Optimal placement and sizing of FACTS devices based on Autonomous Groups Particle Swarm Optimization technique

• Autorzy: Shehata Ahmed A. , Refaat Ahmed , Ahmed Mamdouh K. , Korovkin Nikolay V.

Identyfikatory

DOI

10.24425/aee.2021.136059

• Języki publikacji: EN

Abstrakty

EN

This paper presents the application of Flexible Alternating Current Transmission System (FACTS) devices based on heuristic algorithms in power systems. The work proposes the Autonomous Groups Particle Swarm Optimization (AGPSO) approach fort he optimal placement and sizing of the Static Var Compensator (SVC) to minimize thetotal active power losses in transmission lines. A comparative study is conducted with other heuristic optimization algorithms such as Particle Swarm Optimization (PSO), Time-varying Acceleration Coefficients PSO (TACPSO), Improved PSO (IPSO), Modified PSO(MPSO), and Moth-Flam Optimization (MFO) algorithms to confirm the efficacy of the proposed algorithm. Computer simulations have been carried out on MATLAB with the MATPOWER additional package to evaluate the performance of the AGPSO algorithm on the IEEE 14 and 30 bus systems. The simulation results show that the proposed algorith moffers the best performance among all algorithms with the lowest active power losses and the highest convergence rate.

Słowa kluczowe

EN

active power losses minimization; AGPSO; FACTS; MFO; PSO; SVC

PL

minimalizacja strat mocy czynnej; AGPSO; FACTS; MFO; PSO

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2021
• Tom: Vol. 70, nr 1
• Strony: 161--172
• Opis fizyczny: Bibliogr. 25 poz., rys., tab., wz.

Twórcy

autor

Shehata Ahmed A.

• Institute of Energy, Peter the Great Saint-Petersburg, Polytechnic University Russia

• https://orcid.org/0000-0003-2032-3395

autor

Refaat Ahmed

• Electrical Engineering Department, Port-Said University, Egypt

• https://orcid.org/0000-0002-4865-9045

autor

Ahmed Mamdouh K.

• Institute of Energy, Peter the Great Saint-Petersburg, Polytechnic University Russia

• https://orcid.org/0000-0002-2877-5196

autor

Korovkin Nikolay V.

• Institute of Energy, Peter the Great Saint-Petersburg, Polytechnic University Russia

