Impact Analysis of wind Energy on Electricity Price using Deep Neural Network

Abstract

The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. The impact of wind energy on electricity price is significant and it is an important task for power system planners to forecast the price in light of its variability. The impact of wind energy penetration on electricity price using Support Vector Regression (SVR) and Deep Neural Network (DNN) has been investigated for the Austria Electricity market. From the evaluation metrics calculation, it is observed that the DNN model performs better over SVR for the available dataset. The MAPE Value for DNN model was found 5.384 for the available dataset.