scholarly journals Phase Synchronization Stability of Non-Homogeneous Low-Voltage Distribution Networks with Large-Scale Distributed Generations

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1257 ◽  
Author(s):  
Shi Chen ◽  
Hong Zhou ◽  
Jingang Lai ◽  
Yiwei Zhou ◽  
Chang Yu
Keyword(s):  
Power Law ◽  
Coupling Strength ◽  
Large Scale ◽  
Phase Synchronization ◽  
Distribution Networks ◽  
Critical Coupling ◽  
Power Law Distribution ◽  
Distributed Generations ◽  
Strength Formula ◽  
The Impact

The ideal distributed network composed of distributed generations (DGs) has unweighted and undirected interactions which omit the impact of the power grid structure and actual demand. Apparently, the coupling relationship between DGs, which is determined by line impedance, node voltage, and droop coefficient, is generally non-homogeneous. Motivated by this, this paper investigates the phase synchronization of an islanded network with large-scale DGs in a non-homogeneous condition. Furthermore, we explicitly deduce the critical coupling strength formula for different weighting cases via the synchronization condition. On this basis, three cases of Gaussian distribution, power-law distribution, and frequency-weighted distribution are analyzed. A synthetical analysis is also presented, which helps to identify the order parameter. Finally, this paper employs the numerical simulation methods to test the effectiveness of the critical coupling strength formula and the superiority over the power-law distribution.

scholarly journals Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1648
Author(s):  
Marinko Barukčić ◽  
Toni Varga ◽  
Vedrana Jerković Jerković Štil ◽  
Tin Benšić
Keyword(s):  
Power System ◽  
Power Management ◽  
Computational Intelligence ◽  
Input Data ◽  
Optimization Problem ◽  
Optimal Allocation ◽  
Distribution Networks ◽  
Distributed Generations ◽  
Data Resolution ◽  
The Impact

The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network.

TWOFOLD IMPACT OF DELAYED FEEDBACK ON COUPLED OSCILLATORS

2007 ◽  
Vol 17 (07) ◽  
pp. 2517-2530 ◽  
Author(s):  
OLEKSANDR V. POPOVYCH ◽  
VALERII KRACHKOVSKYI ◽  
PETER A. TASS
Keyword(s):  
Time Delay ◽  
Coupling Strength ◽  
Coupled Oscillators ◽  
Phase Synchronization ◽  
Threshold Value ◽  
Phase Oscillators ◽  
Intermediate Coupling ◽  
Rich Variety ◽  
Dynamical Regimes ◽  
The Impact

We present a detailed bifurcation analysis of desynchronization transitions in a system of two coupled phase oscillators with delay. The coupling between the oscillators combines a delayed self-feedback of each oscillator with an instantaneous mutual interaction. The delayed self-feedback leads to a rich variety of dynamical regimes, ranging from phase-locked and periodically modulated synchronized states to chaotic phase synchronization and desynchronization. We show that an increase of the coupling strength between oscillators may lead to a loss of synchronization. Intriguingly, the delay has a twofold influence on the oscillations: synchronizing for small and intermediate coupling strength and desynchronizing if the coupling strength exceeds a certain threshold value. We show that the desynchronization transition has the form of a crisis bifurcation of a chaotic attractor of chaotic phase synchronization. This study contributes to a better understanding of the impact of time delay on interacting oscillators.

scholarly journals Activity-dependent myelination: A glial mechanism of oscillatory self-organization in large-scale brain networks

2020 ◽  
Vol 117 (24) ◽  
pp. 13227-13237 ◽  
Author(s):  
Rabiya Noori ◽  
Daniel Park ◽  
John D. Griffiths ◽  
Sonya Bells ◽  
Paul W. Frankland ◽  
...  
Keyword(s):  
White Matter ◽  
Large Scale ◽  
Phase Synchronization ◽  
Brain Networks ◽  
Self Organization ◽  
Conduction Delay ◽  
Neural Communication ◽  
Wide Range ◽  
The Impact ◽  
Activity Dependent

Communication and oscillatory synchrony between distributed neural populations are believed to play a key role in multiple cognitive and neural functions. These interactions are mediated by long-range myelinated axonal fiber bundles, collectively termed as white matter. While traditionally considered to be static after development, white matter properties have been shown to change in an activity-dependent way through learning and behavior—a phenomenon known as white matter plasticity. In the central nervous system, this plasticity stems from oligodendroglia, which form myelin sheaths to regulate the conduction of nerve impulses across the brain, hence critically impacting neural communication. We here shift the focus from neural to glial contribution to brain synchronization and examine the impact of adaptive, activity-dependent changes in conduction velocity on the large-scale phase synchronization of neural oscillators. Using a network model based on primate large-scale white matter neuroanatomy, our computational and mathematical results show that such plasticity endows white matter with self-organizing properties, where conduction delay statistics are autonomously adjusted to ensure efficient neural communication. Our analysis shows that this mechanism stabilizes oscillatory neural activity across a wide range of connectivity gain and frequency bands, making phase-locked states more resilient to damage as reflected by diffuse decreases in connectivity. Critically, our work suggests that adaptive myelination may be a mechanism that enables brain networks with a means of temporal self-organization, resilience, and homeostasis.

