Design and construction of a maximum power point tracking system (MPPT) with neural network with forward approach to improve solar energy supply in the navy and practical comparison of power reception in different modes

With the increasing use of solar energy and its many benefits, the use of this new energy in ships has been considered.One of the ways to increase the reliability of the ship is to have a suitable power in all weather conditions of the sea, and naturally in the photovoltaic system, to maximize the energy that can be received from them per kilowatt of power is installed, because the voltage characteristic Solar cell flow is strongly dependent on radiation and cell temperature. On the other hand, load changes also change the operating point and cause deviation from the maximum power point. Therefore, in various articles, much attention has been paid to maximum power methods in photovoltaic systems.In this paper, a new strategy for tracking the maximum power point by feed-in method is proposed, relying on the capabilities of the neural network to use this energy at sea. The feeder approach prevents noise propagation in the network because it is forward and has no feedback. The previous methods do not have the ability to accurately track the maximum power point in the event of turbulence or sudden changes in sunlight. Solar vessels change abruptly, have applications that improve its performance, and simulation and performance results show that the maximum power is received in this method.