The convergence of AI and the energy industry will have dramatic impacts on global consumers.

FREMONT, CA: Artificial intelligence is about to revolutionize lives, work, and leisure, but few understand what the technology can do beyond voice assistants. These are examples of weak AI technology, the most common of all AI applications. But in the data-driven energy industry, sophisticated machine learning is paving the way for strong AI to improve efficiency, forecasting, trading, and user accessibility. Here is more to it.

Electricity is a commodity that can be traded in markets. For these markets to run efficiently, large amounts of data from weather forecasting to grid demand-supply balance must be constantly analyzed by buyers, power sellers, and brokers. Those best positioned to analyze the data have a competitive advantage in the marketplace. Applying machine learning algorithms to wind power capacity is enough to power a city. Using a neural network that tapped into weather forecasts and historical turbine data could predict wind power output 36 hours in advance. In less than one year, machine learning algorithms increased their wind energy value compared to baseline scenarios.

Nearly half of power consumers in the United States have smart electrical meters, offering data about personal energy consumption to allow informed consumer self-regulation of energy usage. New AI-fueled smart meters and smart home platforms are not yet widespread but represent a potential boon to efficiency gains. These energy monitoring devices communicate with other devices, saving owners money by lowering energy waste. The devices controlling air conditioning, advising the charging of electric cars during hours with lower electric costs, controlling lighting, and managing appliances are all examples.

Artificial intelligence can enhance existing energy storage by making it easy to integrate distinct technologies, including renewable microgrids, utility-scale battery storage, pumped hydro, and many more. The role of energy storage in grids is growing along with the proliferation of intermittent power sources, putting a higher strain on power brokers to balance supply and demand. As the technology enhances and costs come down, smart energy storage plays a larger role in the grid’s ancillary services that help grid operators balance and support the transmission of energy from generators to consumers.

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