BIG DATA MODELING OF THE OUTPUT OF SOLAR ENERGY FOR SMART GRID RELIABILITY

Abstract

A Smart Grid is an electricity grid that improves the power generation, distribution of power, and electricity consumption through the introduction of IT on the electricity grid. All this will cause vast data that will have to face by the energy companies. By using Big Data technologies, suitable solutions for utilities is offered, but it is critical to decide to use particular Big Data technology. The reliability of Smart Grid depends on the characteristics of both the demand (load) and the generation. The power generation by the conventional sources, such as thermal power plants is relatively stable and easily estimated. However, the power generation by renewable energy sources, such as solar and wind, is very dynamic and difficult to predict as it depends on the weather conditions. It’s very challenging to have a reliable smart grid under these unpredictable dynamic power generation, especially when the share of the power generated by solar increases. For a long time solar radiation predictions are done using MATLAB, the prediction of solar power using Big Data is a new methodology. In this paper using Big Data, Solar power is predicted with solar radiation as input variable. The Generation Patterns are observed in Tableau. Modeled and trained the historical data by using R programming language. The power generated by
the solar plant, can be predicted using Regression Model and results obtained are presented and analyzed.