Abstract
UPFC device is discussed in this paper along with their models and functions. Moreover, the suggested and the complementally approaches in the current research study. As a result, the methods are divided into three divisions, which are sensitivity analysis based methods, conventional optimization based methods and artificial intelligence (AI) based methods. In addition, artificial intelligence based methods plays a major role in reducing the search space region. However, to optimize the resulting benefits, the placement, sizing and parameter of UPFC device should be determined. This paper presents and discusses in depth an overall review of the last two decades’ studies, including proposed and comparative methods and strategies, approaches, objective functions, UPFC device tools utilized, limitations, contingency situations and all parameters evaluated and simulated. This paper also provides an analysis of UPFC’s various benefits and uses of power flow studies, such as, power loss mitigation, system load ability improvement, power system security, enhancement of voltage stability, cost of generation and UPFC installation and utilizing specific optimization techniques. Therefore, a more weighted overview of the proposed method is presented focused on artificial intelligence optimization methods.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
Alamelu, S., Baskar, S., Babulal, C.K., and Jeyadevi, S. (2015). Optimal siting and sizing of UPFC using evolutionary algorithms. Int. J. Electr. Power Energy Syst. 69: 222–231, https://doi.org/10.1016/j.ijepes.2014.12.081.Search in Google Scholar
Aminifar, F., Fotuhi-Firuzabad, M., Khodaei, A., and Faried, S.O. (2009). Optimal placement of unified power flow controllers (UPFCs) using mixed-integer non-linear programming (MINLP) method. IEEE Xplore 1: 1–7, https://doi.org/10.1109/PES.2009.5275734.Search in Google Scholar
Balamurugan, K. and Muthukumar, K. (2018). Differential Evolution algorithm for contingency analysis-based optimal location of FACTS controllers in deregulated electricity market. Soft Comput. 23: 163–179, https://doi.org/10.1007/s00500-018-3141-x.Search in Google Scholar
Balamurugan, K., Muralisachithanandam, R., Dharmalingam, V., and Srikanth, R. (2013). Optimal choice and location of multi type facts devices in deregulated electricity market using evolutionary programming method. Int. J. Comput. Syst. Eng. 7: 216–222.Search in Google Scholar
Bruno, S. and LaScala, M. (2004). Unified power flow controllers for security-constrained transmission management. IEEE Trans. Power Syst. 19: 418–426, https://doi.org/10.1109/tpwrs.2003.820694.Search in Google Scholar
Chang, R.W., Kuo, T., and Saha, T.K. (2010). Mixed-integer method for optimal UPFC placement based on line flow-based equations. IEEE Xplore 1: 1–6, https://ieeexplore.ieee.org/document/5710701.Search in Google Scholar
Dwivedi, A.K. and Vadhera, S. (2019). Reactive power sustainability and voltage stability with different FACTS devices using PSAT. IEEE Xplore 6: 248–253, https://doi.org/10.1109/SPIN.2019.8711587.Search in Google Scholar
Eia.gov (2019). EIA – annual energy outlook 2019, Available at: https://www.eia.gov/outlooks/aeo/.Search in Google Scholar
Fadaee, M. and Radzi, M.A.M. (2012). Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: a review. Renew. Sustain. Energy Rev. 16: 3364–3369, https://doi.org/10.1016/j.rser.2012.02.071.Search in Google Scholar
Georgilakis, P.S. and Hatziargyriou, N.D. (2019). Unified power flow controllers in smart power systems: models, methods, and future research. IET Smart Grid 2: 2–10, https://doi.org/10.1049/iet-stg.2018.0065.Search in Google Scholar
Gerbex, S., Cherkaoui, R., and Germond, A.J. (2003). Optimal location of FACTS devices to enhance power system security. In: Power. Tech. Co. Proceedings, 3. IEEE, Bologna, Italy, pp. 61–67.10.1109/PTC.2003.1304363Search in Google Scholar
Ghahremani, E. and Kamwa, I. (2013). Optimal placement of multiple-type FACTS devices to maximize power system loadability using a generic graphical user interface. IEEE Trans. Power Syst. 28: 764–778, https://doi.org/10.1109/tpwrs.2012.2210253.Search in Google Scholar
Ieee.org (2021). Understanding FACTS: concepts and technology of flexible AC transmission systems, Available at: https://ieeexplore.ieee.org/book/5264253.Search in Google Scholar
