V-Forecast
Optimize production and consumption planning with precision using AI-powered energy forecasting.
V-Forecast
is a software solution for forecasting electricity load. V-Forecast is a self-learning and self-calibrating system. It relies on artificial intelligence, machine learning, statistical models, and historical load data to automatically generate accurate electricity load forecasts. V-Forecast automatically detects seasonality and can apply multi-seasonality based on historical load data.
V-Forecast’s Algorithm
is powerful and accurate, yet easy to use and quick to implement. It can be up and running in hours or even minutes.
Automatic and Accurate Predictions
V-Forecast uses artificial intelligence, machine learning, and statistical models to automatically generate electricity load forecasts and provide customers with accurate and reliable predictions.
Easy Setup and Use
V-Forecast can be set up and used quickly. With its user-friendly interface, it can be easily operated without complex adjustments or lengthy training.
Low Maintenance Cost
V-Forecast keeps maintenance costs low by minimizing customer intervention and interaction. Thanks to automatic data collection and model updates, customers don't need to constantly monitor the system.
V-Forecast users can define as many assets as they own or desire through asset management and receive forecasts for each asset. Various models are trained, and the most suitable model is determined. With Best Model Selection, asset data is periodically trained, and the most suitable model is selected from among artificial intelligence, machine learning, and statistical models.
Forecast Sharing allows forecasts for each asset to be retrieved via API or sent to customers via email, FTP, FTPS, or SFTP. With Sharing Configuration, forecasts can be scheduled for each asset, and customers can specify a time to receive emails or files.
Day-Ahead Forecast automatically generates 48-hour forecasts for electricity load. The forecasts are intended to enable more efficient use of energy production/consumption data.
V-Forecast users can define as many assets as they own or desire through asset management and receive forecasts for each asset. Various models are trained, and the most suitable model is determined. With Best Model Selection, asset data is periodically trained, and the most suitable model is selected from among artificial intelligence, machine learning, and statistical models.
Forecast Sharing allows forecasts for each asset to be retrieved via API or sent to customers via email, FTP, FTPS, or SFTP. With Sharing Configuration, forecasts can be scheduled for each asset, and customers can specify a time to receive emails or files.
Day-Ahead Forecast automatically generates 48-hour forecasts for electricity load. The forecasts are intended to enable more efficient use of energy production/consumption data.
V-Forecast users can define as many assets as they own or desire through asset management and receive forecasts for each asset. Various models are trained, and the most suitable model is determined. With Best Model Selection, asset data is periodically trained, and the most suitable model is selected from among artificial intelligence, machine learning, and statistical models.
Forecast Sharing allows forecasts for each asset to be retrieved via API or sent to customers via email, FTP, FTPS, or SFTP. With Sharing Configuration, forecasts can be scheduled for each asset, and customers can specify a time to receive emails or files.
Day-Ahead Forecast automatically generates 48-hour forecasts for electricity load. The forecasts are intended to enable more efficient use of energy production/consumption data.
With Automatic Meter Reading System Integration, if the asset is a meter, the data collected can be retrieved and stored for future load forecasting. With Automatic Data Collection, load data collected through V-Sensor and AMR integrations is continuously retrieved and used in forecasts.
With Automatic Meter Reading System Integration, if the asset is a meter, the data collected can be retrieved and stored for future load forecasting. With Automatic Data Collection, load data collected through V-Sensor and AMR integrations is continuously retrieved and used in forecasts.
With Automatic Meter Reading System Integration, if the asset is a meter, the data collected can be retrieved and stored for future load forecasting. With Automatic Data Collection, load data collected through V-Sensor and AMR integrations is continuously retrieved and used in forecasts.
