Optimizing grid-scale battery placement via quantum computing

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From ESS News

Spanish energy giant Iberdrola has tested quantum computing for optimizing the placement of large-scale batteries into the grid for cost, voltage control, and reliability. Accurately modeling large-scale grids and the elements of renewables and storage are notoriously strenuous tasks for classical computing.

A 10-month pilot program between i-DE, Iberdrola’s distribution company in Spain, and quantum computing software company Multiverse Computing, scaled up from small-sized grids to eventually focus on the Gipuzkoa electricity grid, in Basque Country, in northern Spain. The project was also part of the Basque Country Gipuzkoa council’s quantum program.

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The bumper June 2024 edition of pv magazine examines the state of national grids across key European markets as the region’s solar boom continues, considers the role small-scale PV arrays are playing in transforming the energy systems of Brazil and China, and studies the rising importance of artificial intelligence and algorithms when generating grid-related revenue from battery sites.

Multiverse Computing adapted algorithms to run on a quantum annealer, a type of quantum computer, and on classic hardware, to test optimization solutions. The focus, of the company’s report, was to achieve improvements in grid batteries across three key areas: initial cost, voltage control, and reliability.

When optimizing on costs, for example, the target was to reduce the cost of buying and installing multiple batteries in the grid. For reliability, the target was to minimize the impact on grid customers of power outages.

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