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Home - Technology - Dexter Energy adds battery support to prediction, PV Power Optimization Platform – PV Magazine International
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Dexter Energy adds battery support to prediction, PV Power Optimization Platform – PV Magazine International

solarenergyBy solarenergyJuly 11, 2025No Comments3 Mins Read
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The Dutch company says that its short-term trading solutions for solar and other technologies for renewable energy, supports the balance between grid, reduces the costs of imbalance and optimizes energy flows in an “ever-volatile” energy market. It grows internationally and expands its support of battery -related trade.

July 11, 2025
Valerie Thompson

Dexter Energy, a developer-based developer of short-term power and optimization of solar, wind and storage activa, is expanding with plans to enter new geographical markets and to stimulate its software platform with battery activa-related trade and to optimize existing products.

The Amsterdam -based company offers advanced machine learning and optimization software that is used by utility companies, offtakers and independent power producers (IPPs) to support prognoses and short -term trade.

The platform uses predictive artificial intelligence (AI), a mix of advanced machine-learning techniques, such as gradient-reinforced decision trees, deep neural networks and probabilistic time series models, to prediction of the power, energy prices in the short term, more energy-overweights, more energy-overweights, more energy-overweights.

It claims a “very accuracy” prediction system. “We know that our power forecast is very accurate because our customers confirm this consistently. To convince new customers to use our electricity forecast, we have to compete from top-to-head in tasting with other predictors,” Veenen said PV Magazine. “The fact that we have succeeded in doubling our predicted capacity every year over the past five years is also proof that we can fulfill our claims.”

Veeken explained that the Dexter Energy products were designed to provide the energy needs supported by assets with regard to Kannibalization, negative place and non -losses, together with the demand patterns of the sun bringer curve and their effect on prices.

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“Our products help the producers of renewable energy by navigating this new reality and minimizing their equilibrium costs. Our power forecast helps our customers to lower their imbalance volume, reducing the risk of open positions in the balancing market and the financial fines that are connected to them,” he said.

Briefing, the name of another Dexter energy tool, offers signals to customers about when deliberately reduces the overproduction when it is optimal financially.

“These models learn from enormous flows of weather data, market prices and real-time scada data. All heavy lifting is done in our secure cloud environment, so there is no own hardware to install. Traders simply pull the signals via a Rest-api,” said Veeken, referring to a representative state transfer (Api) Application to the internet.

Dexter Energy, founded in 2017, announced this month that it will invest in further growth, expanding the company throughout Europe, further developing its existing products and further increasing support for trade with battery storage. It raised a series of C round of venture capital of € 23 million ($ 27.04 million) from a group of Dutch and international institutional investors to achieve its goals. The company claims more than 80 energy companies as customers, including Sunburn and Pure Energie, both based in the Netherlands, the British Centrica-Energy and Luminus energy based in Belgium.

A Dexter Energy short -term prediction for an anonymized solar port folio of 40 assets on top of the actual performance.

Image: Dexter -Energy

This content is protected by copyright and may not be reused. If you want to work with us and reuse part of our content, please contact: editors@pv-magazine.com.

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See also  Longi wins tender for 800 MW Hexi solar panels – SPE
adds battery Dexter Energy International magazine optimization platform power Prediction support
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