Solar energy industries have benefited considerably from the potential of AI, machine learning predictive models, and data science.
FREMONT, CA: Climate change and the increasing depletion of nonrenewable energy sources are driving forces behind sustainable energy research and development, which affects all governments and businesses. Green energy generation is presently a vitally active and developing area of research. Solar energy is a well-known renewable energy source that is relatively easy to get and has fewer restrictions on purchasing and deployment. Solar energy production remains relatively expensive in comparison to fossil fuels. Energy storage methods are frequently insufficient to provide energy, extended storms, and overcast cloudy conditions throughout the night.
Solar energy systems and connected technologies have developed into a primarily utilized green energy source. Solar power is still not an extensively applied energy source compared to conventional energy sources, given the relatively high deployment costs, low conversion rates, and battery storage issues. Despite the hurdles, there are several innovative studies of new technologies like
machine learning, artificial intelligence, big data, IoT, and new ways for enhancing solar energy transformation efficiency to better the competitiveness of solar power in the marketplace.
Artificial intelligence (AI) and machine learning (ML) have become essential technology solutions. The sector is constantly looking to cater to the quickly increasing demand for clean, cheap, and reliable power. These advanced technologies can analyze the past, streamline the present, and predict the future. This means that AI and ML can remediate most of the hurdles in the solar sector.
With technology making quick advancements, the renewable power sector has made significant progress in the past decade. However, a few hurdles still prevail that can be addressed with the assistance of AI and ML. There is no doubt that the demand for solar power will increase shortly, making it more vital to invest in emerging technologies, including AI, ML, and IoT, to enhance productivity and overcome the shortfalls.
