Management of Voltage Profile and Minimization of Power Losses in a Distribution Network with Embedded Wind Energy Conversion System using GOA-Tuned SMES Unit
DOI:
https://doi.org/10.54536/ajise.v4i3.5889Keywords:
Current Source Converter-Superconducting Magnetic Energy Storage Unit, Distribution Network, Double Fed Induction Generator, Grasshopper Optimization AlgorithmAbstract
Distribution networks are prone to voltage fluctuations and power losses due to line impedances, variable renewable energy generation, network configuration, and sudden changes in load. Superconducting Magnetic Energy Storage (SMES) unit has demonstrated capability to tackle these problems. This paper investigates a Grasshopper Optimization Algorithm (GOA) tuned Current Source Converter (CSC)-SMES in a distribution network with an embedded Wind Energy Conversion System (WECS) to manage voltage profiles and minimize power losses. The system was modeled in MATLAB/Simulink and tested under incremental load increases in a state of discharge condition. Comparative analysis between a conventional PI controlled SMES and a GOA-tuned SMES revealed superior performance with optimization based tuning. For a 15% load increase, the conventional controller (Kp= 1.47 Ki= 0.76) yielded a Voltage Profile Improvement Index (VPII) of 1.011, real power loss of 0.264 p.u., and reactive power loss of 0.211 p.u. The GOA-tuned controller (Kp= 1.66, Ki = 0.95) achieved a VPII of 1.014, reducing real and reactive power losses to 0.257 p.u. and 0.204 p.u., respectively, corresponding to 2.15% and 4.16% improvements. The results confirm that GOA tuned SMES controller performance, providing improved voltage stability and reduced losses in distribution networks integrated with wind energy source.
Downloads
References
Abad, G., Lopez, J., Rodrıguez, M., Marroyo, L., & Iwanski, G. (2011). Doubly fed induction modeling and control. 633.
Abdalkareem Jasim, S., Mireya Romero Parra, R., Salam Karim, Y., Mahdi, A. B., Jade Catalan Opulencia, M., Fakhriddinovich Uktamov, K., & Thaeer Hammid, A. (2022). Optimization of doubly-fed induction generator (DFIG) based wind turbine to achieve maximum power generation with imperialist competitive algorithm (ICA). Science Progress, 105(3). https://doi.org/10.1177/00368504221113193
Abdelbadie, H. T., Taha, A. T., Hasanien, H. M., Turky, R. A., & Muyeen, S. M. (2022). Stability enhancement of wind energy conversion systems based on optimal superconducting magnetic energy storage systems using the Archimedes optimization algorithm. Processes, 10(2), 366. https://doi.org/10.3390/pr10020366
Abualigah, L., & Diabat, A. (2020). A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications. Neural Computing and Applications, 32(19), 15533–15556. https://doi.org/10.1007/s00521-020-04789-8
Adetokun, B. B., Oghorada, O., & Abubakar, S. J. afar. (2022). Superconducting magnetic energy storage systems: Prospects and challenges for renewable energy applications. Journal of Energy Storage, 55(PC), 105663. https://doi.org/10.1016/j.est.2022.105663
Ali, M. H., Murata, T., & Tamura, J. (2008). Transient stability enhancement by fuzzy logic-controlled SMES considering coordination with optimal reclosing of circuit breakers. IEEE Transactions on Power Systems, 23(2), 631–640. https://doi.org/10.1109/TPWRS.2008.920045
Aly, M. M., Salama, H. S., & Abdel-Akher, M. (2017). Power control of fluctuating wind/PV generations in an isolated Microgrid based on superconducting magnetic energy storage. 2016 18th International Middle-East Power Systems Conference, MEPCON 2016 - Proceedings, 1, 419–424. https://doi.org/10.1109/MEPCON.2016.7836925
Borozan, V., Baran, M. E., & Novosel, D. (2001). Integrated Volt/Var control in distribution systems. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, 3(WINTER MEETING), 1485–1490. https://doi.org/10.1109/pesw.2001.917328
Buckles, W., & Hassenzahl, W. V. (2000). Superconducting magnetic energy storage. IEEE Power Engineering Review, 20(5), 16–20. https://doi.org/10.1109/39.841345
Burke, M. J., & Stephens, J. C. (2018). Political power and renewable energy futures: A critical review. Energy Research and Social Science, 35(November), 78–93. https://doi.org/10.1016/j.erss.2017.10.018
Calderaro, V., Conio, G., Galdi, V., Massa, G., & Piccolo, A. (2014). Optimal decentralized voltage control for distribution systems with inverter-based distributed generators. IEEE Transactions on Power Systems, 29(1), 230–241. https://doi.org/10.1109/TPWRS.2013.2280276
Chaychizadeh, F., Dehghandorost, H., Aliabadi, A., & Taklifi, A. (2018). Stochastic dynamic simulation of a novel hybrid thermal-compressed carbon dioxide energy storage system (T-CCES) integrated with a wind farm. Energy Conversion and Management, 166, 500–511. https://doi.org/10.1016/J.ENCONMAN.2018.04.050
El Moursi, M. S., Zeineldin, H. H., Kirtley, J. L., & Alobeidli, K. (2014). A dynamic master/slave reactive power-management scheme for smart grids with distributed generation. IEEE Transactions on Power Delivery, 29(3), 1157–1167. https://doi.org/10.1109/TPWRD.2013.2294793
Gade, V. C., & Kotapuri, M. R. (2018). A Three Phase Matlab Simulink Model of IEEE 57 Bus Power System Network. International Journal of Engineering & Technology, 7(4.24), 142. https://doi.org/10.14419/ijet.v7i4.24.21875
Handayani, L., Abu-Siada, A., Suwarno, S., Hariyanto, N., & Djalal, M. R. (2020). Power system performance enhancement using superconducting magnetic energy storage unit and proportional integral derivative control. 2020 2nd International Conference on Smart Power and Internet Energy Systems, SPIES 2020, 281–286. https://doi.org/10.1109/SPIES48661.2020.9242922
Haque, M. T., & Najafi, S. (2005). Application of neuro-fuzzy dynamic programming to improve the reactive power and voltage profile of a distribution substation. Proceedings - Wec 05: Fourth World Enformatika Conference, 6(6), 126–129.
