(El Sewedy Electric Steel Applications, Egypt)(2) Fahd A. Banakhr
(Yanbu Industrial College, Saudi Arabia)(3) Tarek Hassan Mohamed
(Aswan University, Egypt)(4) Shimaa Mohamed Ali
(Aswan University, Egypt)(5) * Mohamed Metwally Mahmoud
(Aswan University, Egypt)(6) Mohamed I. Mosaad
(Yanbu Industrial College, Saudi Arabia)(7) Alauddin Adel Hamoodi Albla
(Imam Ja’afar Al-Sadiq University, Iraq)(8) Mahmoud M. Hussein
(1) Electrical Engineering Department, Faculty of Energy Engineering, Aswan University, Aswan81511, Egypt. 2) Department of Communications Technology Engineering, Imam Ja’afar Al-Sadiq University, Baghdad 10053, Iraq)*corresponding author
AbstractIn recent years, significant improvements have been made in the load frequency control (LFC) of interconnected microgrid (MG) systems, driven by the growing demand for enhanced power supply quality. However, challenges such as low inertia, parameter uncertainties, and dynamic complexity persist, posing significant hurdles for controller design in MGs. Addressing these challenges is crucial as any mismatch between demand load and power generation inevitably leads to frequency deviation and tie-line power interchange within the MG. This work introduces sophisticated optimization techniques (grey wolf optimization (GWO), whale optimization algorithm (WOA), and balloon effect (BE)) for LFC, focusing on the optimal online tuning of integral controller gain (Ki) for controlled loads. The WOA regulates the frequency of the system so variable loads can be accommodated and 6 MW of PV is added to the MG. A PV and a diesel generator-powered isolated single area MGs with electrical random loads are managed by the adaptive controller by regulating the frequency and power of the PV. Online tuning of integral controllers is possible using the WOA. A comparison is carried out between the WOA+BE and three other optimizers, namely the GWO, GWO+BE method, and the WOA. This paper shows the effect of add BE identifier to standard WOA and GWO. MATLAB simulation results prove that the BE identifier offers a significant advantage to the investigated optimizers in the issue of adaptive frequency stability even when disturbances and uncertainties are concurrent. KeywordsLoad Frequency Control; Microgrid; Optimization Methods; Clean Energy; Adaptive Controller
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DOIhttps://doi.org/10.31763/ijrcs.v4i3.1432 |
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References
[1] IEA, “Net Zero by 2050: A Roadmap for the Global Energy Sector - International Energy Agency,” International Energy Agency, p. 224, 2021, https://www.iea.org/reports/net-zero-by-2050.
[2] R. Kassem et al., “A Techno-Economic-Environmental Feasibility Study of Residential Solar Photovoltaic / Biomass Power Generation for Rural Electrification: A Real Case Study,” Sustainability, vol. 16, no. 5, p. 2036, 2024, https://doi.org/10.3390/su16052036.
[3] M. Mureddu, G. Caldarelli, A. Chessa, A. Scala, and A. Damiano, “Green power grids: How energy from renewable sources affects networks and markets,” PLoS One, vol. 10, no. 9, p. e0135312, 2015, https://doi.org/10.1371/journal.pone.0135312.
[4] M. M. Mahmoud, “Improved current control loops in wind side converter with the support of wild horse optimizer for enhancing the dynamic performance of PMSG-based wind generation system,” International Journal of Modelling and Simulation, vol. 43, no. 6, pp. 952-966, 2023, https://doi.org/10.1080/02286203.2022.2139128.
[5] N. F. Ibrahim et al., “A new adaptive MPPT technique using an improved INC algorithm supported by fuzzy self-tuning controller for a grid-linked photovoltaic system,” PLoS One, vol. 18, no. 11, p. e0293613, 2023, https://doi.org/10.1371/journal.pone.0293613.
[6] M. Awad, M. M. Mahmoud, Z. M. S. Elbarbary, L. Mohamed Ali, S. N. Fahmy, and A. I. Omar, “Design and analysis of photovoltaic/wind operations at MPPT for hydrogen production using a PEM electrolyzer: Towards innovations in green technology,” PLoS One, vol. 18, no. 7, p. e0287772, 2023, https://doi.org/10.1371/journal.pone.0287772.
