Abstract
Renewable energy resources like wind, sun, hydropower, geothermal, and biomass are better alternatives for conventional non-renewable energy resources such as fossil fuel reserves. Renewable energy resources are the better technological option to generate clean energy and overcome the depletion of non-renewable energy resources. This paper presents the complete system design of hybrid solar wind charger. The main contribution is to develop a compact system, which utilizes the eternal solar and wind power to solve the major crisis of pollution as well as the scarcity of fossil fuels. The functionality of the proposed system allows a reliable source of power generation for human beings in the energy crisis.
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References
Arjun A, Athul S, Ayub M, Neethu R, Anith K (2014) Micro-hybrid power systems—a feasibility study. J Clean Energy Technol 3(1):27–32
Balaji TS, Damodhar, Sethil Kumar A (2015) Design of high step up modified for hybrid solar/wind energy system. Middle-East J. Sci Res 23(6):1041–1046
Jenkins P, Elmnifi M, Younis A, Emhamed A (2019) Hybrid power generation by using solar and wind energy: case study. World J Mech 9:81–93
Ataei A, Biglari M, Nedaei M, Assareh E, Choi JK, Yoo C, Adaramola MS (2015) Techno-economic feasibility study of autonomous hybrid wind and solar power systems for rural areas in Iran, a case study in Moheydar village. Environ Prog Sustain Energy 34:1521–1527
Mohamed A, Al-Habaibeh H (2013) An investigation into the current utilization and prospective of renewable energy resources and technologies in Libya. Renew Energy 50:732–740
Fatema N et al. (2021) Intelligent data-analytics for condition monitoring: smart grid applications. Elsevier, p 268. ISBN:Â 978-0-323-85511-2. https://www.sciencedirect.com/book/9780323855105/intelligent-data-analytics-for-condition-monitoring
Smriti S et al (2018) Special issue on intelligent tools and techniques for signals, machines and automation. J Intell Fuzzy Syst 35(5):4895–4899. https://doi.org/10.3233/JIFS-169773
Yadav AK et al. (2020) Soft computing in condition monitoring and diagnostics of electrical and mechanical systems. Springer Nature, Berlin, p 496. https://doi.org/10.1007/978-981-15-1532-3. ISBN 978-981-15-1532-3
Gopal et al. (2021) Digital transformation through advances in artificial intelligence and machine learning. J Intell Fuzzy Syst Pre-press 1–8. doi: https://doi.org/10.3233/JIFS-189787
Jafar A et al. (2021) AI and machine learning paradigms for health monitoring system: intelligent data analytics. Springer Nature, Berlin, p 496. https://doi.org/10.1007/978-981-33-4412-9. ISBN 978-981-33-4412-9
Sood YR et al. (2019) Applications of artificial intelligence techniques in engineering, vol 1. Springer Nature, p 643. doi: https://doi.org/10.1007/978-981-13-1819-1. ISBN 978-981-13-1819-1)
Aggarwal S et al. (2020) Meta heuristic and evolutionary computation: algorithms and applications. Springer Nature, Berlin, p 949.doi: https://doi.org/10.1007/978-981-15-7571-6. ISBN 978-981-15-7571-6
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Sharmila, Gautam, M., Raheja, N., Tiwari, B. (2022). Hybrid Solar Wind Charger. In: Tomar, A., Malik, H., Kumar, P., Iqbal, A. (eds) Machine Learning, Advances in Computing, Renewable Energy and Communication. Lecture Notes in Electrical Engineering, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-16-2354-7_37
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DOI: https://doi.org/10.1007/978-981-16-2354-7_37
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