Optimal Analysis of Microgrid (MG) Systems: Modeling and Control Dynamics for Enhanced Performance – A Case Study Approach

Authors

  • B. O. Ariyo Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria & Department of Electrical and Electronics Engineering, Faculty of Engineering and Technology, University of Ilorin, Nigeria
  • L. M. Adesina Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria
  • O. Ogunbiyi Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria
  • A. Musa Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria & Institute for Intelligent Systems, University of Johannesburg, South Africa
  • B. J. Ojuolape Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria
  • M. O. Balogun Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria

DOI:

https://doi.org/10.63746/njtd.v23i1.3905

Keywords:

HOMER Pro Simulation, MATLAB Simulink Modeling, Microgrid (MG) Optimization, Renewable Energy Integration, Rural Electrification, Techno-Economic Analysis

Abstract

The escalating global energy demand and reliance on renewables highlight the need for sustainable and reliable power solutions. This study investigates the feasibility of a hybrid PV-Wind-BESS microgrid to provide clean electricity for underserved communities, using Olowo-Oko in Kwara State, Nigeria, as a case study. Average daily loads of 19.72 kWh (rainy season) and 22.95 kWh (dry season) were recorded using a Fluke 432-II Power Analyzer. Solar irradiance and wind speed data were sourced from NASA. The microgrid was modeled and simulated in MATLAB Simulink, incorporating advanced control strategies for voltage and frequency regulation. Techniques such as Triangular and Sinusoidal Pulse Width Modulation (TPWM and SPWM), combined with passive filters, effectively mitigated harmonics and enhanced power quality. Simulation results showed stable dynamic performance, minimal ripple, and efficient renewable integration. Further validation using HOMER Pro enabled techno-economic optimization, achieving a 96.8% renewable fraction, a levelized cost of energy (LCOE) of $0.033/kWh, and a payback period of 8 years and 10 days. Sensitivity analysis identified battery cost and inverter performance as key factors influencing system viability. The proposed dual mode microgrid, validated through both dynamic modeling and financial simulation, demonstrates technical robustness and economic feasibility for decentralized rural electrification in Sub-Saharan Africa. This integrated framework offers valuable insights for energy developers, researchers, and policymakers aiming to scale up low-carbon, community-based energy systems. By advancing hybrid microgrid modeling, adaptive control techniques, and cost optimization strategies, the study contributes to the practical realization of SDG 7, supporting universal access to affordable, reliable, and clean energy.

Author Biographies

L. M. Adesina, Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria

Associate Professor,

Department of Electrical and Computer Engineering,

Kwara State University, Malete, Ilorin, Nigeria.

O. Ogunbiyi, Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria

Associate Professor,

Department of Electrical and Computer Engineering,

Faculty of Engineering and Technology,

Kwara State University, Malete, Nigeria.

A. Musa, Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria & Institute for Intelligent Systems, University of Johannesburg, South Africa

Associate Professor,

Department of Electrical and Computer Engineering,

Faculty of Engineering and Technology,

Kwara State University, Malete, Nigeria.

B. J. Ojuolape, Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria

Lecturer I,

Department of Electrical and Computer Engineering,

Faculty of Engineering and Technology,

Kwara State University, Malete, Nigeria.

M. O. Balogun, Department of Electrical and Computer Engineering, Faculty of Engineering and Technology, Kwara State University, Malete, Nigeria

Lecturer I,

Department of Electrical and Computer Engineering,

Faculty of Engineering and Technology,

Kwara State University, Malete, Nigeria.

References

Abedrabboh, O., Koç, M., & Biçer, Y. (2022). Modelling and analysis of a renewable energy-driven climate-controlled sustainable greenhouse for hot and arid climates. Energy Conversion and Management, 273. https://doi.org/10.1016/j.enconman.2022.116412

Abhishek, A., Ranjan, A., Devassy, S., Kumar Verma, B., Ram, S. K., & Dhakar, A. K. (2020). Review of hierarchical control strategies for DC microgrid. In IET Renewable Power Generation (Vol. 14, Issue 10, pp. 1631–1640). John Wiley and Sons Inc. https://doi.org/10.1049/iet-rpg.2019.1136

Adesina, L. M., Ariyo, B. O., Ogunbiyi, O., & Musa, A. (2025). Optimal Analysis of Microgrid ( MG ) Systems?: Modeling and Control Dynamics for Enhanced Performance – A Case Study Approach. KU8+, 2(2), 1–40.