Hasanien, H. M., & Muyeen, S. M. (2015). Particle swarm optimization-based superconducting magnetic energy storage for low-voltage ride-through capability enhancement in wind energy conversion system. Electric Power Components and Systems, 43(11), 1278–1288. https://doi.org/10.1080/15325008.2015.1027017
Kumar, P. P., Nuvvula, R. S. S., & Manoj, V. (2022). Grass Hopper Optimization Algorithm for Off-Grid Rural Electrification of an Integrated Renewable Energy System. E3S Web of Conferences, 350, 02008. https://doi.org/10.1051/e3sconf/202235002008
Liu, F., Mei, S., Xia, D., Ma, Y., Jiang, X., & Lu, Q. (2004). Experimental evaluation of nonlinear robust control for SMES to improve the transient stability of power systems. IEEE Transactions on Energy Conversion, 19(4), 774–782. https://doi.org/10.1109/TEC.2004.827703
Luo, Wang, J., & Krupke, C. (2014). Overview of Current Development in Compressed Air Energy Storage Technology. Energy Procedia, 62, 603–611. https://doi.org/10.1016/j.egypro.2014.12.423
Mahlia, T. M. I., Saktisahdan, T. J., Jannifar, A., Hasan, M. H., & Matseelar, H. S. C. (2014). A review of available methods and development on energy storage; Technology update. Renewable and Sustainable Energy Reviews, 33(May), 532–545. https://doi.org/10.1016/j.rser.2014.01.068
Meraihi, Y., Gabis, A. B., Mirjalili, S., & Ramdane-Cherif, A. (2021). Grasshopper optimization algorithm: Theory, variants, and applications. IEEE Access, 9, 50001–50024. https://doi.org/10.1109/ACCESS.2021.3067597
Mirjalili, S. Z., Mirjalili, S., Saremi, S., Faris, H., & Aljarah, I. (2018). Grasshopper optimization algorithm for multi-objective optimization problems. Applied Intelligence, 48(4), 805–820. https://doi.org/10.1007/s10489-017-1019-8
Muisyo, I. N., Muriithi, C. M., & Kamau, S. I. (2022). Enhancing low voltage ride through capability of grid connected DFIG based WECS using WCA-PSO tuned STATCOM controller. Heliyon, 8(8), e09999. https://doi.org/10.1016/j.heliyon.2022.e09999
Mukherjee, P., & Rao, V. V. (2019). Superconducting magnetic energy storage for stabilizing grid integrated with wind power generation systems. Journal of Modern Power Systems and Clean Energy, 7(2), 400–411. https://doi.org/10.1007/s40565-018-0460-y
Nielsen, K. E., & Molinas, M. (2010). Superconducting Magnetic Energy Storage (SMES) in power systems with renewable energy sources. IEEE International Symposium on Industrial Electronics, 2487–2492. https://doi.org/10.1109/ISIE.2010.5637892
Paserba, J., Electric, M., Products, P., & Miller, N. W. (2017). Coordination of a distribution level continuously controlled compensation device with existing substation equipment for long term VAR management. October. https://doi.org/10.1109/61.296288
Petropoulos, A. D., Koutsoukis, N. C., Karapidakis, E. S., & Georgilakis, P. S. (2014). Optimal mix of wind generation and energy storage systems in power distribution networks. IET Conference Publications, 2014(CP665). https://doi.org/10.1049/CP.2014.1640
Qais, M. H., Hasanien, H. M., & Alghuwainem, S. (2020). Output power smoothing of wind power plants using self-tuned controlled SMES units. Electric Power Systems Research, 178(August 2019), 106056. https://doi.org/10.1016/j.epsr.2019.106056
Sadiq, R., Wang, Z., Chung, C. Y., Zhou, C., & Wang, C. (2021). A review of STATCOM control for stability enhancement of power systems with wind/PV penetration: Existing research and future scope. International Transactions on Electrical Energy Systems, 31(11), 1–27. https://doi.org/10.1002/2050-7038.13079
Said, S., Aly, M., & Hartmann, B. (2019). A robust SMES control for enhancing stability of distribution systems fed from intermittent wind power generation. Turkish Journal of Electrical Engineering and Computer Sciences, 27(5), 3883–3898. https://doi.org/10.3906/elk-1810-10
Said, S. M., Selim, A., & Hartmann, B. (2018). Enhancement of Voltage profile for Unbalanced Distribution System with Wind Energy and Superconducting Magnetic Energy Storage. 289–295.
