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arXiv · 2512.07876

Fourier-Enhanced Recurrent Neural Networks for Electrical Load Time Series Downscaling

Qi Chen·Mihai Anitescu
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Abstract

We present a Fourier-enhanced recurrent neural network (RNN) for downscaling electrical loads. The model combines (i) a recurrent backbone driven by low-resolution inputs, (ii) explicit Fourier seasonal embeddings fused in latent space, and (iii) a self-attention layer that captures dependencies among high-resolution components within each period. Across four PJM territories, the approach yields RMSE lower and flatter horizon-wise than classical Prophet baselines (with and without seasonality/LAA) and than RNN ablations without attention or Fourier features.

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Qi Chen, Mihai Anitescu. 2025-11-27. Fourier-Enhanced Recurrent Neural Networks for Electrical Load Time Series Downscaling. https://arxiv.org/abs/2512.07876

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