Agha Kassab, F., Rodriguez, R., Celik, B., Locment, F., & Sechilariu, M. (2024). A Comprehensive Review of Sizing and Energy Management Strategies for Optimal Planning of Microgrids with PV and Other Renewable Integration. Applied Sciences (Switzerland), 14(22), 1–31. https://doi.org/10.3390/app142210479

Ahmad Khan, A., Faiz Minai, A., Godi, R. K., Shankar Sharma, V., Malik, H., & Afthanorhan, A. (2025). Optimal Sizing, Techno-Economic Feasibility and Reliability Analysis of Hybrid Renewable Energy System: A Systematic Review of Energy Storage Systems’ Integration. IEEE Access, 13(January), 59198–59226. https://doi.org/10.1109/ACCESS.2025.3535520

Aicha, M. Ben, Hacene, N., & Teta, A. (2025). Comparative study of P & O and PSO-based MPPT algorithms for PV systems under partial shading conditions Comparative study of P & O and PSO-based MPPT algorithms for PV systems under partial shading conditions. Researchgate, June, 1–9.

Al-Ezzi, A. S., & Ansari, M. N. M. (2022). Photovoltaic Solar Cells: A Review. In Applied System Innovation (Vol. 5, Issue 4). MDPI. https://doi.org/10.3390/asi5040067

Al-Mahammedi, M. T. F., & Onat, M. (2025). Optimal Siting, Sizing, and Energy Management of Distributed Renewable Generation and Storage Under Atmospheric Conditions. Sustainability (Switzerland), 17(1). https://doi.org/10.3390/su17010300

Al-Quraan, A., Al-Masri, H., Al-Mahmodi, M., & Radaideh, A. (2022). Power curve modelling of wind turbines- A comparison study. IET Renewable Power Generation, 16(2), 362–374. https://doi.org/10.1049/rpg2.12329

Al-Quraan, A., & Al-Qaisi, M. (2021). Modelling, design and control of a standalone hybrid PV-wind micro-grid system. Energies, 14(16), 1–23. https://doi.org/10.3390/en14164849

Alam, F., & Jin, Y. (2023). The Utilisation of Small Wind Turbines in Built-Up Areas: Prospects and Challenges. Wind, 3(4), 418–439. https://doi.org/10.3390/wind3040024

Alotibe, M., & Crebbin, G. (2010). Microgrid: Modelling and Control.

Andreotti, D., Spiller, M., Scrocca, A., Bovera, F., & Rancilio, G. (2024). Modeling and Analysis of BESS Operations in Electricity Markets: Prediction and Strategies for Day-Ahead and Continuous Intra-Day Markets. Sustainability, 16(18), 7940. https://doi.org/10.3390/su16187940

Anselma, P. G., Kollmeyer, P. J., Feraco, S., Bonfitto, A., Belingardi, G., Emadi, A., Amati, N., & Tonoli, A. (2023). Economic Payback Time of Battery Pack Replacement for Hybrid and Plug-In Hybrid Electric Vehicles. IEEE Transactions on Transportation Electrification, 9(1), 1021–1033. https://doi.org/10.1109/TTE.2022.3202792

Assad, U., Hassan, M. A. S., Farooq, U., Kabir, A., Khan, M. Z., Bukhari, S. S. H., Jaffri, Z. U. A., Oláh, J., & Popp, J. (2022). Smartgrid, Demand Response and Optimization: A Critical Review of Computational Methods. Energies, 15(6), 1–36. https://doi.org/10.3390/en15062003

Bhatti, M. Z. A., Siddique, A., Aslam, W., & Atiq, S. (2024). Design and Analysis of a Hybrid Stand-Alone Microgrid. Energies, 17(1). https://doi.org/10.3390/en17010200

Bilendo, F., Meyer, A., Badihi, H., Lu, N., Cambron, P., & Jiang, B. (2023). Applications and Modeling Techniques of Wind Turbine Power Curve for Wind Farms—A Review. In Energies (Vol. 16, Issue 1). MDPI. https://doi.org/10.3390/en16010180

Bui, V. H., Truong, V. A., Nguyen, V. L., & Duong, T. L. (2024). Estimating the potential maximum power point based on the calculation of short-circuit current and open-circuit voltage. IET Power Electronics, 17(3), 402–421. https://doi.org/10.1049/pel2.12651

