Patents by Inventor Ruixiao Zhang

Ruixiao Zhang 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).

  • Patent number: 11939264
    Abstract: The present disclosure provides a preparation method for hydrothermal synthesis of fly ash silicate aggregate including: mixing sodium metasilicate, potassium hydroxide, and inorganic-organic hybrid excitation monomer as raw materials to obtain an inorganic-organic composite activator; preparing a silicate aggregate raw material, mixing measured fly ash, carbide slag, quicklime, and vitrified micro bubble by mass, adding the inorganic-organic composite activator and continue stirring to produce a mixture; forming a ball disc, wetting an expanded perlite that forms a core of the ball by spraying water, adding a prepared mixture, spraying water while adding, standing and curing, performing a maturation and activation treatment in an autoclave, undergoing a silicon calcium reaction for a hydrothermal synthesis to obtain the silicate aggregates.
    Type: Grant
    Filed: September 27, 2023
    Date of Patent: March 26, 2024
    Assignee: Henan Building Materials Research and Design Institute Co., Ltd.
    Inventors: Shengqiang Chen, Zhuhe Zhai, Bing Zhang, Linjian Shangguan, Ruixiao Chen, Luyang Li, Ge Yang, Ming Han, Guowang Li, Rui Yin, Tingting Wang, Yongchuan Liu, Dan Chen
  • Publication number: 20230299585
    Abstract: Disclosed is a coordinated peak shaving optimization method for a plurality of power supplies based on a fluctuation characteristic of a renewable energy source, including the following steps: s1: determining a weekly generated electricity quantity of hydropower based on an available capacity and a storage capacity of an electricity quantity; s2: predicting a renewable energy power generation curve and a load curve of a system weekly; s3: determining a start point of peak shaving of the hydropower based on an external transmission curve, the renewable energy generation curve, and the load curve of the system and a generating capacity of the hydropower; s4: determining a weekly peak shaving demand of the system; and s5: establishing an optimization model with a maximum peak shaving demand. The present disclosure proposes a reasonable arrangement for peak shaving, so as to resolve an accommodation problem caused by large-scale access of a renewable energy source.
    Type: Application
    Filed: June 10, 2021
    Publication date: September 21, 2023
    Inventors: Qiang Zhou, Yanhong Ma, Yanqi Zhang, Yue Wu, Ningbo Wang, Zhicheng Ma, Xushan Han, Guogang Jin, Long Zhao, Qingquan Lv, Dingmei Wang, Jinping Zhang, Pengfei Gao, Ruixiao Zhang, Jianmei Zhang, Jin Li, Zhenzhen Zhang, Lijuan Liu, Senlin Yang, Jun Kang, Rui Song
  • Publication number: 20220037884
    Abstract: A peak shaving control method for emergent source-grid coordination in case of a faulty sending-end power grid. The method includes: S1: evaluating dispatchability of a cluster virtual wind power unit; S2: developing a method for calculating a dispatchability index of the cluster virtual wind power unit; S3: analyzing a source-load peak-shaving resource strategy; and S4: distributing a control strategy for tie-line peak shaving. The present disclosure has the following beneficial effects: In the present disclosure, real-time dispatchability of wind power participating in real-time power balance is first analyzed, specific evaluation indexes and calculation methods are provided, and calculation examples are given for verification. Then, an optimized real-time dispatch strategy is provided based on demand-side response resources, and DC and AC tie-lines are coordinated for operation.
    Type: Application
    Filed: July 10, 2021
    Publication date: February 3, 2022
    Inventors: Qiang Zhou, Yanhong Ma, Yanqi Zhang, Yue Wu, Ningbo Wang, Zhicheng Ma, Xushan Han, Guogang Jin, Long Zhao, Dingmei Wang, Qingquan Lv, Jinping Zhang, Pengfei Gao, Ruixiao Zhang, Jianmei Zhang, Jin Li, Zhenzhen Zhang, Lijuan Liu, Yue Fan, Xiaokan Gou, Xuebin Wang