- The purpose of the project is to predict the electricity output based on the rotating speed of the wind turbines; here we get the output based on the previous data. In this we have two independent variables LV Active Power, Wind Speed and two dependent variable Theoretical Power and wind direction. For that we use one of the regression algorithms like polynomial regression and predict the output by using r2_score. In this we train the model with the previous data and test the data by giving the independent variables and predicting whether it is giving expected output or not. We use a node red for deploying the nodes, we used http request, timestamp, for sending the message we used message payload, for power detection we used theoretical power, inputs as Active Power and Wind Speed and to implement the user interface. There are two steps in the process of wind power prediction. In the first step raw data is collected by the power plant information system and is filtered. This prepares a valid data to be used for building a prediction model. In the second step we use all the regression algorithms to build a model to predict the wind power. It is to achieve a high accuracy with respect to the measured data.
- https://data.open-power-system-data.org/time_series/
- https://www.elia.be/en/grid-data/power-generation
- https://data.open-power-system-data.org/weather_data/
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