Sajjad, F., Rashid, M., Zafar, A., Zafar, K., Fida, B., Arshad, A., Riaz, S., Dutta, A. K., & Rodrigues, J. J. P. C. (2023). An efficient hybrid approach for optimization using simulated annealing and grasshopper algorithm for IoT applications. Discover Internet of Things, 3(1). https://doi.org/10.1007/s43926-023-00036-3
Sannigrahi, S., Ghatak, S. R., Basu, D., & Acharjee, P. (2019). Optimal placement of DSTATCOM, DG and their performance analysis in deregulated power system. International Journal of Power and Energy Conversion, 10(1), 105–128. https://doi.org/10.1504/IJPEC.2019.096725
Saremi, S., Mirjalili, S., & Lewis, A. (2017). Grasshopper Optimisation Algorithm: Theory and application. Advances in Engineering Software, 105, 30–47. https://doi.org/10.1016/j.advengsoft.2017.01.004
Shi, J., Tang, Y. J., Ren, L., Li, J. D., & Chen, S. J. (2008). Application of SMES in wind farm to improve voltage stability. Physica C: Superconductivity and Its Applications, 468(15–20), 2100–2103. https://doi.org/10.1016/j.physc.2008.05.135
Su, C. L. (2010). Stochastic evaluation of voltages in distribution networks with distributed generation using detailed distribution operation models. IEEE Transactions on Power Systems, 25(2), 786–795. https://doi.org/10.1109/TPWRS.2009.2034968
Sulaeman, S., Alharbi, F. T., Benidris, M., & Mitra, J. (2017). A new method to evaluate the optimal penetration level of wind power. 2017 North American Power Symposium, NAPS 2017. https://doi.org/10.1109/NAPS.2017.8107332
Wang, J., Fu, C., & Zhang, Y. (2008). SVC control system based on instantaneous reactive power theory and fuzzy PID. IEEE Transactions on Industrial Electronics, 55(4), 1658–1665. https://doi.org/10.1109/TIE.2007.911933
Wolpert, D. H., & Macready, W. G. (1997). No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1(1), 67–82. https://doi.org/10.1109/4235.585893
Wong, L. A., Ramachandaramurthy, V. K., Taylor, P., Ekanayake, J. B., Walker, S. L., & Padmanaban, S. (2019). Review on the optimal placement, sizing and control of an energy storage system in the distribution network. Journal of Energy Storage, 21(June 2018), 489–504. https://doi.org/10.1016/j.est.2018.12.015
Xing, Y. Q., Jin, J. X., Wang, Y. L., Du, B. X., & Wang, S. C. (2016). An Electric Vehicle Charging System Using an SMES Implanted Smart Grid. IEEE Transactions on Applied Superconductivity, 26(7). https://doi.org/10.1109/TASC.2016.2602245
Yakout, A. H., Hasanien, H. M., & Kotb, H. (2021). Proton Exchange Membrane Fuel Cell Steady State Modeling Using Marine Predator Algorithm Optimizer. Ain Shams Engineering Journal, 12(4), 3765–3774. https://doi.org/10.1016/J.ASEJ.2021.04.014
Yenealem, M. G., Ngoo, L. M. H., Shiferaw, D., & Hinga, P. (2020). Management of voltage profile and power loss minimization in a grid-connected microgrid system using fuzzy-based STATCOM controller. Journal of Electrical and Computer Engineering, 2020. https://doi.org/10.1155/2020/2040139
Ziadi, Z., & Abdel-Akher, M. (2014). Voltage control of unbalanced distribution system with wind energy conversion system and high photovoltaic penetration. Proceedings - ICPERE 2014: 2nd IEEE Conference on Power Engineering and Renewable Energy 2014, 146–151. https://doi.org/10.1109/ICPERE.2014.7067194
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Steven Sesay, Cyrus Wabuge Wekesa
This work is licensed under a Creative Commons Attribution 4.0 International License.
