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Development of a Hardware Model for Renewable Energy-Based DC Micro-Grid with Automatic Power Transmission using IoT

Beer Singh*, Neel Kamal**, Yash Mishra***, Aman Kumar****, Vikash Sharma*****

*-***** Department of Electrical and Electronics Engineering, SR Institute of Management and Technology, Lucknow, India.

Periodicity:July - September'2025

Abstract

This paper explores the design, development, and testing of a hardware model for a renewable energy-based DC microgrid, which incorporates Internet of Things (IoT) technology for efficient power management. By integrating renewable energy sources such as solar and wind, combined with energy storage, power conversion, and real-time monitoring, the proposed microgrid ensures seamless and automated power distribution. Using an ESP32 microcontroller, the system dynamically manages loads and transmission based on energy availability. The IoT-enabled infrastructure facilitates remote control and monitoring, enabling scalable and sustainable solutions for energy management. Experimental results validate the system's high efficiency and feasibility in real-world applications, making it a promising candidate for future smart grids.

Keywords

DC Micro Grid, Renewable Energy, IoT, Smart Grids, Power Transmission, Energy Storage.

How to Cite this Article?

Singh, B., Kamal, N., Mishra, Y., Kumar, A., and Sharma, V. (2025). Development of a Hardware Model for Renewable Energy-Based DC Micro-Grid with Automatic Power Transmission using IoT. i-manager’s Journal on Electrical Engineering, 19(1), 25-32.

References

[1]. Barik, A. K., & Das, D. C. (2018). Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm. IET Renewable Power Generation, 12(14), 1659-1667.

[2]. Chauhan, K., & Chauhan, R. K. (2017). Optimization of grid energy using demand and source side management for DC microgrid. Journal of Renewable and Sustainable Energy, 9(3).

[3]. Delfino, F., Rossi, M., Pampararo, F., & Barillari, L. (2016). An energy management platform for smart microgrids. In Intelligent Computing Systems: Emerging Application Areas (pp. 207–225), Heidelberg: Springer Berlin Heidelberg.

[4]. Farrokhifar, M., Aghdam, F. H., Alahyari, A., Monavari, A., & Safari, A. (2020). Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model. Electric Power Systems Research, 187, 106483.

[5]. Friansa, K., Haq, I. N., Santi, B. M., Kurniadi, D., Leksono, E., & Yuliarto, B. (2017). Development of battery monitoring system in smart microgrid based on internet of things (IoT). Procedia Engineering, 170, 482–487.

[6]. Hossain, M. K., & Ali, M. H. (2016). Transient stability augmentation of PV/DFIG/SG-based hybrid power system by parallel-resonance bridge fault current limiter. Electric Power Systems Research, 130, 89–102.

[7]. Jha, B. K., Tiwari, A., Kuhada, R. B., & Pindoriya, N. M. (2024). IoT-enabled smart energy management device for optimal scheduling of distributed energy resources. Electric Power Systems Research, 229, 110121.

[8]. Kiranvishnu, K., Sireesha, K., & Ramprabhakar, J. (2016). Comparative study of wind speed forecasting techniques. In 2016 Biennial International Conference on Power and Energy Systems: Towards Sustainable Energy (PESTSE) (pp. 1–6). IEEE.

[9]. Li, C., de Bosio, F., Chaudhary, S. K., Graells, M., Vasquez, J. C., & Guerrero, J. M. (2015). Operation cost minimization of droop-controlled DC microgrids based on real-time pricing and optimal power flow. In Proceedings of the 41st Annual Conference of the IEEE Industrial Electronics Society (IECON 2015) (pp. 3905–3909). IEEE.

[10]. Meng, N., Wang, P., Wu, H., Wang, W., & Xu, W. (2015). Optimal sizing of distributed generations in a connected DC micro-grid with hybrid energy storage system. In 2015 IEEE Energy Conversion Congress and Exposition (ECCE) (pp. 3179–3183). IEEE.

[11]. Moayedi, S., & Davoudi, A. (2016). Unifying distributed dynamic optimization and control of islanded DC microgrids. IEEE Transactions on Power Electronics, 32(3), 2329–2346.

[12]. Nguyen, T. A., & Crow, M. L. (2015). Stochastic optimization of renewable-based microgrid operation incorporating battery operating cost. IEEE Transactions on Power Systems, 31(3), 2289–2296.

[13]. Siano, P., & Mohammad, D. (2020). MILP optimization model for assessing the participation of distributed residential PV-battery systems in ancillary services market. CSEE Journal of Power and Energy Systems, 7(2), 348–357.

[14]. Singh, B., & Gupta, B. (2018). Review of DC microgrid technology and applications. IEEE Transactions on Smart Grid, 9(6), 2567–2579.

[15]. Vanitha, R., & Kalpana, P. M. (2019). IoT-based microgrid automation. International Journal of Latest Transactions in Engineering and Science (IJLTES), 8(3), 1–7.

[16]. Xing, L., Xu, Q., Guo, F., Wu, Z. G., & Liu, M. (2021). Distributed secondary control for DC microgrid with event-triggered signal transmissions. IEEE Transactions on Sustainable Energy, 12(3), 1801–1810.

[17]. Zhuang, J., Shen, G., Yu, J., Xiang, T., & Wang, X. (2017). The design and implementation of intelligent microgrid monitoring system based on WEB. Procedia Computer Science, 107, 4–8.

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Pdf	35	35	200	20
Online	15	15	200	15
Pdf & Online	35	35	400	25

Development of a Hardware Model for Renewable Energy-Based DC Micro-Grid with Automatic Power Transmission using IoT

Abstract

Keywords

How to Cite this Article?

References

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