Optimization of Renewable Energy Integration Using AI Techniques

Abstract

The green energy sources aren't always available, adding them to current power systems is very hard. To solve this problem, many AI methods have been suggested as the best way to add green energy sources like wind and sun to the power grid. An in-depth look at how AI can be used to make the best use of green energy sources in power systems is given in this study. One of the most important AI methods used in this case is machine learning, which can be used to predict how much renewable energy will be produced and how much will be needed. This lets renewable energy supplies be better scheduled and managed. Optimization algorithms, such as genetic algorithms and particle swarm optimization, are another important type of AI. They can be used to find the best places for and sizes of green energy sources in the power grid. In addition, AI methods can be used to make power systems that use a lot of green energy sources more stable and reliable. AI-based control methods can be used to lessen the effect of changes in green energy output on the power grid, for example, making sure that there is a steady supply of electricity. This paper talks about how AI methods could be used to make the best use of green energy sources in power systems. By using AI, we can get around the problems that come with combining green energy sources and speed up the move to a future with sustainable and low-carbon energy.