Fast Cycle Structure Detection for Power Grids Based on Graph Computing
作者机构：the Computing&Application Technology Research DivisionGlobal Energy Interconnection Research InstituteBeijing 102209China
出 版 物：《CSEE Journal of Power and Energy Systems》 (中国电机工程学会电力与能源系统学报（英文）)
年 卷 期：2023年第9卷第6期
页 面：2204-2213页
核心收录：
学科分类：0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：National Key Research and Development Program of China(2017YFE0132100)。
主 题：Cycle detection graph computing power grid distribution grid
摘 要：The cycle structure in a power grid may lower the stability of the network;thus,it is of great significance to accu-rately and timely detect cycles in power grid networks.However,detecting possible cycles in a large-scale network can be highly time consuming and computationally intensive.In addition,since the power grid s topology changes over time,cycles can appear and disappear,and it can be difficult to monitor them in real time.In traditional computing systems,cycle detection requires considerable computational resources,making real-time cycle detection in large-scale power grids an impossible task.Graph computing has shown excellent performance in many areas and has solved many practical graph-related problems,such as power flow calculation and state estimation.In this article,a cycle detection method,the Paton method,is implemented and optimized on a graph computing platform.Two cases are used to test its performance in an actual power grid topology scenario.The results show that the graph computing-based Paton method reduces the time consumption by at least 60%compared to that of other methods.
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