Kunjin Chen
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View article: LLM-Powered Ensemble Learning for Paper Source Tracing: A GPU-Free Approach
LLM-Powered Ensemble Learning for Paper Source Tracing: A GPU-Free Approach Open
We participated in the KDD CUP 2024 paper source tracing competition and achieved the 3rd place. This competition tasked participants with identifying the reference sources (i.e., ref-sources, as referred to by the organizers of the compet…
View article: M2GSNet: Multi-Modal Multi-Task Graph Spatiotemporal Network for Ultra-Short-Term Wind Farm Cluster Power Prediction
M2GSNet: Multi-Modal Multi-Task Graph Spatiotemporal Network for Ultra-Short-Term Wind Farm Cluster Power Prediction Open
Ultra-short-term wind power prediction is of great importance for the integration of renewable energy. It is the foundation of probabilistic prediction and even a slight increase in the prediction accuracy can exert significant improvement…
View article: Scale- and Context-Aware Convolutional Non-Intrusive Load Monitoring
Scale- and Context-Aware Convolutional Non-Intrusive Load Monitoring Open
Non-intrusive load monitoring addresses the challenging task of decomposing the aggregate signal of a household's electricity consumption into appliance-level data without installing dedicated meters. By detecting load malfunction and reco…
View article: Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks
Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks Open
This paper develops a novel graph convolutional network (GCN) framework for\nfault location in power distribution networks. The proposed approach integrates\nmultiple measurements at different buses while taking system topology into\naccou…
View article: Method of inter‐turn fault detection for next‐generation smart transformers based on deep learning algorithm
Method of inter‐turn fault detection for next‐generation smart transformers based on deep learning algorithm Open
In this study, an inter‐turn fault diagnosis method is proposed based on deep learning algorithm. 12‐channel data is obtained in MATLAB/Simulink as the time‐domain monitoring signals and labelled with 16 different fault tags, including bot…
View article: Convolutional sequence to sequence non‐intrusive load monitoring
Convolutional sequence to sequence non‐intrusive load monitoring Open
A convolutional sequence to sequence non‐intrusive load monitoring model is proposed in this study. Gated linear unit convolutional layers are used to extract information from the sequences of aggregate electricity consumption. Residual bl…
View article: Convolutional Sequence to Sequence Non-intrusive Load Monitoring
Convolutional Sequence to Sequence Non-intrusive Load Monitoring Open
A convolutional sequence to sequence non-intrusive load monitoring model is proposed in this paper. Gated linear unit convolutional layers are used to extract information from the sequences of aggregate electricity consumption. Residual bl…
View article: Short-term Load Forecasting with Deep Residual Networks
Short-term Load Forecasting with Deep Residual Networks Open
We present in this paper a model for forecasting short-term power loads based on deep residual networks. The proposed model is able to integrate domain knowledge and researchers' understanding of the task by virtue of different neural netw…
View article: Learning-based data analytics: Moving towards transparent power grids
Learning-based data analytics: Moving towards transparent power grids Open
In this paper, we present the learning-based data analytics moving towards transparent power grids and provide some possible extensions including machine learning, big data analytics, and knowledge transferring. The closed loops of data an…
View article: Modeling the Annual Growth Rate of Electricity Consumption of China in the 21st Century: Trends and Prediction
Modeling the Annual Growth Rate of Electricity Consumption of China in the 21st Century: Trends and Prediction Open
In this paper, the annual growth rate of electricity consumption in China in the first 15 years of the 21st century is modeled using multiple linear regression. Historical data and trends of gross domestic product, fixed assets investment …
View article: Fault detection, classification and location for transmission lines and distribution systems: a review on the methods
Fault detection, classification and location for transmission lines and distribution systems: a review on the methods Open
A comprehensive review on the methods used for fault detection, classification and location in transmission lines and distribution systems is presented in this study. Though the three topics are highly correlated, the authors try to discus…