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20212024
most citedTimeGPT in Load Forecasting: A Large Time Series Model Perspective

81 citations · 93 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2024★ 2 cited

Zero and Few Shot Load Forecasting with Large Language Models

Wenlong Liao, Chengrui Zhang, Zhe Yang +4

Deep learning models have shown strong performance in load forecasting, but they generally require large amounts of data for model training before being applied to new scenarios, w…

cs.LG2024★ 81 cited

TimeGPT in Load Forecasting: A Large Time Series Model Perspective

Wenlong Liao, Fernando Porte-Agel, Jiannong Fang +4

Machine learning models have made significant progress in load forecasting, but their forecast accuracy is limited in cases where historical load data is scarce. Inspired by the ou…

eess.SY2023★ 3 cited

Improving the Accuracy and Interpretability of Neural Networks for Wind Power Forecasting

Wenlong Liao, Fernando Porte-Agel, Jiannong Fang +3

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their f…

eess.SY2023★ 2 cited

An Explainable Framework for Machine learning-Based Reactive Power Optimization of Distribution Network

Wenlong Liao, Benjamin Schäfer, Dalin Qin +3

To reduce the heavy computational burden of reactive power optimization of distribution networks, machine learning models are receiving increasing attention. However, most machine…

cs.LG2023★ 2 cited

Explainable Modeling for Wind Power Forecasting: A Glass-Box Approach with High Accuracy

Wenlong Liao, Fernando Porte-Agel, Jiannong Fang +3

Machine learning models (e.g., neural networks) achieve high accuracy in wind power forecasting, but they are usually regarded as black boxes that lack interpretability. To address…

eess.SY2021★ 2 cited

Short-Term Power Prediction for Renewable Energy Using Hybrid Graph Convolutional Network and Long Short-Term Memory Approach

Wenlong Liao, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai +2

Accurate short-term solar and wind power predictions play an important role in the planning and operation of power systems. However, the short-term power prediction of renewable en…

eess.SY2021★ 1 cited

Scenario Generation for Cooling, Heating, and Power Loads Using Generative Moment Matching Networks

Wenlong Liao, Yusen Wang, Yuelong Wang +3

Scenario generations of cooling, heating, and power loads are of great significance for the economic operation and stability analysis of integrated energy systems. In this paper, a…