Sensorless MPP Estimation Method for Reserve Power Control in Photovoltaics

The penetration of photovoltaics in the power system is increasing exponentially, this kind of heavy penetration of the photovoltaics can affect the inertia of the power system adversely as, unlike synchronous generators, the photovoltaic units are static in nature. Therefore, many researchers are working on the converter level control of photovoltaic systems to mimic the inertial capability of the synchronous generators. The problem faced during the deloading of photovoltaics is the continuous requirement of estimation of maximum power point, the maximum power point is required all the time in the system to calculate the amount of power reserve for optimal operation. Therefore, the prediction of the maximum power point under reserve operation of the photovoltaic system is still a debatable task, in this paper, a neural network based sensor less maximum power point estimation techniques is presented. The method aims at accurate estimation of maximum power point under power reserve operation of photovoltaic systems and lowering the cost of system by making the neural network control independent of irradiance and temperature sensors. The developed photovoltaic control is validated with the help of simulation results. The simulations are performed on the SIMULINK toolbox of MATLAB software.