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Methods for Online Peak Demand Reduction of Large Load Users With Energy Storage Discharge
The novel technology focuses on optimizing the usage of energy storage systems to manage electricity consumption for large-load consumers, particularly during peak demand times, when electricity prices skyrocket.
Prof. CHEN Minghua, Prof. S Joe QIN, Dr. MO Yanfang, Dr. LIN Qiulin
  • Energy Storage
  • Electrical Discharge
  • Mains Electricity Grid
  • Peak Demand
  • Competitive Ratio
  • Large-load Consumers
  • Utilities
TRL
3
Generative Learning for Financial Time Series With Irregular and Scale-Invariant Patterns
The patent discloses a novel machine learning framework named FTS-Diffusion for synthesizing realistic financial time series. Its core innovation is a three-module architecture specifically designed to decompose and address the challenges of irregularity and scale-invariance.
Prof. CHEN Minghua, Prof. QIAO Xiao , Mr HUANG Hongbin
  • Generative AI
  • Machine Learning
  • Deep Learning
  • Time Series Synthesis
  • Diffusion Models
  • Dynamic Time Warping (DTW)
  • Scale-Invariant Patterns
TRL
4
Carbon Footprint Optimized Timely E-Truck Transportation
This patent discloses a novel computer-implemented method for the joint Carbon Footprint Optimization (CFO) of an electric truck's journey.
Prof. CHEN Minghua, Dr. LIN Qiulin, Dr. SU Junyan
  • Carbon Footprint Optimization
  • Electric Vehicle Routing Problem
  • Stage-Expanded Graph
  • Dual Subgradient Method
  • Speed Planning
  • Charging Planning
  • State of Charge (SoC) Constraints
TRL
4
Deep Learning-Based Approach for Solving Optimal Power Flow Problems with Flexible Topology
This patent introduces a novel Deep OPF Flexible Topology method, which embeds discrete topology variations into a continuous admittance space, enabling a single DNN to solve OPF problems across multiple grid configurations.
Prof. CHEN Minghua, Dr. ZHOU Min
  • Optimal Power Flow
  • Deep Neural Network
  • Admittance Matrix
  • Voltage Magnitude and Phase Angle
  • Renewable Energy Integration
  • Power Grid Optimization
  • Electric Power Systems
  • Energy Management
  • Smart Grids
  • Sustainable Energy
TRL
4
Deep Learning-based Optimal Power Flow Solution with Applications to Operating Electrical Power Systems
This invention solves AC optimal power flow (AC-OPF) problems using a deep neural network.
Prof. CHEN Minghua, Dr. HUANG Wanjun, Mr. PAN Xiang
  • AC-OPF
  • Optimal Power Flow
  • DeepOPF-V
  • Deep Neural Network
  • Energy
  • Power Supply
  • AC
  • Deep Learning
TRL
5

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