A Practical GIS-Based Reliability Estimation System for Large Scale Distribution Network

2012 ◽  
Vol 433-440 ◽  
pp. 1802-1810 ◽  
Author(s):  
Lin Guan ◽  
Hao Hao Wang ◽  
Sheng Min Qiu
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Network Reliability ◽  
Distribution Network ◽  
Reliability Assessment ◽  
Distribution Networks ◽  
Reliability Estimation ◽  
Assessment Model ◽  
Estimation System ◽  
The Impact

A new algorithm as well as the software design for large-scale distribution network reliability assessment is proposed in this paper. The algorithm, based on fault traversal algorithm, obtains network information from the GIS. The structure of distribution network data storage formats is described, facilitating automatic output of the feeders’ topological and corresponding information from the GIS. Also the judgment of load transfer is discussed and the method for reliability assessment introduced in this paper. Moreover, The impact of the scheduled outage is taken into account in the assessment model, making the results more in accordance with the actual situation. Test Cases show that the proposed method features good accuracy and effectiveness when applied to the reliability assessment of large-scale distribution networks.

Online Reviews' Trustworthiness Analysis Based on Power-Law Distribution

2013 ◽  
Vol 838-841 ◽  
pp. 3260-3267
Author(s):  
Qi Chang Yao ◽  
Xin Feng ◽  
Qi Ming Sun
Keyword(s):  
Power Law ◽  
Attitude Change ◽  
Large Scale ◽  
Online Shopping ◽  
Online Reviews ◽  
Subjective Perception ◽  
Power Exponent ◽  
Power Law Distribution ◽  
Consumer Reviews ◽  
Consumer Attention

In online shopping, studies on consumer reviews are mostly based on the Attitude Change Model. Illustrated from the perspective of perceived trustworthiness, however, it is not easy to measure and characterize the subjective perception of consumers. Starting from the inherent property of online reviews and based on the real data of 360buy which is the domestic large-scale B2C commerce website in China, this paper focuses on the interval distribution of consumer reviews and the data for statistical analysis. Research finds that the distribution of reviews interval can be depicted by the power-law function and there is a monotonically increasing relationship between power-exponent and the customers concerns with the commodity, the higher exponent, the attention consumer get. The findings give an objective basis to judge the credibility of online reviews. The relationship between power-exponent and the consumer attention has demonstrated the vital role of consumer attention in online shopping, and then the double parity between attention and exponent will effectively regulate the e-commerce market environment and promote its healthy operation. Tech Publications.

scholarly journals Exploring the Citywide Human Mobility Patterns of Taxi Trips through a Topic-Modeling Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hui Xiong ◽  
Kaiqiang Xie ◽  
Lu Ma ◽  
Feng Yuan ◽  
Rui Shen
Keyword(s):  
Power Law ◽  
Traffic Management ◽  
Large Scale ◽  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Human Mobility ◽  
Mobility Patterns ◽  
Power Law Distribution ◽  
Modeling Analysis ◽  
Wide Range

Understanding human mobility patterns is of great importance for a wide range of applications from social networks to transportation planning. Toward this end, the spatial-temporal information of a large-scale dataset of taxi trips was collected via GPS, from March 10 to 23, 2014, in Beijing. The data contain trips generated by a great portion of taxi vehicles citywide. We revealed that the geographic displacement of those trips follows the power law distribution and the corresponding travel time follows a mixture of the exponential and power law distribution. To identify human mobility patterns, a topic model with the latent Dirichlet allocation (LDA) algorithm was proposed to infer the sixty-five key topics. By measuring the variation of trip displacement over time, we find that the travel distance in the morning rush hour is much shorter than that in the other time. As for daily patterns, it shows that taxi mobility presents weekly regularity both on weekdays and on weekends. Among different days in the same week, mobility patterns on Tuesday and Wednesday are quite similar. By quantifying the trip distance along time, we find that Topic 44 exhibits dominant patterns, which means distance less than 10 km is predominant no matter what time in a day. The findings could be references for travelers to arrange trips and policymakers to formulate sound traffic management policies.

scholarly journals Distributionally Robust Distributed Generation Hosting Capacity Assessment in Distribution Systems

