Enhancement of a Photovoltaic System and Wind Turbine Utilising a Sensor Tracking Mechanism

The constraints of electrification in Sub-Saharan Africa impede socio-economic development, as the absence of access to dependable energy sources constitutes a major obstacle. This work tackles this problem by developing and evaluating a hybrid photovoltaic (PV)-wind turbine system that use sensor-based tracking to improve energy harvesting efficiency. The suggested system has dual-axis solar tracking to position photovoltaic panels towards the sun and an adaptive wind yaw control system to align the wind turbine with the dominant wind direction. A comparative analysis was carried out utilising HOMER Pro software for techno-economic optimisation and MATLAB/Simulink for modelling and simulation in order to assess the system's performance. The outcomes show that compared to a stationary, non-tracking system, the sensor-optimized setup works noticeably better. In particular, the sensor-tracked system reduced the cost per kWh by 22%, increased energy production by 27.3%, and decreased system downtime by 19%. The sensors' real-time modifications, which optimise the capture of intermittent renewable energy, are responsible for this performance improvement. The study comes to the conclusion that integrating sensor-based tracking is a workable and scalable way to build economical and successful microgrids in climate-variable areas like Nigeria, which would help with off-grid electrification that is sustainable.