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Targeted Adversarial Attacks on Wind Power Forecasts. (arXiv:2303.16633v1 [cs.LG])
cs.CR updates on arXiv.org arxiv.org
In recent years, researchers proposed a variety of deep learning models for
wind power forecasting. These models predict the wind power generation of wind
farms or entire regions more accurately than traditional machine learning
algorithms or physical models. However, latest research has shown that deep
learning models can often be manipulated by adversarial attacks. Since wind
power forecasts are essential for the stability of modern power systems, it is
important to protect them from this threat. In this work, we …
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