A Hybrid Microgrid using A Nodemcu Microcontroller
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Abstract:
Backgorund of study: Access to reliable electricity remains a major issue in remote, hilly, and island areas where conventional power infrastructure is lacking. These communities often face limited energy options, hindering development and quality of life. Renewable energy, particularly when harnessed in hybrid systems, presents an opportunity for sustainable and decentralized solutions. Aims and scope of paper: This study develops a solar-wind hybrid system with battery storage to deliver clean, reliable power to off-grid areas, focusing on design, conversion, optimization, and real-time monitoring. Methods: The system combines solar and wind energy, stabilizes output with boost-buck converters, converts DC to AC via an inverter, uses ESP32 NodeMCU for real-time monitoring through Blynk, and applies MPPT to maximize energy efficiency. Result: The system successfully delivers a stable power supply in off-grid settings by improving energy harvesting efficiency through the MPPT algorithm. Real-time monitoring enhances user interaction and system management. The combination of solar and wind energy supported by battery storage ensures a continuous and dependable power flow. Conclusion : The study confirms that the hybrid microgrid system developed is an efficient, scalable, and environmentally sustainable solution for communities with limited electricity access. It also demonstrates the potential of such technologies to reduce reliance on fossil fuels while promoting clean energy adoption in underserved areas.
Keywords: Electric Bicycle, GPS Location, IOT Security, Microgrid, Nodemcu Microcontroller
References
Heidari, M., Seifossadat, G., & Razaz, M. (2013). Application of decision tree and discrete wavelet transform for an optimized intelligent-based islanding detection method in distributed systems with distributed generations. Renewable and Sustainable Energy Reviews, 27, 525–532. https://doi.org/10.1016/j.rser.2013.06.047
Kim, M. S., Haider, R., Cho, G. J., Kim, C. H., Won, C. Y., & Chai, J. S. (2019). Comprehensive review of islanding detection methods for distributed generation systems. Energies, 12(5), 1–21. https://doi.org/10.3390/en12050837
Lidula, N. W. A., & Rajapakse, A. D. (2012). A pattern-recognition approach for detecting power islands using transient signals-part II: Performance evaluation. IEEE Transactions on Power Delivery, 27(3), 1071–1080. https://doi.org/10.1109/TPWRD.2012.2187344
Narang, D., Ingram, M., Narang, D., & Ingram, M. (2023). A primer on the unintentional islanding protection requirement in IEEE Std 1547–2018.May. pp. 1–34, 2022. [Online]. Available
Rami Reddy, C., Harinadha Reddy, K., Aymen, F., Srikanth Goud, B., Bajaj, M., Abdulaal, M. J., & Milyani, A. H. (2022). Hybrid ROCOF Relay for Islanding Detection. Journal of Electrical Engineering and Technology, 17(1), 51–60. https://doi.org/10.1007/s42835-021-00856-9
Rokach, L., & Maimon, O. (2005). Top-down induction of decision trees classifiers - A survey. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 35(4), 476–487. https://doi.org/10.1109/TSMCC.2004.843247