Djilali, A. B., Yahdou, A., Benbouhenni, H., Alhejji, A., Zellouma, D., & Bounadja, E. (2024). Enhanced perturb and observe control for addressing power loss under rapid load changes using a buck–boost converter. Energy Reports, 12, 1503–1516. https://doi.org/10.1016/j.egyr.2024.07.032

Ebrahimi, A., Attar, S., & Farhang-Moghaddam, B. (2021). A multi-objective decision model for residential building energy optimization based on hybrid renewable energy systems. International Journal of Green Energy, 18(8), 775–792. https://doi.org/10.1080/15435075.2021.1880911

Ekpoh, M. I., Otuagoma, S. O., Ubeku, E. U., & Eyenubo, O. J. (2025). Techno-Economics Analysis of an Off-Grid Hybrid Power System for Rural Areas in Nigeria. Journal Of Engineering Research Innovation And Scientific Development, 3(1), 1–8. https://doi.org/10.61448/jerisd32251

Fani, B., Shahgholian, G., Haes Alhelou, H., & Siano, P. (2022). Inverter-based islanded microgrid: A review on technologies and control. In e-Prime - Advances in Electrical Engineering, Electronics and Energy (Vol. 2). Elsevier Ltd. https://doi.org/10.1016/j.prime.2022.100068

Finnah, B. (2022). Optimal bidding functions for renewable energies in sequential electricity markets. OR Spectrum, 44(1), 1–25. https://doi.org/10.1007/s00291-021-00646-9

Ghayth, A., Yusupov, Z., Hesri, A., & Khaleel, M. (2023). Performance Enhancement of PV Array Utilizing Perturb & Observe Algorithm. International Journal of Electrical Engineering and Sustainability (IJEES), 1(2), 29–37. https://ijees.org/index.php/ijees/index

Ghayth, A., Yusupov, Z., & Khaleel, M. (2023). Performance Enhancement of PV Array Utilizing Perturb & Observe Algorithm. International Journal of Electrical Engineering and Sustainability (IJEES), 1(2), 29–37.

Gholami, M., Muyeen, S. M., & Lin, S. (2024). Optimizing microgrid efficiency: Coordinating commercial and residential demand patterns with shared battery energy storage. Journal of Energy Storage, 88, 1–14. https://doi.org/10.1016/j.est.2024.111485

Gupta, A., & Singh, O. (2021). Design & Analysis of Grid Tied Single Stage Three Phase PV System. International Research Journal of Engineering and Technology. www.irjet.net

He, M., Wang, Y., Song, Z., Tan, Z., Cai, Y., You, X., Xie, G., & Huang, X. (2025). Power Quality Mitigation in Modern Distribution Grids?: A Comprehensive Review of Emerging Technologies and Future Pathways. Processes, 13(2615), 1–25.

Hedayatnia, A., Ghafourian, J., Sepehrzad, R., Al-Durrad, A., & Anvari-Moghaddam, A. (2024). Two-Stage Data-Driven optimal energy management and dynamic Real-Time operation in networked microgrid based deep reinforcement learning approach. International Journal of Electrical Power and Energy Systems, 160, 1–19. https://doi.org/10.1016/j.ijepes.2024.110142

Hernández-Mayoral, E., Jiménez-Román, C. R., Enriquez-Santiago, J. A., López-López, A., González-Domínguez, R. A., Ramírez-Torres, J. A., Rodríguez-Romero, J. D., & Jaramillo, O. A. (2024). Power Quality Analysis of a Microgrid-Based on Renewable Energy Sources: A Simulation-Based Approach. Computation, 12(11), 1–32. https://doi.org/10.3390/computation12110226

Hoarc?, I. C., Bizon, N., ?orlei, I. S., & Thounthong, P. (2023). Sizing Design for a Hybrid Renewable Power System Using HOMER and iHOGA Simulators. Energies, 16(4), 1–25. https://doi.org/10.3390/en16041926

Kareem, P. R., Hasan, F. H., Algburi, S., Ezzat, S. B., & Kareem, P. R. (2025). Investigating the Impact of Internal and External Factors on Solar Cell Performance to Enhance Energy Conversion Efficiency. IRAQI Academic Scientic Journals, 8(1), 14–23.

