Data-Driven Assessment of Low-Speed Wind Energy Harvesting Potential Using MATLAB/Simulink Modeling
Keywords:
Wind energy harvesting, Wireless Sensor Networks, IoT Power Supply, Small-Scale Wind Turbine, Data-Driven Assessment
Abstract
This study presents a data-driven evaluation of a wind energy harvesting system designed for low power applications, particularly wireless sensor networks (WSNs). High resolution wind speed data were collected over a one-year period from January-December 2025 at the Federal University of Petroleum Resources, Effurun (FUPRE), Nigeria, using a calibrated Automated Weather Observing Station (AWOS). A comprehensive system model was developed in MATLAB/Simulink, incorporating aerodynamic wind turbine dynamics, electromagnetic energy conversion, rectification, DC-DC conversion, maximum power point tracking (MPPT) using the perturb and observe (P&O) algorithm, and a power management system (PMS) with battery storage. Simulation results reveal strong seasonal variations in harvested power, with peak performance observed in March, where average DC-DC output reaches approximately 38.022 mW and daily harvested energy peaks at about 0.766 Wh/day. Lower performance is recorded during periods of reduced wind activity, particularly between October and November. Despite these fluctuations, the PMS effectively regulates power flow, ensuring stable energy delivery to the load. The system demonstrates a relatively constant efficiency of approximately 16.47% across all months, indicating stable internal conversion performance. Overall, the results confirm the feasibility of utilizing low-speed wind energy for continuous power supply in autonomous systems. The study highlights the effectiveness of integrating real environmental data with intelligent power management strategies to enhance reliability and energy utilization in wind energy harvesting applications.
References
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Tiliute, D. E. (2007). Battery management in wireless sensor networks. Elektronika Ir Elektrotechnika, 76(4), 9–12.
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Ahmad, I., Rehman, M. M. U., Khan, M., Abbas A., Ishfaq, S. & Malik, S. (2019). Flow-Based Electromagnetic-Type Energy Harvester using Microplanar Coil for IoT Sensors Application. International Journal of Energy Research, 43(10), 5384–5391.
Alexander, J. W., Matheus, F. T., Ian, M. C., Ashraf, A. F. & Johann, S. (2021). Survey of Energy Harvesting Technologies for wireless sensor Networks. IEEE Access 9, 77493-77510.
Apurva, S. (2022). A Review Paper on Wireless Sensor Network. International Journal of Innovative Research in Computer Science & Technology, 10(2), 159-163.
Choudhary, P., Bhargava, L., Singh, V., Choudhary, M. & Suhag, A. K. (2020). A survey – Energy harvesting sources and techniques for internet of things devices. Materials Today, 30(1), 52-56.
Divyanshu, S., Aditya, P. S., Seema, M. & Deepti, G. (2024). Advancements and Challenges in wireless sensor Networks: A Comprehensive review. International Journal of Research, Publication and Reviews, 5(6), 836-842.
Fadoua, Y. & Adil, K. (2022). Energy Harvesting in wireless communication: A survey. Paper presented at the 2021 International Conference on Energy and Green Computing, Mekness, Morocco, 2022. Retrieved from https://doi.org/10.1051/e3sconf/202233600074.
Gupta, C. P. & Kumar, A. (2013). Wireless Sensor Networks: A review. International Journal of Sensors, Wireless Communication and Control, 3, 25-36.
Hamani, I. D., Tikani, R., Assadi, H., & Ziaei-Rad, S. (2020). Energy harvesting from moving harmonic and moving continuous mass traversing on a simply supported beam. Measurement, 150, 1-9.
Hussain, M. N., Halim, M. A., Ali-Khan, M. Y., Ibrahim, S. & Haque, A. (2024). A Comprehensive Review on Techniques and Challenges of Energy Harvesting from Distributed Renewable Energy Sources for Wireless Sensor Networks. Control Systems and Optimization Letters, 2(1), 15-22.
Iftikhar, A., Lim, M. H., Ahmad, M. A., Syed, A. I. & Leong, M. S. (2021). Scopes, challenges and approaches of energy harvesting for wireless sensor nodes in machine condition monitoring systems: A review. Measurements, 183, 1-13.
Jaspreet, S., Ranjit, K. & Damanpreet, S. (2020). Energy Harvesting in Wireless Sensor Networks: A Taxonomic Survey. International Journal of Energy Research, 1-23.
Katrina, C., Diana, S. N. M. & Nasir, B. R. H. (2021). Low power energy harvesting systems: State of the art and future challenges. Renewable and Sustainable Energy Reviews, 147, 1- 20.
Keh, H. C., Wang, Y. H., Lin, K. Y. & Lin, C. C. (2011). Power saving mechanism with optimal sleep control in wireless sensor networks. Tamkang Journal of Science and Technology, 14(3), 235–243.
Khazaee, M., Rezaniakolaie, A., Moosavian, A. & Rosendahl, L. (2019). A novel method for autonomous remote condition monitoring of rotating machines using piezoelectric energy harvesting approach. Sensors and Actuators A: Physical, 295, 37–50.
