DayCast™ is Reuniwatt’s product to obtain day-ahead solar and wind forecasts. Our algorithms are based on meteorological models optimised for solar and wind, that are combined with artificial intelligence and statistical models. They forecast wind and PV production up to 10 days in advance.

Global coverage and local accuracy

Global coverage and local accuracy

Our algorithms of day-ahead solar and wind forecasts are available worldwide. Moreover, Reuniwatt uses regional meteorological models in order to ensure a high temporal and spatial resolution on the chosen site.

Diversification of supply sources

Diversification of supply sources

Reuniwatt’s day-ahead solar forecasts integrate cloudiness parameters coming from several sources, thus enabling to improve their reliability.

Improved cloud representation in weather models

Improved cloud representation in weather models

The classical weather forecasts do not prioritize the thorough investigation of cloud cover evolution. Reuniwatt conducts research towards a dedicated modeling of this major source of variation of the photovoltaic power generation.

Methodology

DayCast™ is a weather forecasting technique developed by Reuniwatt, and specifically optimised for the day-ahead and up to a whole week ahead cloudiness and solar irradiance on the ground, as well as the wind field in different heights .

DayCast™ combines several numerical meteorological models, permitting to improve the forecasts’ robustness. Artificial intelligence techniques train our models to better take local phenomena into account.

DayCast™ offers a global coverage and offers many parameters useful for the next day’s forecasts:

  • Simulation thanks to a weather model integrating regional specificities
  • External weather data integration so as to improve the model’s pertinence
  • Frequent updates of the simulations
  • Initialisation of high-resolution cloud resolving regional models using innovative data assimilation methods

Features

  • Single-site, portfolio or territories forecasts

  • Self-learning module for a continuous performance improvement

  • Forecasting horizon up to 10 days ahead

  • Irradiation components and photovoltaic power generation forecasts

  • Wind speed and wind direction at an hourly temporal resolution

  • Flexible sending (API, FTP, email, …) and format (json, csv…)

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