Python Scripting for DIgSILENT PowerFactory: Enhancing Dynamic Modelling of Cascading Failures
Python Scripting for DIgSILENT PowerFactory: Enhancing Dynamic Modelling of Cascading Failures
复制标题
DIgSILENT PowerFactory 的 Python 脚本：增强级联故障的动态建模
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
R. Preece
中科院分区：
文献类型：
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作者：
Yitian Dai;M. Panteli;R. Preece
产业界和学术界都对连锁故障的潜在风险进行了研究。随着新技术的引入，电力系统运行的不确定性越来越大，这导致对动态仿真的需求越来越大，以充分捕捉系统的行为和演变。本文提出了一种新的动态级联故障仿真平台，实现在DIgSILENT PowerFactory通过Python应用程序编程接口（API）。它可以自动开发级联机制，模拟故障场景和处理结果，并且具有良好的可扩展性，可以很容易地应用于任何电力系统模型。该方法克服了传统人工仿真方法在执行大量重复建模、仿真和数据处理任务时的局限性，大大提高了建模效率。以39节点和2000节点系统为例，说明了各种级联机制的功能，并提供了基于N-2事故分析的停电规模的概率分布。
The potential risk of cascading failure has been investigated by both industry and academia. With the introduction of new technologies, there is increasing uncertainty in power system operation which leads to greater needs for dynamic simulations to fully capture the behaviour and evolution of the system. This paper presents a new dynamic cascading failure simulation platform implemented in DIgSILENT PowerFactory via the Python Application Programming Interface (API). It automatically develops cascading mechanisms, simulates sets of failure scenarios and processes results, and also has good scalability such that it can be easily applied to any power system model. The proposed method overcomes the limitations of traditional manual simulation methods when performing a large number of repetitive modelling, simulation and data processing tasks, and greatly improves modelling efficiency. Case studies on 39-bus and 2000-bus systems are provided to illustrate the functions of various cascading mechanisms and to provide the probability distribution of blackout size based on N-2 contingency analysis.
影响因子：
6.6
作者：
J. Bialek;E. Ciapessoni;D. Cirio;E. Cotilla-Sánchez;C. Dent;I. Dobson;P. Henneaux;P. Hines;J. Jardim;Stephen S. Miller;M. Panteli;M. Papic;A. Pitto;J. Quirós-Tortós;Dee Wu
通讯作者：
J. Bialek;E. Ciapessoni;D. Cirio;E. Cotilla-Sánchez;C. Dent;I. Dobson;P. Henneaux;P. Hines;J. Jardim;Stephen S. Miller;M. Panteli;M. Papic;A. Pitto;J. Quirós-Tortós;Dee Wu