Inkollu, S.R. and Kota, V.R. (2016). Optimal setting of FACTS devices for voltage stability improvement using PSO adaptive GSA hybrid algorithm. Eng. Sci. Technol. Int. J. 19: 1166–1176, https://doi.org/10.1016/j.jestch.2016.01.011.Search in Google Scholar
Jamal, A. and Syahputra, R. (2013). UPFC based on adaptive neuro-fuzzy for power flow control of multimachine power systems. Int. J. Eng. Sci. Invent. 2: 5–14.Search in Google Scholar
Jordehi, A.R. (2015). Optimisation of electric distribution systems: a review. Renew. Sustain. Energy Rev. 51: 1088–1100, https://doi.org/10.1016/j.rser.2015.07.004.Search in Google Scholar
Kalair, A., Abas, N., Kalair, A.R., Saleem, Z., and Khan, N. (2017). Review of harmonic analysis, modeling and mitigation techniques. Renew. Sustain. Energy Rev. 78: 1152–1187, https://doi.org/10.1016/j.rser.2017.04.121.Search in Google Scholar
Kalyani, R.P., Crow, M.L., and Tauritz, D.R. (2006). Optimal placement and control of unified power flow control devices using evolutionary computing and sequential quadratic programming. IEEE Xplore 178: 959–964, https://doi.org/10.1109/PSCE.2006.296442.Search in Google Scholar
Kamal, S., Sayeed, F., Ahanger, T.A., Subbalakshmi, C., Kalidoss, R., Singh, N., and Nuagah, S.J. (2022). Particle Swarm optimization and modular multilevel converter communication in electrical applications with machine learning algorithm. Comput. Intell. Neurosci. 2022: e8516928, https://doi.org/10.1155/2022/8516928.Search in Google Scholar PubMed PubMed Central
Kang, T., Yao, J., Duong, T., Yang, S., and Zhu, X. (2017). A hybrid approach for power system security enhancement via optimal installation of flexible AC transmission system (FACTS) devices. Energies 10: 1305, https://doi.org/10.3390/en10091305.Search in Google Scholar
Kavitha, K. and Neela, R. (2018). Optimal allocation of multi-type FACTS devices and its effect in enhancing system security using BBO, WIPSO & PSO. J. Electric. Syst. Inf. Technol. 5: 777–793, https://doi.org/10.1016/j.jesit.2017.01.008.Search in Google Scholar
Kazemi, A., Parizad, A., and Baghaee, H.R. (2009). On the use of harmony search algorithm in optimal placement of facts devices to improve power system security. IEEE. EUROCON 9: 70–576, https://doi.org/10.1109/EURCON.2009.5167689.Search in Google Scholar
Kowsalya, M., Ray, K.K., and Kothari, D.P. (2009). Loss optimization for voltage stability enhancement incorporating UPFC using particle swarm optimization. J. Electric. Eng. Technol. 4: 492–498, https://doi.org/10.5370/jeet.2009.4.4.492.Search in Google Scholar
Kumar, B.V. and Srikanth, N.V. (2017). A hybrid approach for optimal location and capacity of UPFC to improve the dynamic stability of the power system. Appl. Soft Comput. 52: 974–986, https://doi.org/10.1016/j.asoc.2016.09.031.Search in Google Scholar
Leung, H.C. and Lu, D.D.-C. (2011). Particle swarm optimization for OPF with consideration of FACTS devices. IEEE Xplore 11: 2406–2410, https://doi.org/10.1109/IECON.2011.6119686.Search in Google Scholar
Lim, J.-U. and Moon, S.I. (2002). The power flow control of UPFC for cost minimization. KIEE Intern. Trans. Power Eng. 12A: 31–35.Search in Google Scholar
Lucio, I., Antonio La, C., and Michele, P. (2006). Optimal allocation of FACTS devices by using multi-objective optimal power flow and genetic algorithms. Int. J. Emerg. Elec. Power Syst. 7: 1–19, https://doi.org/10.2202/1553-779X.1099.Search in Google Scholar
Made Wartana, I., Singh, J.G., Ongsakul, W., Buayai, K., and Sreedharan, S. (2011). Optimal placement of UPFC for maximizing system loadability and minimize active power losses by NSGA-II. In: IEEE Xplore. International conference and utility exhibition on power and energy systems: issues and prospects of Asia. IEEE, Pattaya, Thailand, pp. 1–8.10.1109/ICUEPES.2011.6497710Search in Google Scholar
Mori, H. and Goto, Y. (2000). A parallel tabu search based method for determining optimal allocation of FACTS in power systems. IEEE Xplore 2: 1077–1082, https://doi.org/10.1109/ICPST.2000.897170.Search in Google Scholar
Mori, H. and Maeda, Y. (2006). Application of two-layered tabu search to optimal allocation of UPFC for maximizing transmission capability. IEEE Xplore 2: 1699–1702, https://doi.org/10.1109/ISCAS.2006.1692931.Search in Google Scholar
Nasser, A. and Adnan, H. (2018). A literature review on the unified power flow controller UPFC. Int. J. Comput. Appl. 182: 23–29, https://doi.org/10.5120/IJCA2018917775.Search in Google Scholar