• https://orcid.org/0000-0002-1173-8727

Bibliografia

• [1] Vera S.M., Nuez I., Hernandez-Tejera M., A FACTS devices allocation procedure attending to load share, Energies, vol. 13, no. 8 (2020), DOI: 10.3390/en13081976.
• [2] Singh B., Kumar R., A comprehensive survey on enhancement of system performances by using different types of FACTS controllers in power systems with static and realistic load models, Energy Reports, vol. 6, pp. 55–79 (2020).
• [3] Shehata A. A., Ahmed M. K., State estimation accuracy enhancement for optimal power system steady state modes, IOP Conference Series: Materials Science and Engineering, vol. 643 (2019), DOI: 10.1088/1757-899X/643/1/012049.
• [4] Sreedharan S., Joseph T., Joseph S., Chandran C. V., Vishnu J., Das V., Power system loading margin enhancement by optimal STATCOM integration – A case study, Computers and Electrical Engineering, vol. 81, no. 106521 (2019).
• [5] Al Ahmad A., Sirjani R., Optimal placement and sizing of multi-type FACTS devices in power systems using metaheuristic optimisation techniques: An updated review, Ain Shams Engineering Journal(2019), DOI: 10.1016/j.asej.2019.10.013.
• [6] Belazzoug M., Boudour M., Sebaa K., FACTS location and size for reactive power system compensation through the multi-objective optimization, Archives of Control Sciences, vol. 20, no. 4, pp. 473–489(2010).
• [7] Kotsampopoulos P., Georgilakis P., Lagos D. T., Kleftakis V., Hatziargyriou N., FACTS providing grids ervices: applications and testing, Energies, vol. 12, no. 13 (2019), DOI: 10.3390/en12132554.
• 8] Kavitha K., Neela R., Optimal allocation of multi-type FACTS devices and its effect in enhancing system security using BBO, WIPSO & PSO, Journal of Electrical Systems and Information Technology, vol. 5,no. 3, pp. 777–793 (2018).
• [9] Shehata A. A., Korovkin N. V., An accuracy enhancement of optimization techniques containing fractional-polynomial relationships, 2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE), pp. 1–5 (2020).
• [10] Dash S. P., Subhashini K. R., Satapathy J. K., Optimal location and parametric settings of FACTS devices based on JAYA blended moth flame optimization for transmission loss minimization in power systems, Microsystem Technologies, vol. 26, no. 5, pp. 1543–1552 (2020).
• [11] Saurav S., Gupta V. K., Mishra S. K., Moth-flame optimization based algorithm for FACTS devices allocation in a power system, 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), pp. 1–7 (2017).
• [12] Jyotshna D.K., Madhuri N., Optimal allocation of SVC for enhancement of voltage stability using harmony search algorithm, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 4, no. 7, pp. 6693–6701 (2015).
• [13] Ravi K., Rajaram M., Optimal location of FACTS devices using Improved Particle Swarm Optimization, International Journal of Electrical Power and Energy Systems, vol. 49, pp. 333–338 (2013).
• [14] Mathad V. G., Ronad B. G., Jangamshetti S. H., Review on comparison of FACTS controllers for power system stability enhancement, International Journal of Scientific and Research Publications, vol. 3,no. 3, pp. 2250–3153 (2013).
• [15] Murali D., Rajaram M., Reka N.,Comparison of FACTS devices for power system stability enhancement, International Journal of Computer Applications, vol. 8, no. 4, pp. 30–35 (2010).
• [16] Rezaee J. A., Particle swarm optimisation (PSO) for allocation of FACTS devices in electric transmission systems: A review, Renewable and Sustainable Energy Reviews, vol. 52, pp. 1260−1267 (2015).
• [17] Shaheen A. M., Spea S. R., Farrag S. M., Abido M. A., A review of metaheuristic algorithms for reactive power planning problem, Ain Shams Engineering Journal, vol. 9, no. 2, pp. 215–231 (2018).
• [18] Suresh V., Janik P., Jasinski M., Metaheuristic approach to optimal power flow using mixed integer distributed ant colony optimization, Archives of Electrical Engineering, vol. 69, no. 2, pp. 335–348(2020).
• [19] Benchabira A., Khiat M., A hybrid method for the optimal reactive power dispatch and the control of voltages in an electrical energy network, Archives of Electrical Engineering, vol. 68, no. 3, pp. 535–551 (2019).
• [20] Ziyu T., Dingxue Z., A modified particle swarm optimization with an adaptive acceleration coefficient, 2009 Asia-Pacific Conference on Information Processing, vol. 2, pp. 330–332 (2009).
• [21] Mirjalili S., Lewis A., Sadiq A. S., Autonomous particles groups for particle swarm optimization, Arabian Journal for Science and Engineering, vol. 39, no. 6, pp. 4683–4697 (2014).
• [22] The IEEE 14 and 30 Bus Test Systems, available online at: http://labs.ece.uw.edu/pstca.
• [23] Cui Z., Zeng J., Yin Y., An improved PSO with time-varying accelerator coefficients, 2008 8 th International Conference on Intelligent Systems Design and Applications, vol. 2, pp. 638–643 (2008).
• [24] Bao G. Q., Mao K. F., Particle swarm optimization algorithm with asymmetric time varying acceleration coefficients, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), no. 3, pp. 2134–2139 (2009).
• [25] Mirjalili S., Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm, Knowledge-Based Systems, vol. 89, pp. 228–249 (2015).

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).