Kreishan, M. Z., & Zobaa, A. F. (2023). Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization. Energies, 16(10). https://doi.org/10.3390/en16104257

Kumar, P. H., Gopi, R. R., Rajarajan, R., Vaishali, N. B., Vasavi, K., & Kumar P, S. (2024). Prefeasibility techno-economic analysis of hybrid renewable energy system. E-Prime - Advances in Electrical Engineering, Electronics and Energy, 7, 1–19. https://doi.org/10.1016/j.prime.2024.100443

Letzgus, S., & Müller, K. R. (2024). An explainable AI framework for robust and transparent data-driven wind turbine power curve models. Energy and AI, 15. https://doi.org/10.1016/j.egyai.2023.100328

Marti-Puig, P., Hernández, J. Á., Solé-Casals, J., & Serra-Serra, M. (2024). Enhancing Reliability in Wind Turbine Power Curve Estimation. Applied Sciences (Switzerland), 14(6). https://doi.org/10.3390/app14062479

Ma?lak, G., & Or?owski, P. (2022). Microgrid Operation Optimization Using Hybrid System Modeling and Switched Model Predictive Control. Energies, 15(3). https://doi.org/10.3390/en15030833

Mazorra-Aguiar, L., Lauret, P., David, M., Oliver, A., & Montero, G. (2021). Comparison of two solar probabilistic forecasting methodologies for microgrids energy efficiency. Energies, 14(6). https://doi.org/10.3390/en14061679

Mohammed, M. F., & Qasim, M. A. (2022). Single Phase T-Type Multilevel Inverters for Renewable Energy Systems, Topology, Modulation, and Control Techniques: A Review. Energies, 15(22), 1–24. https://doi.org/10.3390/en15228720

Mohammed, R. H., Abdulrazzaq, A. A., & Al-Azzawi, W. K. (2022). Benefits of MPP tracking PV system using perturb and observe technique with boost converter. International Journal of Power Electronics and Drive Systems, 13(4), 2468–2477. https://doi.org/10.11591/ijpeds.v13.i4.pp2468-2477

Mokhtari, K., Shokri-Kojori, S., & Aliyari-Shoorehdeli, M. (2024). A new generalized state-space averaged model, control design and stability analysis for three phase grid-connected quasi-Z-Source inverters. International Journal of Electrical Power and Energy Systems, 158. https://doi.org/10.1016/j.ijepes.2024.109932

Nadzim, M., Yusoof, M., Iqbal Zakaria, M., Farina Shair, E., Khalid, N. S., Rahman, A., & Emhemed, A. A. (2023). Investigating the Effectiveness of Maximum Power Point Tracking (MPPT) with Perturb and Observe (P&O) Algorithm in Solar Power Battery Charging System. In Journal of Engineering Research and Education (Vol. 15).

Ngao-det, M., Thongpron, J., Namin, A., Patcharaprakiti, N., Muangjai, W., & Somsak, T. (2025). Systematic Optimize and Cost-Effective Design of a 100% Renewable Microgrid Hybrid System for Sustainable Rural Electrification in Khlong Ruea, Thailand. Energies, 18(7), 1–35. https://doi.org/10.3390/en18071628

Nur-e-alam, M., Abedin, T., Samsudin, N. A., & Petr?, J. (2025). Optimization of energy management in Malaysian microgrids using fuzzy logic-based EMS scheduling controller. Scientific Reports, 15(995), 1–15.

Nur-E-Alam, M., Abedin, T., Samsudin, N. A., Petr?, J., Barnawi, A. B., Soudagar, M. E. M., Khan, T. M. Y., Bashir, M. N., Islam, M. A., Yap, B. K., & Kiong, T. S. (2025). Optimization of energy management in Malaysian microgrids using fuzzy logic-based EMS scheduling controller. Scientific Reports, 15(1), 1–15. https://doi.org/10.1038/s41598-024-82360-4

Nwakarame, I. P., & Awogbemi, T. O. (2024). Exchange Rate Volatility on Economic GrowtThe Impact of Foreign h of Nigeria. 10(4), 215–227.

