26 citations · 36 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…
A Review of Graph Neural Networks and Their Applications in Power Systems
Wenlong Liao, Birgitte Bak-Jensen, Jayakrishnan Radhakrishna Pillai +2
Deep neural networks have revolutionized many machine learning tasks in power systems, ranging from pattern recognition to signal processing. The data in these tasks is typically r…