A simple neural network solar tracker for optimizing conversion efficiency in off-grid solar generators

Abstract

A new model of neural network and a new type of neural controller are proposed, aiming to reduce cost and complexity without sacrificing efficiency of traditional, more complex neural net-based solar trackers.

The solution is derived from Mark Tilden’s neural and nervous networks, using a biologic analogy to seamlessly integrate sensors, artificial neurons and effectors in a single, efficient device.

Testing is in progress at the time of the elaboration of this paper but available and relevant preliminary results are shown. The project aims to develop a small pilot tracker – based solar plant for testing purposes and to develop a useable technology for the ever-growing demand for green power.