电力系统的传统振荡问题及控制措施实践

2018 年 6 月 16 日 NE电气

上期内容:电力电子化电力系统的功率振荡问题

近期重要事宜公告:

阅读量最高的17篇学术报告

河北工业大学电气工程学院诚聘英才

华科徐伟教授清华张品佳教授华电李庆民教授赵成勇教授亚利桑那州立大学Raja Ayyanar教授佐治亚大学叶津教授清华四川能源互联网研究院   招收博士研究生、博士后、访问学者。更多招聘信息,请点击“高薪诚聘电气工程博士博士后”。


王新宝经理提供,特此感谢!

专家介绍

王新宝,现任南瑞继保电气研究院电网保护所电力系统分析部经理,主要从事电力系统仿真建模、电网安全稳定控制、FACTS及直流输电技术在电力系统中的应用、以及新能源并网控制等方面的研究工作,先后荣获中国电机工程学会、机械工业联合会、新疆生产建设兵团等多个省部级单位或团体的科技奖励。获得发明专利10余项,发表论文10余篇,2018年被补选为中国电机工程学会电力系统专委会委员。


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Biological systems with intertwined feedback loops pose a challenge to mathematical modeling efforts. Moreover, rare events, such as mutation and extinction, complicate system dynamics. Stochastic simulation algorithms are useful in generating time-evolution trajectories for these systems because they can adequately capture the influence of random fluctuations and quantify rare events. We present a simple and flexible package, BioSimulator.jl, for implementing the Gillespie algorithm, $\tau$-leaping, and related stochastic simulation algorithms. The objective of this work is to provide scientists across domains with fast, user-friendly simulation tools. We used the high-performance programming language Julia because of its emphasis on scientific computing. Our software package implements a suite of stochastic simulation algorithms based on Markov chain theory. We provide the ability to (a) diagram Petri Nets describing interactions, (b) plot average trajectories and attached standard deviations of each participating species over time, and (c) generate frequency distributions of each species at a specified time. BioSimulator.jl's interface allows users to build models programmatically within Julia. A model is then passed to the simulate routine to generate simulation data. The built-in tools allow one to visualize results and compute summary statistics. Our examples highlight the broad applicability of our software to systems of varying complexity from ecology, systems biology, chemistry, and genetics. The user-friendly nature of BioSimulator.jl encourages the use of stochastic simulation, minimizes tedious programming efforts, and reduces errors during model specification.

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