Obiwulu, A. U., Erusiafe, N., Olopade, M. A., & Nwokolo, S. C. (2022). Modeling and estimation of the optimal tilt angle, maximum incident solar radiation, and global radiation index of the photovoltaic system. Heliyon, 8(6). https://doi.org/10.1016/j.heliyon.2022.e09598

Odoi-Yorke, F., & Woenagnon, A. (2021). Techno-economic assessment of solar PV/fuel cell hybrid power system for telecom base stations in Ghana. Cogent Engineering, 8(1), 1–25. https://doi.org/10.1080/23311916.2021.1911285

Oleschuk, v. (2023). Evolution and dissemination of specialized strategies, methods, and techniques of synchronous pulsewudth modulation for control of voltage source inverters and inverter-based systems. Technical Electrodynamics, 2023(5), 14–27. https://doi.org/10.15407/techned2023.05.014

Olurinola, I. O., & Egbe, I. E. (2024). Examining the Effects of Fiscal-Monetary Policy Interactions on Unemployment Rates in Nigeria ( 1985-2023 ). 8(9), 1–16. https://doi.org/10.47772/IJRISS

Prabhakar, D., Nagaraja, S., Koundinya, S. P., & Meghana, R. (2025). Power Extraction in Photovoltaic Systems using P&O-Based MPPT with DC-DC Buck Converter Integration. WSEAS Transactions on Electronics, 16, 46–50. https://doi.org/10.37394/232017.2025.16.6

Quizhpe, K., Arévalo, P., Ochoa-Correa, D., & Villa-Ávila, E. (2024). Optimizing Microgrid Planning for Renewable Integration in Power Systems: A Comprehensive Review. Electronics, 13(18), 1–30. https://doi.org/10.3390/electronics13183620

Rao, K. S., & Kumar, Y. V. P. (2021). Comprehensive Modelling of Renewable Energy Based Microgrid for System Level Control Studies. International Journal of Renewable Energy Research, 11(1), 223–234. https://doi.org/10.20508/ijrer.v11i1.11745.g8127

Rashwan, A., Mikhaylov, A., Senjyu, T., Eslami, M., Hemeida, A. M., & Osheba, D. S. M. (2023). Modified Droop Control for Microgrid Power-Sharing Stability Improvement. Sustainability (Switzerland), 15(14), 1–19. https://doi.org/10.3390/su151411220

Regany, D., Palau, F. M., Crespo, A., Barrau, J., Vilarrubí, M., & Rosell-Urrutia, J. (2025). Enhancing efficiency of dense array CPV receivers with controlled DC-DC converters and adaptive microfluidic cooling under non-uniform solar irradiance. Solar Energy Materials and Solar Cells, 279. https://doi.org/10.1016/j.solmat.2024.113262

Remoaldo, D., & Jesus, I. S. (2021). Analysis of a traditional and a fuzzy logic enhanced perturb and observe algorithm for the mppt of a photovoltaic system. Algorithms, 14(1), 1–19. https://doi.org/10.3390/a14010024

Rice, I. K., Zhu, H., Zhang, C., & Tapa, A. R. (2023). A Hybrid Photovoltaic/Diesel System for Off-Grid Applications in Lubumbashi, DR Congo: A HOMER Pro Modeling and Optimization Study. Sustainability (Switzerland), 15(10). https://doi.org/10.3390/su15108162

Salehi, N., Martinez-Garcia, H., Velasco-Quesada, G., & Guerrero, J. M. (2022). A Comprehensive Review of Control Strategies and Optimization Methods for Individual and Community Microgrids. IEEE Access, 10, 15935–15955. https://doi.org/10.1109/ACCESS.2022.3142810

Sarang, S. A., Raza, M. A., Panhwar, M., Khan, M., Abbas, G., Touti, E., Altamimi, A., & Wijaya, A. A. (2024). Maximizing solar power generation through conventional and digital MPPT techniques?: a comparative analysis. Scientific Reports, 14(8944), 1–18. https://doi.org/10.1038/s41598-024-59776-z

Sawadogo, B., Benmouna, A., Becherif, M., Barakat, S., & Samy, M. (2025). Integrated solar electrification and community empowerment in a burkina faso Village: A feasibility and design study. Results in Engineering, 27, 1–18. https://doi.org/10.1016/j.rineng.2025.105686

Seane, T. B., Samikannu, R., & Bader, T. (2022). A review of modeling and simulation tools for microgrids based on solar photovoltaics. In Frontiers in Energy Research (Vol. 10). Frontiers Media S.A. https://doi.org/10.3389/fenrg.2022.772561

Singh, K. M., & Gope, S. (2021). Renewable energy integrated multi-microgrid load frequency control using grey wolf optimization algorithm. Materials Today: Proceedings, 46, 2572–2579. https://doi.org/10.1016/j.matpr.2021.02.035

