A New Controller to Enhance PV System Performance Based on Neural Network - Roshdy A AbdelRassoul; Yosra Ali; Mohamed Saad Zaghloul (Renewable Energy and Sustainable Development)
In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system. Neural controller is optimized using particle swarm optimization (PSO)   leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become 0.00001% and 0.1798 seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.In recent years, a radical increase of photovoltaic (PV) power generators installation took place because of increased efficiency of solar cells, as well as the growth of manufacturing technology of solar panels. This paper shows the operation and modeling of photovoltaic systems, particularly designing neural controller to control the system. Neural controller is optimized using particle swarm optimization (PSO)   leads to getting the best performance of the designed PV system. Using neural network the maximum overshoot and rise time obtained become <span style="color: #1d2129; background-image: initial; background-attachment: initial; background-size: initial; background-origin: initial; background-clip: initial; background-position: initial; background-repeat: initial;">0.00001% and <span style="color: #1d2129; background-image: initial; background-attachment: initial; background-size: initial; background-origin: initial; background-clip: initial; background-position: initial; background-repeat: initial;">0.1798 seconds, respectively also this paper introduce a comparison between some kind of controller for PV system.