公开(公告)号：US10211851B2

公开(公告)日：2019-02-19

申请号：US15947857

申请日：2018-04-08

Applicant: Hefei University of Technology

Inventor： Kaile Zhou ,  Lulu Wen ,  Shanlin Yang ,  Xinhui Lu ,  Zhen Shao ,  Li Sun

IPC: H03M7/00 ,  H03M7/30 ,  G01R22/06 ,  G01D4/00 ,  H04L29/06

Abstract: The present invention relates to a method and a system for compressing data from a smart meter. The method comprises: LZ-encoding electricity load data collected by the smart meter whenever the smart meter collects the electricity load data; storing the LZ-encoded electricity load data in a temporary database through a smart grid communication channel; reading the electricity load data from the temporary database every preset second duration, wherein the read electricity load data is electricity load data stored in the temporary database within the second duration before a corresponding reading time point; and LZ-decoding the read electricity load data, SAX-compressing the LZ-decoded electricity load data, and storing the SAX-compressed electricity load data in a data center. The present invention has high compression rate, reduces the transmission burden for communication lines and storage burden for the data center, and improves the efficiency of smart electricity data analysis and mining.

公开(公告)号：US10026134B2

公开(公告)日：2018-07-17

申请号：US15597598

申请日：2017-05-17

Applicant: Hefei University of Technology

Inventor： Kaile Zhou ,  Xinhui Lu ,  Shanlin Yang ,  Li Sun ,  Chi Zhang ,  Zhen Shao

IPC: B60L11/18 ,  G06Q50/06 ,  G06Q10/06

Abstract: A charging and discharging scheduling method for electric vehicles in microgrid under time-of-use price includes: determining the system structure of the microgrid and the characters of each unit; establishing the optimal scheduling objective function of the microgrid considering the depreciation cost of the electric vehicle (EV) battery under time-of-use price; determining the constraints of each distributed generator and EV battery, and forming an optimal scheduling model of the microgrid together with the optimal scheduling objective function of the microgrid; determining the amount, starting and ending time, starting and ending charge state, and other basic calculating data of the EV accessing the microgrid under time-of-use price; determining the charge and discharge power of the EV when accessing the grid, by solving the optimal scheduling model of the microgrid with a particle swarm optimization algorithm.