Taye, B. A., & Choudhury, N. B. D. (2023). Adaptive filter based method for hybrid energy storage system management in DC microgrid. E-Prime - Advances in Electrical Engineering, Electronics and Energy, 5, 1–13. https://doi.org/10.1016/j.prime.2023.100259

Twaisan, K., & Bar, N. (2022). Integrated Distributed Energy Resources (DER) and Microgrids: Modeling and Optimization of DERs. In Electronics (Switzerland) (Vol. 11, Issue 18, pp. 1–24). MDPI. https://doi.org/10.3390/electronics11182816

Umar, D. A., Yaw, C. T., Koh, S. P., Tiong, S. K., Alkahtani, A. A., & Yusaf, T. (2022). Design and Optimization of a Small-Scale Horizontal Axis Wind Turbine Blade for Energy Harvesting at Low Wind Profile Areas. Energies, 15(9). https://doi.org/10.3390/en15093033

Uwineza, L., Kim, H. G., & Kim, C. K. (2021). Feasibilty study of integrating the renewable energy system in Popova Island using the Monte Carlo model and HOMER. Energy Strategy Reviews, 33, 100607. https://doi.org/10.1016/j.esr.2020.100607

Vaish, J., Tiwari, A. K., & Siddiqui, K. M. (2023). Optimization of micro grid with distributed energy resources using physics based meta heuristic techniques. IET Renewable Power Generation, 1–17. https://doi.org/10.1049/rpg2.12699

Venkateswari, R., & Rajasekar, N. (2021). Review on parameter estimation techniques of solar photovoltaic systems. In International Transactions on Electrical Energy Systems (Vol. 31, Issue 11). John Wiley and Sons Ltd. https://doi.org/10.1002/2050-7038.13113

Wang, Z., Liu, Y., Wang, R., & Hu, Y. (2024). Cost – Benefit Analysis of Cross-Regional Transmission of Renewable Electricity?: A Chinese Case Study. Sustainability, 16(10538), 1–21.

Xia, G., Draxl, C., Berg, L. K., & Cook, D. (2021). Quantifying the impacts of land surface modeling on hub-height wind speed under different soil conditions. Monthly Weather Review, 149(9), 3101–3118. https://doi.org/10.1175/MWR-D-20-0363.1

Yimen, N., Hamandjoda, O., Meva’a, L., Ndzana, B., & Nganhou, J. (2018). Analyzing of a photovoltaic/wind/biogas/pumped-hydro off-grid hybrid system for rural electrification in Sub-Saharan Africa - Case study of Djoundé in Northern Cameroon. Energies, 11(10), 1–30. https://doi.org/10.3390/en11102644

Zadehbagheri, M., Kiani, M. J., & Khandan, S. (2025). Designing a Robust SMC for Voltage and Power Control in Islanded Micro-grid and Simultaneous use of Load Shedding Method. Journal of Operation and Automation in Power Engineering, 13(1), 74–87. https://doi.org/10.22098/joape.2023.12215.1910

Zulu, M. L. T., Carpanen, R. P., & Tiako, R. (2023). A Comprehensive Review: Study of Artificial Intelligence Optimization Technique Applications in a Hybrid Microgrid at Times of Fault Outbreaks. In Energies (Vol. 16, Issue 4, pp. 1–32). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/en16041786

Published

2026-03-31

Issue

Vol. 23 No. 1 (2026): Volume 23, Issue 1, March 2026.

Section

Articles

License

Copyright (c) 2026 Nigerian Journal of Technological Development

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

In accordance with the Copyright Act of 1976, which became effective January 1, 1978, the following statement signed by each author must accompany the manuscript submitted: "I, the undersigned author, transfer all copyright ownership of the manuscript referenced above to the Nigerian Journal of Technological Development, in the event the work is published. I warrant that the article is original, does not infringe upon any copyright or other proprietary right of any third party, is not under consideration by another journal, and has not been published previously. I have reviewed and approved the submitted version of the manuscript and agree to its publication in the Nigerian Journal of Technological Development." A copyright transfer form can be downloaded from the NJTD Website (http://njtd.com.ng/index.php/njtd). Author(s) will be consulted, whenever possible, regarding republication of material. All authors must have access to the data presented, and the authors and sponsor (if applicable) must agree to share original data with the editor if requested.

Similar Articles

1 2 > >> 

You may also start an advanced similarity search for this article.