[7] A. E. Elwakeel et al., “Design and Implementation of a PV-Integrated Solar Dryer Based on Internet of Things and Date Fruit Quality Monitoring and Control,” International Journal of Energy Research, 2023, https://doi.org/10.1155/2023/7425045.
[8] Z. Xie, D. Zhang, X. Han, and W. Hu, “Power system transient stability preventive control optimization method driven by Stacking Ensemble Learning,” Energy Reports, vol. 9, pp. 757-765, 2023, https://doi.org/10.1016/j.egyr.2023.05.106.
[9] O. A. Alimi, K. Ouahada and A. M. Abu-Mahfouz, "A Review of Machine Learning Approaches to Power System Security and Stability," IEEE Access, vol. 8, pp. 113512-113531, 2020, https://doi.org/10.1109/ACCESS.2020.3003568.
[10] M. M. Mahmoud et al., “Integration of Wind Systems with SVC and STATCOM during Various Events to Achieve FRT Capability and Voltage Stability: Towards the Reliability of Modern Power Systems,” International Journal of Energy Research, 2023, https://doi.org/10.1155/2023/8738460.
[11] O. M. Kamel, A. A. Z. Diab, M. M. Mahmoud, A. S. Al-Sumaiti, and H. M. Sultan, “Performance Enhancement of an Islanded Microgrid with the Support of Electrical Vehicle and STATCOM Systems,” Energies, vol. 16, no. 4, p. 1577, 2023, https://doi.org/10.3390/en16041577.
[12] A. M. Ewais, A. M. Elnoby, T. H. Mohamed, M. M. Mahmoud, Y. Qudaih, and A. M. Hassan, “Adaptive frequency control in smart microgrid using controlled loads supported by real-time implementation,” PLoS One, vol. 18, no. 4, p. e0283561, 2023, https://doi.org/10.1371/journal.pone.0283561.
[13] Ibraheem, P. Kumar and D. P. Kothari, "Recent philosophies of automatic generation control strategies in power systems," IEEE Transactions on Power Systems, vol. 20, no. 1, pp. 346-357, 2005, https://doi.org/10.1109/TPWRS.2004.840438.
[14] M. M. Hussein, T. H. Mohamed, M. M. Mahmoud, M. Aljohania, M. I. Mosaad, and A. M. Hassan, “Regulation of multi-area power system load frequency in presence of V2G scheme,” PLoS One, vol. 18, no. 9, p. e0291463, 2023, https://doi.org/10.1371/journal.pone.0291463.
[15] L. C. Saikia, J. Nanda, and S. Mishra, “Performance comparison of several classical controllers in AGC for multi-area interconnected thermal system,” International Journal of Electrical Power & Energy Systems, vol. 33, no. 3, pp. 394-401, 2011, https://doi.org/10.1016/j.ijepes.2010.08.036.
[16] D. Vamvakas, P. Michailidis, C. Korkas, and E. Kosmatopoulos, “Review and Evaluation of Reinforcement Learning Frameworks on Smart Grid Applications,” Energies, vol. 16, no. 14, p. 5326, 2023, https://doi.org/10.3390/en16145326.
[17] J. Pascual, D. Arcos-Aviles, A. Ursúa, P. Sanchis, and L. Marroyo, “Energy management for an electro-thermal renewable–based residential microgrid with energy balance forecasting and demand side management,” Applied Energy, vol. 295, p. 117062, 2021, https://doi.org/10.1016/j.apenergy.2021.117062.
[18] S. Zheng, X. Tang, B. Song, S. Lu, and B. Ye, “Stable adaptive PI control for permanent magnet synchronous motor drive based on improved JITL technique,” ISA Transactions, vol. 52, no. 4, pp. 539-549, 2013, https://doi.org/10.1016/j.isatra.2013.03.002.
[19] H. Bevrani, F. Habibi, P. Babahajyani, M. Watanabe and Y. Mitani, "Intelligent Frequency Control in an AC Microgrid: Online PSO-Based Fuzzy Tuning Approach," IEEE Transactions on Smart Grid, vol. 3, no. 4, pp. 1935-1944, 2012, https://doi.org/10.1109/TSG.2012.2196806.
