Area of research
Electrical and Electronic Engineering · Renewable Energy, Sustainability and the Environment
Research interest
Research focused on Photovoltaic system and Deep belief network, with related work in Extreme learning machine, Cluster analysis, Artificial neural network. Notable publications include 'A multi-step ahead photovoltaic power prediction model based on similar day, enhanced colliding bodies optimization, variational mode decomposition, and deep extreme learning...', 'A Multi-step ahead photovoltaic power forecasting model based on TimeGAN, Soft DTW-based K-medoids clustering, and a CNN-GRU hybrid neural network', and 'Short-Term Photovoltaic Power Prediction Based on Similar Days and Improved SOA-DBN Model'.
Optimal Allocation Method for Energy Storage Capacity Considering Dynamic Time-of-Use Electricity Prices and On-Site Consumption of New Energy
A Multi-step ahead photovoltaic power forecasting model based on TimeGAN, Soft DTW-based K-medoids clustering, and a CNN-GRU hybrid neural network
Short Term Wind Speed Prediction Based on VMD and DBN Combined Model Optimized by Improved Sparrow Intelligent Algorithm
A multi-step ahead photovoltaic power prediction model based on similar day, enhanced colliding bodies optimization, variational mode decomposition, and deep extreme learning machine
Short-Term Photovoltaic Power Prediction Based on Similar Days and Improved SOA-DBN Model