Methods and software for solar power plant cluster management

Abstract

Object is solar power plant management software. Nowadays, solar panel production technologies are developing rapidly, investments in solar energy are growing, so users are interested in increasing energy production for faster return on investment. To increase the efficiency of solar panels, special rotating mechanisms are used to rotate the panel perpendicularly to the sun rays. This allows users to significantly increase the amount of energy produced by the panel over time. This article considers ways to increase the efficiency of solar panels’ energy generation by using a minimum number of additional sensors. The article describes the solar power plant monitoring system which uses machine learning to resolve sun tracking problem. The advantages and disadvantages of a prototype are analyzed. The concept of microservices is described and the benefits of using it in the developed system are given. Different approaches to increase speed, quality and reliability of such systems are investigated on the example of a prototype. Efficiency of using proposed approaches has been tested on a solar simulator. Ref. 5, pic. 5.

Keywords

• Solar power plant
• solar power plant monitoring
• reinforcement machine learning
• q-learning
• parallel programming
• threads, microservices