您当前的位置:
首页 >
文章列表页 >
A low-carbon operation optimization method of ETG-RIES based on adaptive optimization spiking neural P systems
Contents | 更新时间:2026-06-24
    • A low-carbon operation optimization method of ETG-RIES based on adaptive optimization spiking neural P systems

    • Protection and Control of Modern Power Systems   Vol. 9, Issue 5, (2024)
    • DOI:10.23919/PCMP.2023.000208    

      CLC:
    • Published:2024

    移动端阅览

  • Tao Wang, Zhu Huang, Ruixuan Ying, et al. A low-carbon operation optimization method of ETG-RIES based on adaptive optimization spiking neural P systems[J]. Protection and Control of Modern Power Systems, 2024, 9(5). DOI: 10.23919/PCMP.2023.000208.

  •  
  •  
icon
试读结束,您可以激活您的VIP账号继续阅读。
去激活 >
icon
试读结束,您可以通过登录账户,到个人中心,购买VIP会员阅读全文。
已是VIP会员?
去登录 >

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

A fault segment location method for distribution networks based on spiking neural P systems and Bayesian estimation
An explainable framework for load forecasting of a regional integrated energy system based on coupled features and multi-task learning
Coordination of battery energy storageand power-to-gas in distribution systems
Intelligent Self-Adjusting Protection Algorithm for Smart LVDC Distribution Networks
Dual Alternative Iteration Algorithm-Based Hierarchical MPC Strategy for Frequency Regulation Control and Active Power Allocation of Wind-storage Coupling System

Related Author

Yi Wang
Liyuan Liu
Kailang Wu
Jie Gu
Lu Meng
Honglin Wen
Jinghuan Ma
Teodor Ognyanov Trifonov

Related Institution

No data
0