How AI for the Electric Industry Opens Up New Possibilities for Renewables
- Jun 19, 2020 3:42 pm GMT
Artificial intelligence (AI) and renewable energy are two pillars of the future. Each represents progress toward a cleaner, more efficient world. Though they are part of different fields within technology, AI and renewable energy can overlap. AI gives new possibilities to renewable energy that can bring sustainability to the energy industry's forefront in innovative ways.
Solar and wind power are two of the most common renewables that businesses and homeowners turn to for energy and electricity. If industry experts begin integrating AI with these two energy sources, other renewables would be quick to follow. With AI, renewable energy can accomplish more — from predictive analysis to blackout monitoring.
Sustainability is at the center of energy conversations around the globe. Within those discussions, renewable energy is inherent — without it, sustainability and environmental protection will not succeed. Both sustainability and renewability together are necessary. By itself, this movement is powerful. With AI, though, it can achieve more.
AI is the other movement at the forefront of conversations. It revolutionizes businesses and industries, operates new technology and changes platforms. As AI devices continually learn and improve with their abilities, business owners and individuals see the importance of the innovation.
Though AI is an industry trend on its own, it's now time to merge the two. Together, AI and renewable energy can start a new movement that combines two factors to combat climate change — new technology and sustainability.
How AI Can Help
Renewable energy is powerful, but AI can transform it in new ways with computing and storage capabilities as well as data collection. With these functions, AI creates a platform for smart grids, predictions, pattern recognition and reliability.
A smart grid is the result of full AI integration. It's a network of systems that connect the grid to the consumer and allows for real-time monitoring of energy flow, storage and data collection. A smart grid distributes energy privately or publicly, depending on the setup. Experts can tack the information to see the performance levels of the grid. For instance, AI can prevent blackouts since workers can see energy levels fluctuating and act accordingly and proactively.
AI itself can act in advance as well. With renewables like solar and wind, some critics remain skeptical of weather patterns and instances of no sun or strong enough winds. With predictive abilities and data, AI can detect current and future weather patterns. From there, it can store energy in the grid as needed and use it in instances of cloudiness or still air.
Then, pattern recognition comes from deep learning. This capability aids supply and demand levels. As AI detects how consumers use energy and how the grids supply it, it can better regulate each side. If consumers show a pattern of increased energy use, AI can help suppliers meet that demand.
Last, reliability is key for energy operations. AI enables predictive maintenance for the grid. With this feature, workers can monitor the mechanics and materials. The system will able to predict which parts need replacing as well as their level of health. This feature will save money as well as allow the renewables to work as efficiently as possible.
With AI working to help renewable energy, three areas benefit. This integration will expand the market and growth of renewables, creating more sustainability. Businesses and homeowners benefit from pricing, as renewable energy has a significant return on investment (ROI) with the correct implementation. Plus, users of the energy grid will reduce their carbon footprint and contribute to environmental protection. AI is now what boosts these factors for the best form of renewable energy.
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