Online Tracking of Maximum Panel Power Output in Photovoltaic Stand Alone System with Different Insolation

In solar photovoltaic stand - alone system the basic device is the PV module which is used to charge the storage device during daytime and supplies power to the load during dusk to dawn. This paper presents knowledge based system for evaluating power generation system in PV model. The performance of a PV system depends on the environmental factors such as irradiation and cell temperature. It is a non-linear characteristic and this characteristic is varied in different PV technologies. To solve this problem, an intelligent technique called the Artificial Neural Network (ANN) can be talented solution for obtaining the maximum output power in real-time operation. Initially this work focuses on the simulation of characteristics of the panel power output of PV module at different level of radiation. Thus panel power output is evaluated different level of radiation and the simulated characteristics are figure with the 3D nomogram analysis. The database device using microcontroller is designed as per the simulation studies and it is attached in the solar panel to monitor the real time value of PV standalone system. The above mentioned simulated comparison is validated with results of local climatic data and its accuracy of the proposed methods has been measured with the error estimation method. Thus the proposed method will be very useful for determining the real-time optimum operating condition of PV system with estimated maximum power generation.