2002 · 13 citations · 5 references
EngineeringElectrical EngineeringEnergy SystemsPower ElectronicsRenewable Energy SystemsDc-ac InvertersPower Electronics For Renewable EnergyRenewable Energy Power ConversionRenewable Energy TechnologySolar Energy SystemsSolar Photovoltaic SystemsDuty Cycle ControlGrid-connected Photovoltaic SystemsMaximum Power OutputMaximum Power Point TrackingNeural Network ControlPhotovoltaic Energy SystemsPhotovoltaic SystemsVoltage
The propose of this work is to describe the implementation of a controller for tracking the point of maximum power transfer based on neural networks, using a microcontroller of the PIC family, on energy systems that use photovoltaic panels. A neural network is used to determine, at each instant, the output voltage in a DC-DC boost converter connected to the solar panels, in way to obtain the maximum power transfer of these panels. This implementation releases the use of a great performance computer, once the neural network was already trained and this way, it can be implemented in a dedicated system. The maximum power transfer of the system is obtained adjusting the duty cycle of the DC-DC boost converter. One three-phase inverter was implemented with a new control circuit to generate the PWM signal.
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Neural networks: A comprehensive foundation
Ryszard Tadeusiewicz · Control Engineering Practice · 1995 · 7.3K citations