Solar panel is a power source having nonlinear internal resistance. As the intensity of light falling on the panel varies, its voltage as well as its internal resistance both varies. To extract maximum power from the panel, the load resistance should be equal to the internal resistance of the panel. Maximum power point trackers (MPPT)are used to operate a photovoltaic panel at its maximum power point in order to increase the system efficiency. This paper presents the improved model of solar photovoltaic (SPV)module and back propagation neural network based maximum power point tracking (MPPT)for boost converter in a standalone photovoltaic system under variable temperature and insolation conditions. Neural network has the potential to provide an improved method of deriving non-linear models which is complementary to conventional techniques. The neural network based MPPT is simulated and studied using MatLab software.