Short-Term Spatio-Temporal Wind Power Forecast in Robust Look-ahead Power System Dispatch

208 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting (2017, background): “(Xie et al., 2014) also considered probabilistic TDD forecast for power system economic dispatch.”
Low-dimensional models in spatio-temporal wind speed forecasting (2015, unknown): “[15] also considered probabilistic TDD forecast for power system economic dispatch.”
Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform (2016, background): “[24] propose a probabilistic forecast model based 90 on TDD model including spatial as well as the temporal correlations and geostrophic wind information.”
Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting (2019, background): “It is shown in the literature that neighboring wind sites have high spatial correlations [27].”
Grid Integration Challenges of Wind Energy: A Review (2020, methodology): “analysis [37], statistical method [38], and artificial intelligence [39].”
Adaptive Robust Optimization With Dynamic Uncertainty Sets for Multi-Period Economic Dispatch Under Significant Wind (2014, methodology): “The work in [35] applies two advanced statistical methods for wind forecasting, and integrates these models with a robust look-ahead ED.”