Investigating the effect of Sun Tracking on PV Voltage in Solar Installation using Microcontroller Prototype Model
Obasi Chijioke Chukwuemeka1, Ogbikaya Stephen2, Balogun Aizebeoje Vincent3, Chukwu Nnaemeka Paul4

1Obasi Chijioke Chukwuemeka, Department of Computer Engineering, Edo University, Iyamho, Edo State, Nigeria.
2Ogbikaya Stephen, Electrical Electronics Engineering Department, Edo University, Iyamho, Edo State, Nigeria.
3Balogun Aizebeoje Vincent, Mechanical Engineering Department, Edo University, Iyamho, Edo State, Nigeria.
4Chukwu Nnaemeka Paul, Department of the Computer Engineering Technology Department in the School of Engineering Technology of Federal Polytechnic Ekowe, Bayelsa State, Nigeria.

Manuscript received on 18 February 2018 | Revised Manuscript received on 27 February 2018 | Manuscript published on 28 February 2018 | PP: 41-44 | Volume-7 Issue-3, February 2018 | Retrieval Number: C5293027318/18©BEIESP
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Abstract: Weather monitoring is a global phenomenon and its impact world-wide cannot be over emphasized. The monitored parameters are always factored into result-based performance and efficiency. This efficiency can also be determined by the solar irradiance. Solar energy installations are some of the alternative energy generation strategy adopted globally, hence it is important to determine the location, size and position of the panel to ensure maximum solar irradiance. This work is aimed to study the effect of sun tracking solar installation on charging voltage using microcontroller. AT89S52 microcontroller was adopted to implement a model prototype for sun tracking solar installation during cloudy morning and sunny weather conditions. Readings from the prototype were used to characterize the cloudy and non-cloudy weather conditions. From the characteristic curves plotted, it was established that the optimum performance could be obtained during the cloudy morning and sunny afternoon. This further elucidates the impact of sun tracking in solar installations which could be beneficial to solar installation managers and scientists.
Keywords: Charging Voltage, Cloudy, Microcontroller, Prototype Model, Solar Installation, Sunny, Sun Tracking.

Scope of the Article: Machine Learning