Pacific Gas & Electric (PG&E) is to deploy Fluence’s AI trading platform for optimisation and market bidding services for its 182.5MW/730MWh Moss Landing battery system.
California investor-owned utility PG&E is the first to install the trading platform, and the first in the California Independent System Operator (CAISO) market, following the acquisition of AMS.
Using artificial intelligence, advanced price forecasting, portfolio optimisation and market bidding algorithms, the software will ensure the system is responding optimally to market and reliability needs in the CAISO wholesale market.
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With updated price forecasts and optimised bids every hour, PG&E will maximise the value of the storage asset, as well as improve grid reliability and efficiency and support California’s transition to a more sustainable and resilient electric grid.
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“PG&E was one of the first utilities to appreciate the need for a sophisticated AI-enabled bidding technology to optimise its energy storage assets,” says Seyed Madaeni, chief digital officer of Fluence.
“This technology-agnostic software provides PG&E with a single tool that can optimise not only the Moss Landing project, but potentially entire portfolios of generation and storage resources to enhance affordability of resources.”
The trading platform, which can be used to optimise a variety of energy resources, is claimed to increase revenue and operational efficiency for battery-based energy storage by up to 50% and revenue for standalone renewable energy assets by over 10% via optimised wholesale market bidding.
It is currently used by energy asset owners to optimise approximately 15% of all wind and solar energy assets bidding into Australia’s National Electricity Market.
Fluence’s digital team tested the software’s integration with PG&E’s bidding and scheduling systems for the 4MW Yerba Buena and 2MW Vaca Dixon energy storage installations.
PG&E plans to begin using the software at Moss Landing when the project comes online later this year.