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Gracias a 12 años de investigación académica, Calibsun ha desarrollado un algoritmo de aprendizaje automático (machine learning) que permite analizar datos meteorológicos en tiempo real para ofrecer previsiones climáticas óptimas. Para comprobar el rendimiento de sus modelos de previsión, Calibsun ha realizado backtests. Este método de evaluación consiste en simular las previsiones que habría generado el modelo a partir de datos históricos durante un tiempo determinado.

Los objetivos de reducción de emisiones para la industria energética, consumidores e industria en general, están acelerando el desarrollo de fuentes de energía renovable (FER). La energía fotovoltaica (FV) se ha establecido como una tecnología puntera, rentable y sostenible. El crecimiento en la producción de energía solar destaca la importancia de pronósticos precisos para estimar la potencia de las instalaciones en diversos horizontes temporales.

To increase their energy sovereignety while accelerating their energy transition, many industries are integrating solar energy into their energy mix through self-consumption.

Intermittent, variable and subject to the uncertain weather, solar energy remains a highly promising solution for meeting decarbonization targets and reducing greenhouse gas emissions.

Unlike deterministic methods, which produce a single result, probabilistic approaches provide a range of possible outcomes with associated probabilities. These methods take into account the uncertainty inherent in the various factors influencing forecasts, such as data variability.

Solar resource forecasting has become an essential aspect of the operation of photovoltaic (PV) power plants to increase the production of renewable energy from the sun. Solar resource forecasting is essentially a data story, where vast quantities of data are collected, analyzed and transformed into actionable information by grid operators, power plant operators, energy trading aggregators and developers of future installations.

According to the International Energy Agency (IEA), photovoltaics should account for 2,350 GW of power worldwide within 4 years, surpassing hydraulic in 2024, natural gas in 2026 and coal in 2027 in electricity generation.