FOREX Press I. J. of Electrical & Electronics Research
Support Open Access
  • Home/
  • IJEER-110208

Research Article |

Congestion Management of Power Systems by Optimal Allocation of FACTS devices using Hybrid Techniques

Author(s): Dhanadeepika Bosupally1*, Vanithasri Muniyamuthu 2 and Chakravarthy Muktevi3

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 11, Issue 2

Publisher : FOREX Publication

Published : 18 May 2023

e-ISSN : 2347-470X

Page(s) : 299-307

DOI: https://doi.org/10.37391/IJEER.110208

Abstract

For system operators, Congestion management is a difficult task as the market’s security and reliability are protected by this methodology. As the magnitude of an electric transmission system is extremely dynamic, limits must be estimated much beforehand, in order to manage the congestion issues at the right time. Flexible AC transmission systems (FACTS) are used to control voltage fluctuation by adjusting the system's real and reactive power. A combination of Improved Remora Optimization (IRO) and Improved Radial Basis Function (IRBF) is used to allocate positions and sizes of the FACTS devices. In this study, Static Synchronous Compensator (STATCOM), Interlink Power Flow Controllers (IPFC) and Unified Power Flow Controllers (UPFC) are among the FACTS devices used. In the proposed hybrid IRO-IRBF technique, following are the functional aims calculated: build-on-expenditure, Line Loading (LL), Total Voltage Deviation (TVD) and real power loss. Additionally, the hybrid IRO-IRBF technique is used to confirm the proper location using the IEEE 30 bus structure. TVD, power loss, installation costs, and line loading are the measurements used to assess the implementation performance of the hybrid IRO-IRBF approach. From the result analysis, the hybrid IRO-IRBF achieved a real power loss of 0.1591 p.u., and TVD of 0.02 p.u., which is lesser than the existing Whale Optimization Algorithm and Mayfly Optimization Algorithm.

Keywords: Flexible ac transmission systems, improved radial basis function, improved remora optimization, interlink power flow controller,static synchronous compensator, unified power flow controller.




Dhanadeepika Bosupally*, Department of Electrical & Electronics Engineering, Annamalai University, Chidambaram, India; Email: dhanadeepika@gmail.com

Vanithasri Muniyamuthu, Department of Electrical & Electronics Engineering, Annamalai University, Chidambaram, India; Email: vanithasimman@gmail.com

Chakravarthy Muktevi, Department of Electrical & Electronics Engineering, Vasavi College of Engineering, Hyderabad, India; Email: hodeee@staff.vce.ac.in

