 |
In conclusion, let me sum up my main points.
We developed PV power generation and power load prediction models using deep learning and machine learning.
And we rovided the validity of the results using eXplainable AI.
Prediction model was derived by substituting appropriate variables for the time when the power generation could not be measured.
Values influenced the result value was derived through the SHAP algorithm.
Research to increase energy efficiency in a small power grid by applying a prediction model developed in the future to a building or home unit and scheduling it based on the prediction results is expected to be possible.
|
IEEE/ICACT20230158 Slide.13
[Big Slide]
[YouTube]