Patents by Inventor LI-FEN CHOU

LI-FEN CHOU has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Power generation prediction system and method thereof
    Patent number: 11196380
    Abstract: A power generation prediction system using a first and second neural networks is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again. The power generation prediction data is a power generation prediction bound having a maximum and minimum power generation prediction values, and thus the power deployment terminal in a power grid can deploy power more precisely.
    Type: Grant
    Filed: December 19, 2019
    Date of Patent: December 7, 2021
    Assignee: Taiwan Power Company
    Inventors: Chih-Jung Chang, Li-Fen Chou, Yih-Guang Leu
  • Power generation prediction system and a method thereof
    Patent number: 10643128
    Abstract: A power generation prediction system using a first neural network and a second neural network is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again.
    Type: Grant
    Filed: July 5, 2018
    Date of Patent: May 5, 2020
    Assignee: Taiwan Power Company
    Inventors: Chih-Jung Chang, Li-Fen Chou, Yih-Guang Leu
  • POWER GENERATION PREDICTION SYSTEM AND METHOD THEREOF
    Publication number: 20200127598
    Abstract: A power generation prediction system using a first and second neural networks is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again. The power generation prediction data is a power generation prediction bound having a maximum and minimum power generation prediction values, and thus the power deployment terminal in a power grid can deploy power more precisely.
    Type: Application
    Filed: December 19, 2019
    Publication date: April 23, 2020
    Inventors: CHIH-JUNG CHANG, LI-FEN CHOU, YIH-GUANG LEU
  • POWER GENERATION PREDICTION SYSTEM AND A METHOD THEREOF
    Publication number: 20190012598
    Abstract: A power generation prediction system using a first neural network and a second neural network is provided, and the first neural network is connected to the second neural network. The first neural network receives first input data, and generates the amount prediction data according to the first input data. The first input data is used to determine amount prediction data, and the amount prediction data is used to determine power generation prediction data. The second neural network receives the amount prediction data, and calculates the power generation prediction data according to the amount prediction data. When a device in a selected area is deteriorated or reinstalled, the second neural network is fine-tuned and trained again.
    Type: Application
    Filed: July 5, 2018
    Publication date: January 10, 2019
    Inventors: CHIH-JUNG CHANG, LI-FEN CHOU, YIH-GUANG LEU