Applications of Machine Learning in Harnessing of Renewable Energy

Nonrenewable sources of energy are depleting rapidly as the ratio of their consumption is higher than its reproduction as it takes millions of years to replenish, high demand, and utilization in agriculture and industries have affected the environment drastically. To fulfill the growing demand and necessity of energy for the continuous process of production and manufacturing promoted the use of renewable sources of energy, but renewable sources of energy need more development to be used with its full potential despite its massive availability. Fortunately, evolution in artificial intelligence has conferred scientists and developers to come up with several methods and improvements in the effective, efficient, and optimized usage renewable energy sources. This paper explores the areas of machine learning application for the effective harnessing of renewable energy sources such as wind energy, geothermal energy, solar energy, and wave energy.