Hitachi Energy Launches AI-Powered Energy Forecasting ToolHitachi Energy Launches AI-Powered Energy Forecasting Tool

Hitachi Energy has introduced Nostradamus AI, an AI-powered energy forecasting tool designed to derive value from the escalating amounts of data generated by the energy sector.

The energy industry faces mounting challenges, including increasing demand, the integration of renewable energy sources and the need for grid stability amidst market volatility.

Energy producers, utilities and traders need to navigate these complexities as the amount of data grows exponentially. For example, wind turbines generate more than 400 billion data points annually, according to the International Energy Agency (IEA). Smart meters are also generating growing amounts of data.

Simultaneously, renewable energy sources bring variability to the grid, complicating the task of balancing supply and demand. AI offers a way to process these massive datasets effectively, improving forecasting accuracy and helping organizations meet energy security and decarbonization goals.

Nostradamus AI incorporates historical energy market data with machine learning techniques to deliver forecasts that are over 20% more accurate than some industry benchmarks, according to Hitachi. Users can also input their own data alongside third-party sources to customize forecasts for various scenarios, including system load, renewable generation and market pricing.

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The tool uses regression-style forecasting, a statistical method that enables the exploration of the relationship between two or more variables, providing results that are accurate and easy to interpret.

Nostradamus AI has a cloud-native design that enables scaling from single-use forecasts to carrying out thousands of predictions simultaneously. It can also readily integrate with existing systems and APIs.

Target applications for Nostradamus AI include enhancing resource planning and operational efficiencies for utilities and optimizing renewable generation predictions for energy producers. It also aims to support system operators to ensure grid reliability and transparency for regulatory compliance and helps traders refine market strategies with precise pricing forecasts.

This article was first published in IoT World Today's sister publication AI Business.