The energy landscape is changing rapidly. With climate volatility growing and demand for electricity rising, the sector is increasingly using renewable sources to generate energy, which is forcing providers to rethink how they manage infrastructure and deliver services. Renewable energy sources, such as wind and solar, are inherently weather-dependent. Consequently, providers must now be able to accurately predict weather forecasts at greater speed and scale to continue delivering reliable services to customers. To analyse vast volumes of complex environmental and geospatial data, they need to move away from traditional numerical forecasting methods. Instead, they are turning to AI-powered models that can be embedded in modern data platforms and are available to various teams. BKW, an energy group based in Switzerland, has partnered with Microsoft Energy & Resources Industry to build a cloud-based data and AI platform capable of ingesting, processing and operationalising weather, environmental and geospatial data at scale without relying on custom systems or niche tools. Built on a Microsoft Azure-native operational infrastructure, BKW’s platform combines Aurora, an AI weather foundation model developed by Microsoft Research and Microsoft AI Weather, with the Microsoft Planetary Computer Pro geospatial intelligence platform. Aurora uses a large-scale AI model trained on decades of atmospheric data to quickly generate accurate ensemble weather forecasts. Its outputs are stored in Microsoft Planetary Computer Pro, which uses two specialised data catalogues – Microsoft AI Weather Grid HD EU Swiss energy group BKW has collaborated with Microsoft to build an AI-powered weather forecasting platform that will enable it to deliver reliable energy services across Europe CASE STUDY: BKW Accelerating the move to renewable energy Photo: BKW 56
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