A study on renewable energy generation for decentralized grid resources and services

Abstract

Energy has always been the fuel of our civilization. Without electricity, heat, and all other types of energy, running our modern society would be impossible. In recent times, there has been a surge in the use of renewable energy instead of coal, which is essential for the future of renewable energy and the health of the environment. Energy has always been a key factor in the health and development of nations. Engineers are trying to develop new technologies to produce clean energy. Renewable energy, sunlight, refers to water, precipitation, the energy to be utilized to convert the fossil fuel for energy and used in existing for the use by the conversion to renewable energy, such as biological organisms. There are several types of renewable energy, including solar energy, wind power, water power, fuel cells, wave energy, and bio-energy, all of which permit the conversion of renewable resources into electric power. Although renewable energies are considered the most valuable alternatives to fossil fuel, there are difficulties associated with them, such as the variable and uncontrollable generation of energy from most renewable sources. These characteristics result in problems with managing energy when NRE power plants are connected to the main grid. Thus, predictions of the amount of renewable energy that will be generated using weather data are valuable in helping to incorporate NRE in smart grids. In this paper we will discuss how scientists can predict the amount of renewable energy that will be generated using mathematical models and weather databases. We will also use the R language to produce linear regression models that can help us understand power generation given weather data from 2007 to 2014. Our focus is on generation by solar photovoltaics and we test our models to make sure that the predictions are reliable. © 2016 International Information Institute.