A Spatio-Temporal Analysis Approach for Short-Term Forecast of Wind Farm Generation

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Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting (2017, background): “(He et al., 2014) presented Markov chain-based stochastic models for predictions of wind power generation after characterizing the statistical distribution of aggregate power with a graph learning-based spatio-temporal analysis.”
Low-dimensional models in spatio-temporal wind speed forecasting (2015, unknown): “[17] presented Markov chain-based stochastic models for predictions of wind power generation after characterizing the statistical distribution of aggregate power with a graph learning-based spatio-temporal analysis.”
Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting (2019, background): “Markov chain-based statistical methods that leverage graphical spatio-temporal learning-based model and statistical characteristics of aggregated wind generation are presented in [30] to forecast wind generation output.”
Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform (2016, background): “Wind 95 farm generation forecast is studied in another work [27] by applying spatiotemporal analysis to data from multiple classes of wind turbines, in which finite-state Markov chain models are obtained for short-term forecasts.”