[20] H. Shayeghi, H. A. Shayanfar, and A. Jalili, “Load frequency control strategies: A state-of-the-art survey for the researcher,” Energy Conversion and Management, vol. 50, no. 2, pp. 344-353, 2009, https://doi.org/10.1016/j.enconman.2008.09.014.
[21] J. Yang, Z. Zeng, Y. Tang, J. Yan, H. He, and Y. Wu, “Load frequency control in isolated micro-grids with electrical vehicles based on multivariable generalized predictive theory,” Energies, vol. 8, no. 3, pp. 2145-2164, 2015, https://doi.org/10.3390/en8032145.
[22] B. H. Abed-alguni and D. Paul, “Island-based Cuckoo Search with elite opposition-based learning and multiple mutation methods for solving optimization problems,” Soft Computing, vol. 26, pp. 3293-3312, 2022, https://doi.org/10.1007/s00500-021-06665-6.
[23] Y. Xu, C. Li, Z. Wang, N. Zhang and B. Peng, "Load Frequency Control of a Novel Renewable Energy Integrated Micro-Grid Containing Pumped Hydropower Energy Storage," IEEE Access, vol. 6, pp. 29067-29077, 2018, https://doi.org/10.1109/ACCESS.2018.2826015.
[24] V. Devaraj and M. Kumaresan, “Isolated and Grid-Connected Hybrid Microgrid Model Frequency Stabilization by Novel Salp-Swarm Optimization Algorithm,” SSRG International Journal of Electrical and Electronics Engineering, vol. 10, no. 6, pp. 58-69, 2023, https://doi.org/10.14445/23488379/IJEEE-V10I6P107.
[25] H. Haes Alhelou, M. E. H. Golshan and N. D. Hatziargyriou, "A Decentralized Functional Observer Based Optimal LFC Considering Unknown Inputs, Uncertainties, and Cyber-Attacks," IEEE Transactions on Power Systems, vol. 34, no. 6, pp. 4408-4417, 2019, https://doi.org/10.1109/TPWRS.2019.2916558.
[26] M. Z. Kreishan and A. F. Zobaa, “Optimal allocation and operation of droop-controlled islanded microgrids: A review,” Energies, vol. 14, no. 15, p. 4653, 2021, https://doi.org/10.3390/en14154653.
[27] S. Mirjalili and A. Lewis, “The Whale Optimization Algorithm,” Advances in Engineering Software, vol. 95, pp. 51-67, 2016, https://doi.org/10.1016/j.advengsoft.2016.01.008.
[28] M. M. Mahmoud, M. M. Aly, H. S. Salama, and A. M. M. Abdel-Rahim, “Dynamic evaluation of optimization techniques–based proportional–integral controller for wind-driven permanent magnet synchronous generator,” Wind Engineering, vol. 45, no. 3, pp. 696-709, 2021, https://doi.org/10.1177/0309524X20930421.
[29] Y. A. Dahab, H. Abubakr and T. H. Mohamed, "Adaptive Load Frequency Control of Power Systems Using Electro-Search Optimization Supported by the Balloon Effect," IEEE Access, vol. 8, pp. 7408-7422, 2020, https://doi.org/10.1109/ACCESS.2020.2964104.
[30] R. Ali, T. H. Mohamed, Y. S. Qudaih, and Y. Mitani, “A new load frequency control approach in an isolated small power systems using coefficient diagram method,” International Journal of Electrical Power & Energy Systems, vol. 56, pp. 110-116, 2014, https://doi.org/10.1016/j.ijepes.2013.11.002.
[31] P. D. P. Reddy, V. C. V. Reddy, T. G. Manohar, “Optimal renewable resources placement in distribution networks by combined power loss index and whale optimization algorithms,” Journal of Electrical Systems and Information Technology, vol. 5, no. 2, pp. 175-191, 2018, https://doi.org/10.1016/j.jesit.2017.05.006.
[32] C. Muro, R. Escobedo, L. Spector, and R. P. Coppinger, “Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations,” Behavioural Processes, vol. 88, no. 3, pp. 192-197, 2011, https://doi.org/10.1016/j.beproc.2011.09.006.
[33] S. Mirjalili, S. M. Mirjalili, and A. Lewis, “Grey Wolf Optimizer,” Advances in Engineering Software, vol. 69, pp. 46-61, 2014, https://doi.org/10.1016/j.advengsoft.2013.12.007.Refbacks
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