Open AccessDiscrete event chain description of power system transient dynamic simulations for efficient cluster analysis
Author(s) -
Chen Ying,
Huang Shaowei,
Xia Yue,
Wei Zun
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5615
Subject(s) - computer science , transient (computer programming) , event (particle physics) , discrete event simulation , state space , process (computing) , electric power system , cluster (spacecraft) , algorithm , data mining , power (physics) , simulation , mathematics , statistics , physics , quantum mechanics , programming language , operating system
The results of an electromechanical transient simulation can be viewed as a time series data set. Storing these data requires a sizeable space, and the considerable data size renders comparative analysis difficult. For mitigating these problems, a method for analysing and describing a discrete‐event chain in the dynamic process of a power system is proposed. Based on the symbolic description, the continuous dynamic process is represented as a discrete‐event chain, resulting from the change in state variables beyond the given threshold. Therefore, the event‐driven electromechanical transient simulation is developed, and the continuous dynamics and discrete‐event chain simulation results are obtained. Subsequently, the event relation matrix is obtained, normalised, and then converted into a bitmap. Finally, the k ‐means method is used for the cluster analysis on the bitmap of the simulation result. Two test cases involving an IEEE 39‐bus system and a practical system are considered. Case studies demonstrate the effectiveness of the proposed method.