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September 29, 2023
The US Department of Energy has agreed to supply up to US$3.3 billion in loan funding to US residential solar developer Sunnova.
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September 28, 2023
The US Energy Information Administration has published its latest monthly report into the country’s energy mix.
July 18, 2023
PVCase has closed its latest funding round, raising US$100 million from investors Highland Europe, Energize and Elephant.
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April 17, 2023
Procuring power purchase agreement tools will be an option for industry players amid an energy pricing crisis and volatility.
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February 9, 2023
While collecting verified bottom-up project data in real time has previously been cost-prohibitive, satellite data can now be leveraged to make comprehensive market intelligence attainable for investors. Daniel Cruise and Joseph Triepke, partners at energy intelligence firm Lium Research, reveal how satellites can provide more reliable insights into the construction of US utility-scale solar projects.
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December 1, 2022
Enerparc’s Yoojin Lee reveals how the company’s artificial intelligence approaches are used to make day-ahead forecasts more accurate.
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July 7, 2022
PV Tech Premium spoke with Lawrence Berkeley National Laboratory (LBNL) about the i2X programme to provide some added clarity on the main challenges the US interconnection system faces.
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March 3, 2022
Last year analysis by renewables performance aggregator and insurance provider kWh Analytics highlighted the extent of solar asset underperformance against P50 estimates in the US. Here, the company’s Sarath Srinivasan details some of the reasons behind that underperformance.
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December 28, 2021
Accurate generation modelling and forecasting is integral to not just the financial performance of operational solar farms, but how they are integrated into modern grids. A study from Monash University in Australia has proven how artificial intelligence approaches can help drastically improve performance forecasts. Dr. Christoph Bergmeir, who led that study, details its key learnings.
July 19, 2021
Machine learning techniques have been used in a study to boost the accuracy of renewables forecasts by up to 45%, helping improve grid operations in Australia.

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