solar and wind power plants
Renewable energy forecast
short-term forecasts up to 6 hours.
Such forecasts are used in the balancing electricity market, where pricing occurs due to stochastic growth or reduction in consumption.
Such forecasts are used in the balancing electricity market, where pricing occurs due to stochastic growth or reduction in consumption.
short-term forecast
wind power plant forecast
solar power plant forecast
MEDIUM-TERM FORECAST
Medium-term forecasts are carried out with a horizon of up to a day.
Similar forecasts are used in the daily forward market (DAM), where pricing occurs based on counters of offers from consumers and electricity producers.
Similar forecasts are used in the daily forward market (DAM), where pricing occurs based on counters of offers from consumers and electricity producers.
Long-term forecasting is carried out with a horizon of up to 15 days.
Such forecasts are used for long-term planning (maintenance of generating equipment, analysis of the possibilities of covering peak electricity consumption.
Such forecasts are used for long-term planning (maintenance of generating equipment, analysis of the possibilities of covering peak electricity consumption.
long-term forecast
how it works
Short-term forecast
For medium- and long-term forecasting we use:
- Images of geostationary satellites in the visible and infrared range
- Combination of recurrent and deep convolutional neural network algorithms for predicting atmospheric images at the considered forecast horizon
- Computer vision for identifying the effective albedo of terrestrial regions
- Models (ESRA, Perez) for determining surface insolation
- Computer simulation of the station’s operation with the obtained insolation indicators
Short-term and Medium term forecasts
For medium- and long-term forecasting we use:
- Global weather forecast databases from GFS and ECMWF;
- Numerical modeling of atmospheric processes (WRF)
- Modeling of insolation parameters based on the obtained atmospheric parameters
- Recurrent and Convolutional Neural Networks for More Accurate Prediction
Input data to improve the accuracy of your solar power plants forecasts
- power plant coordinates
- Data on technological solutions of solar power plants (number of solar power plants, technical characteristics of solar power plants and inverter equipment, tilt angles of solar power plants and inter-row distances between solar power plant arrays, installed power of solar power plants)
- Access to stations SCADA data
- Data on wind farm solution technologies (number of wind turbines, wind turbine coordinates, installed wind power plant capacity)
- Access to WPP SCADA data
- Technical characteristics of wind turbines
Input data to increase the accuracy of your wind farm forecasts
WHAT WE NEED FOR FORECASTING
Contact us
email: info@smartren.pro