    [1] Narain, A., Srivastava, S. K., Singh, S. N., 2020. Congestion management approaches in restructured power system: Key issues and challenges. The Electricity Journal, 33(3), 106715. [Cross Ref]
    [2] Mahadevan, J., Rengaraj, R., Bhuvanesh, A., 2021. Application of multi-objective hybrid artificial bee colony with differential evolution algorithm for optimal placement of microprocessor based FACTS controllers. Microprocess. Microsyst., 104239. [Cross Ref]
    [3] Verma, R., Rathore, A., 2021. Optimal placement of facts device considering voltage stability and losses using teaching learning based optimization. J. Inst. Eng. India Ser. B, 102(4), 771–776. [Cross Ref]
    [4] Zarkani, M. K., Tukkee, A. S., Alali, M. J., 2021. Optimal placement of facts devices to reduce power system losses using evolutionary algorithm. Indones. J. Electr. Eng. Comput. Sci, 21(3), 1271–1278. [Cross Ref]
    [5] Nusair, K., Alasali, F., Hayajneh, A., Holderbaum, W., 2021. Optimal placement of FACTS devices and power‐flow solutions for a power network system integrated with stochastic renewable energy resources using new metaheuristic optimization techniques. Int. J. Energy Res., 45(13), 18786–18809. [Cross Ref]
    [6] Parastvand, H., Bass, O., Masoum, M. A., Chapman, A., Lachowicz, S., 2020. Cyber-security constrained placement of FACTS devices in power networks from a novel topological perspective. IEEE Access, 8, 108201–108215. [Cross Ref]
    [7] Kumar, Ch. S. and Tara Kalyani, S. 2022. Power Quality Improvement using Solar Fed Multilevel Inverter Based STATCOM. International Journal of Electrical and Electronics Research (IJEER), 10(4), 1159-1165. [Cross Ref]
    [8] Wartana, I.M., Agustini, N.P., Sreedharan, S., Optimal integration of wind energy with a shunt-FACTS controller for reductions in electrical power loss. Indones. J. Electr. Eng., Comput. Sci 2021, 23(1), 41–53. [Cross Ref]
    [9] Munisekhar, P., Jayakrishna, G., Visali, N. 2022. Strategic Integration of DG and ESS by using Hybrid Multi Objective Optimization with Wind Dissemination in Distribution Network. International Journal of Electrical and Electronics Research (IJEER), 10(4), 1199-1205. [Cross Ref]
    [10] El-Azab, M., Omran, W.A., Mekhamer, S. F., Talaat, H. E, 2020. Allocation of FACTS devices using a probabilistic multi-objective approach incorporating various sources of uncertainty and dynamic line rating. IEEE Access, 8, 167647-167664. [Cross Ref]
    [11] Kumar, A.V.S., Prakash, Aradhya, S. R. S., Swetha, G., 2022. Comprehensive Survey on Recent Trends in Optimization Methods and Different Facts Controllers-Based Power Quality Improvement System. In Sustainable Technology and Advanced Computing in Electrical Engineering, Lecture Notes in Electrical Engineering; Springer: Singapore, 939, 971-985. [Cross Ref]
    [12] Makkar, P., Sikka, S., Malhotra, A. 2022. Optimization of Software Quality Attributes using Evolutionary Algorithm. International Journal of Electrical and Electronics Research (IJEER), 10(2), 131-137. [Cross Ref]
    [13] Chinda, P. R., Rao, R. D., 2022. Multi-attribute decision making approach for placement of Dynaflow controllers in a power system network using particle mobility honey bee algorithm. Ain Shams Eng. J. 13(5), 101682. [Cross Ref]
    [14] Shehata, A. A., Tolba, M. A., El-Rifaie, A.M., Korovkin, N. V., 2022. Power system operation enhancement using a new hybrid methodology for optimal allocation of FACTS devices. Energy Rep. 2022, 8, 217-238. [Cross Ref]
    [15] Ayanlade, S. O., Ogunwole, E. I., Salimon, S. A., Ezekiel, S. O., 2021. Effect of Optimal Placement of Shunt Facts Devices on Transmission Network Using Firefly Algorithm for Voltage Profile Improvement and Loss Minimization. In Advances on Intelligent Informatics and Computing, IRICT, 22-23 December, 385–396. [Cross Ref]
    [16] Singh, D. K., Srivastava, S., Khanna, R. K., Balasubbareddy, M., 2021, Optimal placement of IPFC for solving optimal power flow problems using Hybrid Sine-Cosine Algorithm. Elementary Education Online, 19(4), 3064-3080.
    [17] Nadeem, M., Imran, K., Khattak, A., Ulasyar, A., Pal, A., Zeb, M. Z., Khan, A. N., Padhee, M., 2020. Optimal placement, sizing and coordination of FACTS devices in transmission network using whale optimization algorithm. Energies, 13(3), 753. [Cross Ref]
    [18] Amarendra, A., Srinivas, L. R., Rao, R. S., 2020. Enhance power system security with FACTS devices based on Mayfly Optimization Algorithm. Journal of Current Science and Technology, 12(2), 162-210.
    [19] Sarwar, M., Siddiqui, A. S., 2021, a novel approach for optimal allocation of series FACTS device for transmission line congestion management. Eng. Rep. 3(6), e12342. [Cross Ref]
    [20] Okampo, E. J., Nwulu, N., Bokoro, P. N., 2022, Optimization of Voltage Security with Placement of FACTS Device Using Modified Newton–Raphson Approach: A Case Study of Nigerian Transmission Network. Energies, 15(12), 4211. [Cross Ref]
    [21] Kumar, K.S., Reddy, T.B., Sujatha, P. 2021. Optimal Placement of FACTS for Congestion Management in Deregulated Power System with Water Wave Optimization (WWO) Algorithm. International Journal of Grid and Distributed Computing, 14(1), 922-941.
    [22] Haroon, A., Javed, I. S., Baig, H. R., Nasir, A., Ashraf, A., 2020. Modeling, control and placement of FACTS devices: A review. Mehran University Research Journal of Engineering & Technology, 39(4), 719-733. [Cross Ref]
    [23] Wen, C., Jia, H., Wu, D., Rao, H., Li, S., Liu, Q., Abualigah, L., 2022. Modified remora optimization algorithm with multistrategies for global optimization problem. Mathematics, 10(19), 3604. [Cross Ref]
    [24] Zheng, R., Jia, H., Abualigah, L., Wang, S., Wu, D. 2022, an improved remora optimization algorithm with autonomous foraging mechanism for global optimization problems. Math. Biosci. Eng, 19(4), 3994-4037. [Cross Ref]
    [25] Zhang, D., Zhang, N., Ye, N., Fang, J., Han, X., 2021. Hybrid learning algorithm of radial basis function networks for reliability analysis. IEEE Trans. Reliab., 70(3), 887-900. [Cross Ref]

Dhanadeepika Bosupally, Vanithasri Muniyamuthu and Chakravarthy Muktevi (2023), Congestion Management of Power Systems by Optimal Allocation of FACTS devices using Hybrid Techniques. IJEER 11(2), 299-307. DOI: 10.37391/IJEER.110208.