Blog: How the Application of Artificial Intelligence is Impacting Renewable Energy
The implementation of artificial intelligence (AI) is impacting renewable energy in important ways. According to a report from the International Energy Agency, global electricity generation from renewable energy sources like wind, solar, hydro, and geothermal is expected to see a 26 percent increase by 2020.
As a business owner seeking to reduce your company’s carbon footprint, it is vital for you to find ways to become more energy efficient. Consider how this may be possible through the implementation of AI technology and renewable energy sources.
Case Study: UK National Grid
In 2016, Britain’s electricity production “was the cleanest it had been in 60 years”as most energy production came from solar and wind power. However, they experienced issues with renewable energy sources like solar and wind power. One downside to using solar power is the sun is not always shining, and this meant they weren’t able to meet demand surges like traditional power methods would. As a result, their grid operator system continually met the power demand through coordinationwith conventional power stations to operate at “below maximum potential output and ramp up as needed.”
Implementing Artificial Intelligence
Artificial intelligence uses algorithms and machine learning to mine and analyze data to execute better decision-making processes for improved results. It is positively impacting wind, solar, hydro, geothermal, and biomass production to create more sustainable ways to generate efficient power.
1. Intelligent Wind Power
AI and smart data mining can create extremely precise forecasts that enable augmented incorporation of this renewable energy resource into the power grid to help reduce our carbon footprint and optimize energy costs.
2. Intelligent Solar Power
Radiant energy is produced from sunlight during the day and captured in solar panels, then converted to electricity or thermal power. Solar power is the cleanest and most plentiful renewable resource we can use to reduce our carbon footprint. Energy from the panels is used, then what is not consumed in the evening is stored to use later. A smart grid converter is an intelligent hybrid component that effectively controls solar power energy storage and usage.
3. Intelligent Hydro Power
Digitization in hydro power is making this renewable resource more innovative and efficient. Enhanced adaptability and precise data mining is important in monitoring the performance of hydropower turbines and plant equipment. Pioneering AI and machine learning uses data mining to enhance the operational systems of the plant, execute actionable perceptions from analyzed data, and increase energy efficiency.
4. Intelligent Geothermal Power
The geothermal power market is expected to increase to $7.71 billionby the end of 2017. The earth generates and stores geothermal energy, and this renewable resource is globally sustainable. However, extraction of geothermal power requires precise monitoring to prevent depletion in the local area. Approximately 90 percent of residences in Iceland are powered by geothermal energy. Artificial intelligence and machine learning is being used for geothermal explorationto mine data from GIS and GPS studies, and land surveys, to ascertain the ideal inspection sites.