Loan, T. F. W., Marcelo, A. T., Pedro, M. A. Pedro, G. B. Robson, F. D. (2023). Modeling and Simulating Wind Energy Generation Systems by Means of Co-Simulation Techniques. Energies, 16(19), 1-20.
Marco, G. (2021). Energy Harvesting Strategies for Wireless Sensor Networks and Mobile Devices: A Review. Electronics, 10(6), 1-53.
Muhammad, U. M., Hein, V., Avinash, S. & Muhammad, O. (2025). Advances in Energy Harvesting for Sustainable Wireless Sensor Networks: Challenges and Opportunities. Hardware, 5(1), 1-26.
Obbo, A., Ariho, P. & Nabaasa, E. (2022). Towards Crowd Detection Using Wireless Sensor Networks. European Journal of Technology, 6(2), 32-48.
Onuekwusi, N., Achumba, I., Chukwuchekwa, N., Chukwudebe, G., & Ononiwu, G. (2015). Leveraging wireless sensor networks for improved infrastructure management in the energy sector. Paper presented at the 2015 Nigerian Society of Engineers Annual National Conference, Akure, Nigeria. Retrieved from https://www.researchgate.net/publication/334646341_Leveraging_Wireless_Sensor_Networks_for_Improved_Infrastructure_Management_in_the_Energy_Sector.
Panatik, K. Z., Kamardin, K., Shariff, S. A., Yuhaniz, S. S., Ahmad, N. A., Yusop, O. M. & Ismail, S. (2016). Energy harvesting in wireless sensor networks: A survey. Paper presented at IEEE 3rd International Symposium on Telecommunication Technologies, Kuala Lumpur, Malaysia. Retrieved from https://ieeexplore.ieee.org/document/7918084.
Penella, M. T., Albesa, J., & Gasulla, M. (2009). Powering Wireless Sensor Nodes: Primary Batteries versus Energy Harvesting. Paper presented at the 2009 IEEE instrumentation and measurement technology conference, Singapore. Retrieved from https://www.researchgate.net/publication/41821038_Powering_wireless_sensor_nodes_Primary_batteries_versus_energy_harvesting.
Prauzek, M., Konecny, J., Borova, M., Janosova, K., Hlavica, J. & Musilek, P. (2018). Energy harvesting sources, storage devices and system topologies for environmental wireless sensor networks: A review. Sensors, 18(8), 1-22.
Rajanbabu, A., Thangamuniyandi, C. & Ganesan J. (2020). Energy Harvesting Technology and its Potential applications–A Mini Review. Journal of Nuclear Engineering and Technology, 9 (3), 33–43.
Raquib, M. F., Ahmed, W.R. & Muhammad, F. S. (2016). Renewable energy harvesting for wireless sensors using passive RFID tag technology: A review. Renewable and Sustainable Energy Reviews, 58, 1114-1128.
Shafiq, M., Kauhaniemi, K., Robles, G., Isa, M., & Kumpulainen, L. (2019). Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements. Electrical Power Systems Research, 167, 150–162.
Shaikh, F. K. & Zeadally, S. (2016). Energy harvesting in wireless sensor networks: A comprehensive review. Renewable and Sustainable Energy Reviews, 55, 1041-1054.
Shaikh, F. K., Zeadally, S. & Exposito, E. (2015). Enabling technologies for green internet of things. IEEE System Journal, 11(2), 983–994.
Shaikh, F. K., Zeadally, S. & Siddiqui, F. (2013). Energy efficient routing in wireless sensor networks. In: Chilamkurti N., Zeadally S., & Chaouchi H. (Eds.), Next- generation wireless technologies: 4G and beyond, computer communications and networks (pp. 131-157). London, UK: Springer.
Sichitiu, M. L. & Dutta, R. (2005). Benefits of multiple battery levels for the lifetime of large wireless sensor networks. Paper presented at the 4th International IFIP-TC6 Conference on Research in Networking, Waterloo, Canada. Retrieved from https://dl.ifip.org/db/conf/networking/networking2005/SichitiuD05.pdf.
Tigilu, M. & Mukhdeep, S. M. (2018). Modeling of Wind Energy Harvesting System: A Systematic Review. International Journal of Engineering, Science and Mathematics, 7(4), 444-467.
Tiliute, D. E. (2007). Battery management in wireless sensor networks. Elektronika Ir Elektrotechnika, 76(4), 9–12.
Wang, J., Gao, Y., Liu, W., Sangaiah, A.K. & Kim, H. J. (2019). Energy efficient routing algorithm with mobile sink support for wireless sensor networks. Sensors, 19(7), 1-19.
Zhou, P., Wang, C. & Yang, Y. (2019). Self-sustainable sensor networks with multi-source energy harvesting and wireless charging. Paper presented at the 2019 IEEE International Conference on Computer communications, Paris, France. Retrieved from https://www.researchgate.net/publication/333849744_Self-sustainable_Sensor_Networks_with_Multi-source_Energy_Harvesting_and_Wireless_Charging.
Published
2026-05-13
How to Cite
Igbinoba, C. K., & Okhaifoh, J. E. (2026). Data-Driven Assessment of Low-Speed Wind Energy Harvesting Potential Using MATLAB/Simulink Modeling. European Journal of Science, Innovation and Technology, 6(3), 47-58. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/765
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