scholarly journals Self-Organized Criticality and Trend Analysis in Time Series of Blackouts for the China Power Grid

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Qun Yu ◽  
Na Cao ◽  
Qilin Liu ◽  
Yuqing Qu ◽  
Yumin Zhang
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Power Grid ◽  
Data Series ◽  
Power Outage ◽  
Power Failure ◽  
Self Organized ◽  
Time Correlations ◽  
Long Time ◽  
Self Organized Criticality

This paper proposes effective evidence on the correlation between trend and self-organized criticality (SOC) of the power outage sequence in China. Taking the data series of blackouts from 1981 to 2014 in the China power grid as the research object, the method of V/S is introduced into the analysis of the power system blackout sequence to demonstrate their prominent long-time correlations. It also verifies the probability distribution of load loss about blackout size in the China power grid has a tail feature, which shows that the time series of blackouts in the China power grid is consistent with SOC. Meanwhile, a kind of mathematical statistics analysis is presented to prove that there is a seasonal trend of blackouts, and the blackout frequency and blackout size have not decreased over time but have an upward trend in the China power grid, thereby indicating that blackout risk may be increasing with time. The last 34 years’ data samples of power failure accidents in the China power grid are used to test the proposed method, and the numerical results show that the proposed self-organized criticality and trend analysis method can pave the way for further exploration of the mechanism of power failure in the China power grid.

scholarly journals Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Andrey Dmitriev ◽  
Victor Dmitriev ◽  
Stepan Balybin
Keyword(s):  
Time Series ◽  
Critical State ◽  
Empirical Investigation ◽  
Phenomenological Theory ◽  
Self Organization ◽  
Protest Movements ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Stochastic Sources ◽  
Adiabatic Mode

Recently, there has been an increasing number of empirical evidence supporting the hypothesis that spread of avalanches of microposts on social networks, such as Twitter, is associated with some sociopolitical events. Typical examples of such events are political elections and protest movements. Inspired by this phenomenon, we built a phenomenological model that describes Twitter’s self-organization in a critical state. An external manifestation of this condition is the spread of avalanches of microposts on the network. The model is based on a fractional three-parameter self-organization scheme with stochastic sources. It is shown that the adiabatic mode of self-organization in a critical state is determined by the intensive coordinated action of a relatively small number of network users. To identify the critical states of the network and to verify the model, we have proposed a spectrum of three scaling indicators of the observed time series of microposts.

scholarly journals Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Yongxiao Ge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
River Runoff ◽  
Temporal Trends ◽  
Temporal Distribution ◽  
Trend Test ◽  
Data Series ◽  
Mk Test ◽  
Comparison Results ◽  
Innovative Trend Analysis

This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the “peak” values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for “low” values, and 40 time series (44.94%) showed increasing patterns for “medium” values. According to the “low”, “medium”, and “peak” values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating “low”, “medium”, and “peak” values.

PUNCTUATED EQUILIBRIUM: A VIEW FROM THE PERSPECTIVE OF THE THEORY OF SELF-ORGANIZED CRITICALITY

METOD ◽  
2020 ◽  
pp. 416-442
Author(s):  
Dmitriy Zhukov
Keyword(s):  
Social Systems ◽  
Punctuated Equilibrium ◽  
Computer Experiments ◽  
Political Activity ◽  
Pink Noise ◽  
Social Transformations ◽  
Protest Movements ◽  
Self Organized ◽  
Long Time ◽  
Self Organized Criticality

Punctuated equilibrium is regarded as the state of natural and social systems manifested in occasional intense, quick bursts of activity. Within the framework of the theory of self-organized criticality (SOC), punctuated equilibrium can be formalized as pink noise. SOC theory, having been developed by the end of 1980s, was originally intended to explain natural science phenomena. However, soon after its presentation, it began to spread across the social and humanitarian field of knowledge. Critical state is one on the brink of a bifurcation point. It turns out that some systems can stay in a state of permanent choice for a fairly long time. The author presents the examples of punctuated equilibrium revealed in computer experiments with artificial societies, as well as through empirical observation (particularly, in the dynamics of voting patterns, internet activity, and protest movements in the past and present). The key concepts of SOC theory and tools for pink noise identification are laid out. The sandpile model has been given special attention. Certain papers have been analyzed in which SOC theory was applied to gain some political science knowledge. According to SOC, in certain cases, there is no need to search for some significant extraordinary factor to shed light on explosive social transformations (including revolutions and other bursts of social and political activity). Social transformations can be induced by quite ordinary - and thus undistinguished - properties of systems, micro-level pro- cesses, and local impulses. SOC theory, therefore, refocuses the attention of researchers from the search for direct causes of events to the identification of states of the subject that generates these events.

scholarly journals Comparison of Statistical Methods to Graphical Methods in Rainfall Trend Analysis: Case Studies from Tropical Catchments

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Upaka Rathnayake
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Climatic Factors ◽  
Data Series ◽  
Graphical Methods ◽  
Rainfall Trend ◽  
Comparison Analysis ◽  
Analysis Techniques ◽  
Rainfall Trends ◽  
Time Series Analyses

Time series analyses for climatic factors are important in climate predictions. Rainfall is being one of the most important climatic factors in today’s concern for future predictions; thus, many researchers analyze the data series for identifying potential rainfall trends. The literature shows several methods in identifying rainfall trends. However, statistical trend analysis using Mann–Kendall equation and graphical trend analysis are the two widely used and simplest tests in trend analysis. Nevertheless, there are few studies in comparing various methods in the trend analysis to suggest the simplest methods in analyzing rainfall trends. Therefore, this paper presents a comparison analysis of statistical and graphical trend analysis techniques for two tropical catchments in Sri Lanka. Results reveal that, in general, both trend analysis techniques produce comparable results in identifying rainfall trends for different time steps including annual, seasonal, and monthly rainfalls.

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