您当前的位置:
首页 >
文章列表页 >
A bi-level optimal dispatch strategy for synergistic peak shaving with high-energy-consumption fused magnesia loads and energy storage
Internet of Energy | 更新时间:2026-02-28
    • A bi-level optimal dispatch strategy for synergistic peak shaving with high-energy-consumption fused magnesia loads and energy storage

    • The research progress in the field of new energy access was introduced. Experts established a power regulation model for electric melting magnesium furnaces and constructed a dual layer scheduling model for joint optimization with thermal power units, providing a solution to enhance the peak shaving capability of the power grid.
    • ZHEJIANG ELECTRIC POWER   Vol. 45, Issue 2, Pages: 72-79(2026)
    • DOI:10.19585/j.zjdl.202602007    

      CLC:
    • Received:21 May 2025

      Revised:2025-07-22

      Published:25 February 2026

    移动端阅览

  • LI Junhui,FAN Tianzhen,YU Meng,et al.A bi-level optimal dispatch strategy for synergistic peak shaving with high-energy-consumption fused magnesia loads and energy storage[J].ZHEJIANG ELECTRIC POWER,2026,45(02):72-79. DOI: 10.19585/j.zjdl.202602007.

  •  
  •  

0

Views

0

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

An optimal dispatch strategy for integrated energy systems based on generalized energy storage aggregation characteristics
An optimal scheduling method for port integrated energy system considering ship demand response at multiple time scales
Analysis of the evolution, key technologies, and challenges of virtual power plants in China
A study on incentive mechanisms for air-conditioning loads participating in demand response
An optimal strategy for energy storage allocation in active distribution networks considering new energy consumption rates

Related Author

ZHAO Ting
SUN Xin
XIE Jingdong
XIE Wenqiang
SHI Mingming
LIU Ruihuang
DU Can
HUA Haochen

Related Institution

College of Electrical Engineering, Shanghai University of Electric Power
School of Electrical and Power Engineering, Hohai University
Electric Power Research Institute of State Grid Jiangsu Electric Power Co., Ltd.
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University
Guodian Nanjing Automation Co., Ltd.
0