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2981 ◽  
Author(s):  
Mohammad Seydali Seyf Abad ◽  
Jin Ma ◽  
Ahmad Ahmadyar ◽  
Hesamoddin Marzooghi
Keyword(s):  
Robust Optimization ◽  
Distributed Generation ◽  
Optimization Model ◽  
Distribution Systems ◽  
Historical Data ◽  
Distribution Networks ◽  
Distributionally Robust Optimization ◽  
Distributed Generations ◽  
Distributionally Robust ◽  
The Impact

Uncertainties associated with the loads and the output power of distributed generations create challenges in quantifying the integration limits of distributed generations in distribution networks, i.e., hosting capacity. To address this, we propose a distributionally robust optimization-based method to determine the hosting capacity considering the voltage rise, thermal capacity of the feeders and short circuit level constraints. In the proposed method, the uncertain variables are modeled as stochastic variables following ambiguous distributions defined based on the historical data. The distributionally robust optimization model guarantees that the probability of the constraint violation does not exceed a given risk level, which can control robustness of the solution. To solve the distributionally robust optimization model of the hosting capacity, we reformulated it as a joint chance constrained problem, which is solved using the sample average approximation technique. To demonstrate the efficacy of the proposed method, a modified IEEE 33-bus distribution system is used as the test-bed. Simulation results demonstrate how the sample size of historical data affects the hosting capacity. Furthermore, using the proposed method, the impact of electric vehicles aggregated demand and charging stations are investigated on the hosting capacity of different distributed generation technologies.

Empirical Analysis of Relationship-based User Reposting Behavior on Microblog Network

2015 ◽  
Vol 7 (3) ◽  
pp. 1-12
Author(s):  
Su-Meng Diao ◽  
Yun Liu ◽  
Qing-An Zeng
Keyword(s):  
Social Influence ◽  
Empirical Analysis ◽  
Power Law ◽  
Social Service ◽  
Large Scale ◽  
Activity Level ◽  
Information Propagation ◽  
Interval Time ◽  
The Impact

Microblogs have become a significant online social service for information propagation. Compared with other SNS, a microblog makes use of a flexible unidirectional subscription structure to encourage users to get information from others. In this paper, the authors performed relationship-based large-scale statistics and analyzed long-term reposting behavior. The total number of reposts from a certain followee with a bidirectional or unidirectional relationship is power-law, as well as a reposting interval time. Statistics suggest the curve of bidirectional friends decays slower with a smaller slope, which implies the interactions between bidirectional friends are more stable and intensive. Moreover, reposts from bidirectional friends take approximate 55 percentages, although bidirectional relationships comprise only 33 percent of relationships. Furthermore, the authors investigated the impact of following relationships and found that users focus more on social influence and activity level for unidirectional friends; however, for bidirectional friends, interactions and closeness are more crucial.

Self-Organized Critical Models

2003 ◽  
Author(s):  
M. E. J. Newman ◽  
R. G. Palmer
Keyword(s):  
Computer Simulations ◽  
Power Law ◽  
Large Scale ◽  
Fitness Landscape ◽  
Fitness Landscapes ◽  
Power Law Distribution ◽  
Edge Of Chaos ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Phenotype Space

The models discussed in the last chapter are intriguing, but present a number of problems. In particular, most of the results about them come from computer simulations, and little is known analytically about their properties. Results such as the power-law distribution of extinction sizes and the system's evolution to the "edge of chaos" are only as accurate as the simulations in which they are observed. Moreover, it is not even clear what the mechanisms responsible for these results are, beyond the rather general arguments that we have already given. In order to address these shortcomings, Bak and Sneppen (1993; Sneppen et al. 1995; Sneppen 1995; Bak 1996) have taken Kauffman's ideas, with some modification, and used them to create a considerably simpler model of large-scale coevolution which also shows a power-law distribution of avalanche sizes and which is simple enough that its properties can, to some extent, be understood analytically. Although the model does not directly address the question of extinction, a number of authors have interpreted it, using arguments similar to those of section 1.2.2.5, as a possible model for extinction by biotic causes. The Bak-Sneppen model is one of a class of models that show "self-organized criticality," which means that regardless of the state in which they start, they always tune themselves to a critical point of the type discussed in section 2.4, where power-law behavior is seen. We describe self-organized criticality in more detail in section 3.2. First, however, we describe the Bak-Sneppen model itself. In the model of Bak and Sneppen there are no explicit fitness landscapes, as there are in NK models. Instead the model attempts to mimic the effects of landscapes in terms of "fitness barriers." Consider figure 3.1, which is a toy representation of a fitness landscape in which there is only one dimension in the genotype (or phenotype) space. If the mutation rate is low compared with the time scale on which selection takes place (as Kauffman assumed), then a population will spend most of its time localized around a peak in the landscape (labeled P in the figure).

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