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Found 2 papers, 1 papers with code
Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data
In this work, we propose two deep-learning-based regional forecasting methods that can effectively leverage both types of time series (aggregated and individual) with weather data in a region.
Multi-Resolution, Multi-Horizon Distributed Solar PV Power Forecasting with Forecast Combinations
We propose a forecast combination approach based on particle swarm optimization (PSO) that will enable a forecaster to produce accurate forecasts for the task at hand by weighting the forecasts produced by individual models.
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