| 引用本文: | 康瑞,齐林海,王红,潘爱强,周健.基于流式计算的暂态电压扰动并行实时监测技术[J].电力系统保护与控制,2020,48(2):129-136.[点击复制] |
| KANG Rui,QI Linhai,WANG Hong,PAN Aiqiang,ZHOU Jian.Parallel real-time monitoring technology for transient voltage disturbance based on flow calculation[J].Power System Protection and Control,2020,48(2):129-136[点击复制] |
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| 摘要: |
| 暂态电压扰动模式识别面临两个挑战，一是局限于单一监测点的扰动识别不能准确解释复杂扰动的完整过程，另一是离线分析很难满足辅助决策实时性的要求。提出基于Storm流式计算框架，结合logstash和Kafka消息中间件，构建面向多监测点的实时数据监测处理平台。采用滑动时间窗口算法，实现Storm编程逻辑拓扑。通过设置基本时间窗口大小和数量，实现面向区域电网的多时空尺度、多业务模型的暂态电压扰动模式识别。实验结果表明，合理设置Storm组件的任务数目能够最大限度发挥并行处理能力。通过仿真数据测试得到的吞吐量和平均处理延迟结果，能够满足电网对流数据实时处理的高吞吐量、可扩展性、实时性和准确性的要求。 |
| 关键词: 暂态电压扰动 流式计算 并行滑动窗口 模式识别 |
| DOI：10.19783/j.cnki.pspc.190231 |
| 投稿时间：2019-03-05修订日期：2019-07-10 |
| 基金项目:中央高校基本科研业务专项资金项目资助(2018MS030);国家电网公司科技项目资助(52094018001C)“城市电网电能质量大数据深化分析及应用技术研究” |
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| Parallel real-time monitoring technology for transient voltage disturbance based on flow calculation |
| KANG Rui,QI Linhai,WANG Hong,PAN Aiqiang,ZHOU Jian |
| (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;Electric Power Research Institute, SMEPC, Shanghai 200437, China) |
| Abstract: |
| Transient voltage disturbance pattern recognition faces two challenges. First, disturbance recognition limited to a single monitoring point cannot accurately explain the complete process of complex disturbance, and the other is that off-line analysis cannot meet the requirements of real-time decision-making. Based on the Storm streaming computing framework, combined with logstash and Kafka message middleware, this paper builds a real-time data monitoring and processing platform for multiple monitoring points. The sliding time window algorithm is used to implement the Storm programming logic topology. By setting the basic time window size and quantity, it realizes the identification of transient voltage disturbance patterns for multi-temporal scale and multi-service models for regional power grids. The experimental results show that the number of tasks for properly setting the Storm component can maximize the parallel processing capability. The throughput and average processing delay results obtained by the simulation data test can meet the requirements of high throughput, scalability, real-time and accuracy of real-time processing of grid convection data. This work is supported by Fundamental Research Funds for the Central Universities (No. 2018MS030) and Science and Technology Project of State Grid Corporation of China “Big Data Deep Analysis and Application Technique Research for Power Quality of Urban Power Grid” (No. 52094018001C). |
| Key words: transient voltage disturbance flow calculation parallel sliding window pattern recognition |