Naveen Kumar, G. and Surya Kalavathi, M. (2014). Cat Swarm optimization for optimal placement of multiple UPFC’s in voltage stability enhancement under contingency. Int. J. Electr. Power Energy Syst. 57: 97–104, https://doi.org/10.1016/j.ijepes.2013.11.050.Search in Google Scholar
Ongsakul, W. and Jirapong, P. (2005). Optimal allocation of FACTS devices to enhance total transfer capability using evolutionary programming. IEEE. Inter. Symp. Circuits. Syst. 5: 4175–4178, https://doi.org/10.1109/ISCAS.2005.1465551.Search in Google Scholar
Parizad, A., Khazali, A., and Kalantar, M. (2009). Application of HSA and GA in optimal placement of FACTS devices considering voltage stability and losses. EPECS. IEEE Xplore 1: 1–7, https://ieeexplore.ieee.org/document/5415693.Search in Google Scholar
Rajderkar, V.P. and Chandrakar, Vinod.K. (2021). Allocation of Unified Power Flow Controller (UPFC) through sensitivity approach for enhancing the system performance. IEEE Xplore 6: 1–4, https://doi.org/10.1109/I2CT51068.2021.9417915.Search in Google Scholar
Rashed, G.I., Sun, Y., Rashed, K.A., and Shaheen, H.I. (2012). Optimal location of unified power flow controller by differential evolution algorithm considering transmission loss reduction. In: IEEE international con. on power system technoloy (POWERCON), 1. IEEE, Auckland, New Zealand, pp. 1–6.10.1109/PowerCon.2012.6401297Search in Google Scholar
Saiveerraju, M., and Ram, B. (2009). DE based optimal power flow for location of UPFC considering voltage stability, Available at: https://www.semanticscholar.org/paper/DE-Based-Optimal-Power-Flow-for-Location-of-UPFCSaiveerrajuRam/37d79189247be9e33d798794550105be1df661c6.Search in Google Scholar
Saravanan, M., Slochanal, S.M.R., Venkatesh, P., and Abraham, J.P.S. (2007). Application of particle swarm optimization technique for optimal location of FACTS devices considering cost of installation and system loadability. Elec. Power Syst. Res. 77: 276–283, https://doi.org/10.1016/j.epsr.2006.03.006.Search in Google Scholar
Shaheen, H.I., Rashed, G.I., and Cheng, S.J. (2007a). Application of evolutionary optimization techniques for optimal location and parameters setting of multiple UPFC devices. In: IEEE Xplore. Third international conference on natural computation. ICNC. 4: pp. 688–697.10.1109/ICNC.2007.251Search in Google Scholar
Shaheen, H.I., Rashed, G.I., and Cheng, S.J. (2007b). Optimal location and parameters setting of unified power flow controller based on evolutionary optimization techniques. IEEE Xplore 6: 1–8. https://doi.org/10.1109/PES.2007.385581.Search in Google Scholar
Singh, J.G., Singh, S.N., and Srivastava, S.C. (2007). Enhancement of power system security through optimal placement of TCSC and UPFC. IEEE Xplore 6: 1–6, https://doi.org/10.1109/PES.2007.385939.Search in Google Scholar
Singh, S.N. and Erlich, I. (2005). Locating unified power flow controller for enhancing power system loadability. IEEE Xplore 1: 1–5, https://doi.org/10.1109/FPS.2005.204219.Search in Google Scholar
Taher, S.A. and Amooshahi, M.K. (2012). New approach for optimal UPFC placement using hybrid immune algorithm in electric power systems. Int. J. Electr. Power Energy Syst. 43: 899–909, https://doi.org/10.1016/j.ijepes.2012.05.064.Search in Google Scholar
Taher, S.A. and Karim Amooshahi, M. (2011). Optimal placement of UPFC in power systems using immune algorithm. Simulat. Model. Pract. Theor. 19: 1399–1412, https://doi.org/10.1016/j.simpat.2011.03.001.Search in Google Scholar
Tokachichu, J. and Gaddam, T.R.D. (2022). Performance analysis of a transmission line connected with UPFC designed with three level cascaded H bridge inverter with generalized SVM technique using PI, FUZZY LOGIC, ANN and ANFIS controllers. Mater. Today Proc. 51: 1243–1251, https://doi.org/10.1016/j.matpr.2021.07.338.Search in Google Scholar
Wang, D. and Cai, K. (2017). Multi-objective crashworthiness optimization of vehicle body using particle swarm algorithm coupled with bacterial foraging algorithm. Proc. Inst. Mech. Eng. – Part D J. Automob. Eng. 232: 1003–1018, https://doi.org/10.1177/0954407017724636.Search in Google Scholar
Zhang, X.P., Handschin, E., and Yao, M. (2001). Modeling of the generalized unified power flow controller (GUPFC) in a nonlinear interior point OPF. IEEE Power Eng. Rev. 21: 57, https://doi.org/10.1109/MPER.2001.4311541.Search in Google Scholar
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