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Stream/Area:
-
Subject:
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Paper ID:
IJSREM68568
Volume:
10 |
10 |
Oct 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Department Of Electrical Engineering
Trinity College of Engineering and Research
Photovoltaic (PV) and wind generation are attractive clean sources, but each one fluctuates with the weather. Pairing them on a shared electrical platform together with a battery can give a steadier supply than either source achieves alone. This paper reviews seven published studies that cover six connected themes: solar–wind hybridization, multi-criteria sizing by particle swarm optimization, real-time energy management under pulse loads, a smart hybrid supply for telecom base stations, smart-grid integration of renewable sources, and monitoring based on artificial intelligence (AI) and the Internet of Things (IoT). The studies agree on the importance of correct component sizing, well-chosen converter interfaces, coordinated use of storage, accurate measurement and a reliable communication path. Drawing on these lessons, the paper outlines a laboratory-scale hybrid generator built from a solar PV panel, a small wind turbine, a battery, power converters and an ESP32 microcontroller that reads voltage and current sensors at the source, battery and load branches. A test plan and three performance indicators, namely renewable contribution, efficiency and load availability, are defined for later experimental use. The review also records open issues: limited field validation, differing assumptions between studies, sensor and data quality, and the gap between displaying data and actually controlling energy flow.
KEYWORDS
This paper examined seven studies spanning solar–wind hybridization, multi-objective sizing, real-time energy management, smart-grid integration, micro grid monitoring and AI/IoT techniques. Across them, source integration, suitable power conversion, coordinated storage and reliable measurement emerge as the main requirements for making better use of renewable energy. The literature also shows that model assumptions, site conditions, communication limits and scarce field validation restrict how widely the results can be applied. A solar–wind system that pairs battery storage and converters with an ESP32 and voltage/current sensors is a practical way to watch how renewable generation and the load behave. It should be evaluated with timestamped measurements under several operating conditions, and efficiency, renewable contribution and load availability should be computed from stated definitions and measured data. Future work may add source forecasting, validated anomaly detection, optimized sizing and closed-loop energy management once the basic measurement and protection functions are verified.
[1] M. I. Hossain, A. Hossain, T. H. Galib, and A. Hoque, “Hybrid power generation using multiple sources of energy: Bangladesh perspective,” in Proc. 2013 Int. Conf. Informatics, Electronics and Vision (ICIEV), 2013, pp. 1–5, doi: 10.1109/ICIEV.2013.6572571. [2] L. Wang and C. Singh, “Multicriteria design of hybrid power generation systems based on a modified particle swarm optimization algorithm,” IEEE Trans. Energy Convers., vol. 24, no. 1, pp. 163–172, Mar. 2009, doi: 10.1109/TEC.2008.2005280. [3] A. Mohamed, V. Salehi, and O. Mohammed, “Real-time energy management algorithm for mitigation of pulse loads in hybrid microgrids,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 1911–1922, Dec. 2012, doi: 10.1109/TSG.2012.2200702. [4] P. Diamantoulakis, M. A. Ghassemi, and G. K. Karagiannidis, “Smart hybrid power system for base transceiver stations with real-time energy management,” in Proc. IEEE Global Communications Conf. (GLOBECOM), 2013, doi: 10.1109/GLOCOM.2013.6831494. [5] A. Shahid, “Smart grid integration of renewable energy systems,” in Proc. 2018 7th Int. Conf. Renewable Energy Research and Applications (ICRERA), 2018, pp. 944–948, doi: 10.1109/ICRERA.2018.8566827. [6] Z. Nishtar and J. Afzal, “A review of real-time monitoring of hybrid energy systems by using artificial intelligence and IoT,” Pakistan J. Eng. Technol., vol. 6, no. 3, pp. 8–15, Sep. 2023, doi: 10.51846/vol6iss3pp8-15. [7] P. García, P. Arboleya, B. Mohamed, A. A. C. Vega, and M. C. Vega, “Implementation of a hybrid distributed/centralized real-time monitoring system for a DC/AC micro grid with energy storage capabilities,” IEEE Trans. Ind. Informant., 2016, doi: 10.1109/TII.2016.2574999.
Publication Date
10/31/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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