scholarly journals Increasing the Resolution of Wide-Area Situational Awareness of the Power Grid through Event Unmixing

Author(s):  
Hairong Qi ◽  
Yilu Liu ◽  
Fran Li ◽  
Jiajia Luo ◽  
Li He ◽  
...  
Author(s):  
Thomas J. Overbye ◽  
Jessica L. Wert ◽  
Komal S. Shetye ◽  
Farnaz Safdarian ◽  
Adam B. Birchfield

2016 ◽  
Vol 60 (1) ◽  
pp. 10:1-10:11 ◽  
Author(s):  
C. Basu ◽  
M. Padmanaban ◽  
S. Guillon ◽  
L. Cauchon ◽  
M. De Montigny ◽  
...  

Author(s):  
Manu Parashar ◽  
Jay Giri ◽  
Reynaldo Nuqui ◽  
Dmitry Kosterev ◽  
R Gardner ◽  
...  

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 780
Author(s):  
Xiwei Bai ◽  
Daowei Liu ◽  
Jie Tan ◽  
Hongying Yang ◽  
Hengfeng Zheng

Accurate identification of critical nodes and regions in a power grid is a precondition and guarantee for safety assessment and situational awareness. Existing methods have achieved effective static identification based on the inherent topological and electrical characteristics of the grid. However, they ignore the variations of these critical nodes and regions over time and are not appropriate for online monitoring. To solve this problem, a novel data-driven dynamic identification scheme is proposed in this paper. Three temporal and three spatial attributes are extracted from their corresponding voltage phasor sequences and integrated via Gini-coefficient and Spearman correlation coefficient to form node importance and relevance assessment indices. Critical nodes and regions can be identified dynamically through importance ranking and clustering on the basis of these two indices. The validity and applicability of the proposed method pass the test on various situations of the IEEE-39 benchmark system, showing that this method can identify the critical nodes and regions, locate the potential disturbance source accurately, and depict the variation of node/region criticality dynamically.


2013 ◽  
Vol 448-453 ◽  
pp. 2259-2265
Author(s):  
Sheng Chun Yang ◽  
Bi Qiang Tang ◽  
Jian Guo Yao ◽  
Feng Li ◽  
Yi Jun Yu ◽  
...  

With the construction of UHV power grid, integration of large-scale renewable clean energy, and large-scale energy base putting into operation, the power grid dispatching faced with more and more complex challenges. On the basis of existing research results, architecture of intelligent dispatching based on situation awareness is proposed, so as to accurately achieve prevention and control of the power system. The shortcomings of traditional dispatching mode are analyzed firstly, and the concepts and characterization approaches of grid situational awareness and operation state trajectory of power grid are then introduced. The overall objective of intelligent dispatching is presented, including data processing and integrated knowledge mining, predictive perception of grid operation, risk analysis and comprehensive early warning, so as to achieve "automatic cruise under normal operating conditions, automatic navigation under abnormal operating conditions ". The functional framework of intelligent dispatching is also proposed in details, including four major aspects of the perception and forecasts, risk analysis, decision-making support, and automatic control, as well as three supporting functions such as post-assessment of dispatching, trajectory index calculation, and human-computer interaction (HCI).Technical innovations to support automatic intelligent dispatching are discussed and organised in three levels, i.e. perception, comprehension and projection. The breakthroughs are: construction of index system, trajectory recognition based on massive information and knowledge mining, trajectory projection taking into accounts the uncertainties, online risk assessment and early warning, power grid intelligent decision-making support, automatic coordination of grid operation control, online assessment, natural human-computer interaction mode, and etc... These are the future research areas of automatic intelligent dispatching.


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