Artificial Intelligence Platform Cuts Energy Bills for Heavy Building Materials Firm

artificial intelligence
(Photo: Aggregate Industries. Courtesy of Open Energi)

Artificial intelligence is expected to save heavy building materials company Aggregate Industries 10% on annual electric bills and energy intensity, reports. The UK-headquartered company has added Open Energi’s Dynamic Demand 2.0 to 30 bitumen tanks across eight sites.

The technology works by using the flexibility inherent in the tanks’ normal heating and cooling cycle and adapts that to lowering energy intensity, Edie explained. Artificial intelligence in the platform optimizes electricity use in response to fluctuations in factors such as grid frequency, wholesale electricity prices, and system imbalance prices.

“The platform accesses the imbalance market via Renewable Balancing Reserve (RBR), an Ørsted product which incentivizes businesses to reduce their electricity demand at certain times through financial rewards,” Edie reported.

On average, Aggregate Industries’ assets are responding to three 30-minute RBR calls a day, Open Energi says.

Aggregate Industries’ energy manager Richard Eaton said that he expects the company to install Open Energi’s technology in 48 of its UK asphalt plants, representing up to 4.5 MW of demand flexibility.

The company is an early adopter, Edie reported. Since 2013, Aggregate Industries has applied firm frequency response services to 133 bitumen tanks at 42 of asphalt plants in the United Kingdom.

“Eaton previously told Edie that through better management of assets, the move has provided 4 MW of real-time flexible capacity to the grid and facilitated an energy consumption reduction of 350,000 kWh per year in the process,” the site says.

In addition to expanding the use of Dynamic Demand 2.0, Aggregate Industries is also looking at where the technology could be beneficial for their other assets and processes, according to Eaton.

“As energy markets evolve, it’s important we keep up with the pace of change,” he said.

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