首页> 外文期刊>Electric power systems research >A new real-time multi-agent system for under frequency load shedding in a smart grid context
【24h】

A new real-time multi-agent system for under frequency load shedding in a smart grid context

机译:一种新的实时多智能体系统,可在智能电网环境中降低低频负荷

获取原文
获取原文并翻译 | 示例
           

摘要

Automatic under frequency load shedding schemes need to be carefully designed in order to reduce the risk of widespread system collapse. This paper proposes a centralized hierarchical multi-agent system that coordinates various stages of monitoring and decision making processes. The main contribution is to improve traditional contingency response algorithms such as load shedding schemes, taking advantage of the future smart grid infrastructure. The multi-agent system seeks for a minimum amount of load disconnection in a short period of time, causing the least possible disturbance in the system frequency. A hardware-in-the-loop simulation of a full electric power system using a real time digital simulator was utilized. The solution was embedded in a real time system, consisting of hardware and software, to test and validate the proposed methodology. In addition, the studied methodology was compared with two other load shedding philosophies through a load shedding metric score. Shedding was carried out in a single step and the amount of disconnected load was close to the dynamic power unbalance. The results show that it is possible to improve the traditional load shedding philosophy schemes and use advanced communication infrastructure, monitoring and embedded processing capabilities to provide better stability and reduce unnecessary load disconnections from the system.
机译:为了降低广泛的系统崩溃的风险,需要精心设计自动的低频减载方案。本文提出了一种集中式的分层多主体系统,该系统可协调监视和决策过程的各个阶段。主要贡献是利用未来的智能电网基础设施,改进了传统的应急响应算法,例如减载方案。多代理系统在短时间内寻求最小的负载断开连接,从而在系统频率中引起最小的干扰。利用了使用实时数字仿真器的完整电力系统的硬件在环仿真。该解决方案被嵌入包含硬件和软件的实时系统中,以测试和验证所提出的方法。此外,通过减载指标评分,将研究方法与其他两种减载理念进行了比较。卸货仅一步完成,断开的负载量接近动态功率不平衡。结果表明,可以改善传统的减载策略方案,并使用先进的通信基础架构,监视和嵌入式处理功能来提供更好的稳定性并减少不必要的负载与系统的断开连接。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号