Combining Numerical Weather Predictions and Satellite Data for PV Energy nowcasting
Product Description
Domain: Machine
Learning Tool:
MATLAB
Abstract
As a support system for PV energy generation
systems, predicting the accurate weather is more important. Combining the
numerical weather predictions and live satellite data is combined together to
form a new prediction scope and that is implemented using support vector
regression models. The existing system with numerical weather prediction
approach using machine learning is tested for performance in terms of accuracy.
In the proposed system, gradient boosted regression model combined with
decision tree algorithm to form a new tunable regression model. The proposed system
calls the live weather data using java script and fetches the data into the cloud
for analysis. The data received will be compared with the historical weather
records and the prediction process is evaluated. The proposed platform achieves
improved accuracy comparing with the existing system.
Existing system
The existing system with numerical weather
prediction approach using machine learning is tested for performance in terms
of accuracy. In the proposed system, gradient boosted regression model combined
with decision tree algorithm to form a new tunable regression model.
Problem statement
- Restricted models with limited
datasets with static location
Proposed System
The proposed system calls the live weather data
using java script and fetches the data into the cloud for analysis. The data
received will be compared with the historical weather records and the
prediction process is evaluated. The proposed platform achieves improved
accuracy comparing with the existing system.
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The Delivery time for Hardware Mini projects is 7-8 working days.