A novel power optimized hybrid renewable energy system using neural computing and bee algorithm

ABSTRACT With rapid depletion of non-renewable energy resources or the fossil fuels like coal, petroleum etc., there has been a significant shift in innovations towards exploiting and tapping of energy from renewable energy resources like sun, bio gas, wind etc., E Off late, there has been an increased research towards combined or hybrid integrated energy generation systems based on renewable resources like sun-wind, sun-biogas etc., These hybrid systems effectively address the past demerits observed in standalone systems which could provide substantial power only during specific periods and seasons. For example, solar power would be much reduced during the night time. Hence hybrid systems effectively counteract this issue as the lack of stability in one system is well compensated by the other. This research paper proposes an optimized hybrid PV-wind power generation system with optimization towards maximization of power generated from the system with the help of neural architecture and bee colony algorithm. The proposed system has been implemented and tested for a wide range of solar irradiances and wind velocities and maximum and stable power generation has been observed when compared to existing techniques