DOOCN-XIV: Cascading Failures in Complex Networks

Dynamics On and Of Complex Networks 2023

The satellite will be held using Zoom Video Webinar system. link

Workshop videos are now available here.

The Dynamics On and Of Complex Networks (DOOCN) workshop series, aims at exploring statistical dynamics on and off complex networks. Dynamics on networks refers to the different types of processes that take place on networks, like spreading, diffusion, and synchronization. Modeling such processes is strongly affected by the topology and temporal variation of the network structure, i.e., by the dynamics of networks. Understanding and analyzing cascading failures in complex networks have been the focus of research for years. However, the complex interactions among the large number of components in these systems and their contributions to cascading failures are not yet completely understood. This motivates us to focus on "Cascading Failures in Complex Networks" as the topic of interest in the 2023 edition.

Understanding and analyzing cascading failures in complex systems is an important task. As an example, cascading failures in power grids can be defined as successive interdependent failures of components in the system, which are usually initiated by few outages due to internal or exogenous disturbances and are propagated in a relatively short period of time leading to large blackouts. While large blackouts are infrequent, their occurrence still has substantial risks associated with the significant economic losses and social impacts that they cause. Various studies and models have been developed to understand and control these complex phenomena. Cascading failures can also occur in computer networks (such as the Internet) in which network traffic is severely impaired or halted to or between larger sections of the network, caused by failing or disconnected hardware or software. In finance, the risk of cascading failures of financial institutions is referred to as systemic risk: the failure of one financial institution may cause other financial institutions to fail, cascading throughout the system. Biochemical cascades exist in biology, where a small reaction can have system-wide implications. One negative example is ischemic cascade, in which a small ischemic attack releases toxins which kill off far more cells than the initial damage, resulting in more toxins being released. The vast application of the concept of cascading failures motivates us to focus on this specific following theme this year.

The 14^th edition of the DOOCN workshop, “DOOCN-XIV: Cascading Failures in Complex Networks; will be held on August 28-29, 2023 in conjunction with the upcoming STATPHYS28 2023 conference which will take place during 7–11 August 2023, in Tokyo, Japan although the workshop will be held online.

Invited Speakers

Program

• All times are in Central European Time (CET)
• August 28
• 14:30–14:35: Opening
• 14:35–15:10: Invited Talk by Frank Hellmann

  Title: Complex Coupling Formulations for Power Grid Dynamics

  Abstract: Collective phenomena like synchronization underpin the function of the power grid. I present a new and surprising formulation of the physics of the grid in terms of the coupling between nodes. This resembles an adaptive network formulation and enables an elegant analysis of the full systems dynamics. Using this formulation I present a new proof of concept quasi-local control law for power grids that guarantees synchronization. I will also present initial results on empirically derived complex oscillator models for the future grid in this approach.

• 15:10–15:45: Invited Talk by Christian Beck

  Title: Propagation of frequency perturbations in power grids

  Abstract: A large amount of experimentally measured data is now available to analyse the statistics of power grid frequency deviations from 50Hz and to understand their dynamical behaviour. I briefly present superstatistical models that can be used in this context. I will then discuss the propagation speed of local perturbations in the grid, including both large-scale propagation of a given perturbation as well frequency differences on much smaller scales.

• 15:45–16:00: Coffee Break
• 16:00–16:35: Invited Talk by Nora Molkenthin

  Title: Sampling vulnerable power grid networks using MCMC

  Abstract: The transition to the exclusive use of renewable energy sources poses a difficult problem for the electricity grid, as the states of the grid become more variable and unpredictable, possibly leading to states vulnerable to cascading failures. Here we want to address this problem by using Marcov Chain Monte Carlo (MCMC) sampling to generate and analyze ensembles of vulnerable states. This allows us to better understand and even predict such states from the input patterns alone. We find that more clustered generators and consumers lead to larger failure cascades and non-local first outages are an early warning sign for unfolding large cascades.

• 16:35–17:10: Invited Talk by Dirk Witthaut

  Title: Cascading failures in power grids: Physical insights and robust grid structures

  Abstract: Cascading failures are the biggest threat for the stability of electric power systems: Large blackouts can typically be traced back to the failure of a single transmission element. In my talk I will analyze the spreading of cascades from the perspective of theoretical physics and network science. The main question is: Given the failure of a single transmission line, how do power flows change and where are secondary failures most likely? Based on this analysis, I discuss specific structural features that make a network more robust to transmission line failures. We show that the spreading of a cascade between different parts of a network can be large suppressed by an appropriate design.

• 17:10–17:35: Contributed Talk by Guga Mikaberidze

  Title: Sandpile cascades on oscillator networks: the BTW model meets Kuramoto

  Abstract: Cascading failures abound in complex systems, and the BTW sandpile model provides a theoretical underpinning for their analysis. Yet, it does not account for the possibility of nodes having oscillatory dynamics, such as in power grids and brain networks. We will consider a network of Kuramoto oscillators upon which the BTW model is unfolding, enabling us to study how the feedback between the oscillatory and cascading dynamics can lead to new emergent behaviors. We assume that the more out-of-sync a node is with its neighbors, the more vulnerable it is and lower its load-carrying capacity accordingly. And when a node topples and sheds load, its oscillatory phase is reset at random. This leads to novel cyclic behavior at an emergent, long timescale. The system spends the bulk of its time in a synchronized state where the load builds up with minimal cascades. Yet, eventually, the system reaches a tipping point where a large cascade triggers a "cascade of larger cascades,” which can be classified as a Dragon King event. The system then undergoes a short transient back to the synchronous build-up phase. The coupling between capacity and synchronization gives rise to endogenous cascade seeds in addition to the standard exogenous ones, and we will show their respective roles.

• August 29
• 14:30–15:05: Invited Talk by Mattia Frasca/Lucia Gambuzza

  Title: Reconstruction of cascading failures in dynamical models of power grids

  Abstract: In this talk we propose a method to reconstruct the active links of a power network described by a second-order Kuramoto model and subject to dynamically induced cascading failures. Starting from the assumption (realistic for power grids) that the structure of the network is known, our method reconstructs the active links from the evolution of the relevant dynamical quantities of the nodes of the system, that is, the node phases and angular velocities

• 15:05–15:40: Invited Talk by Pere Colet

  Title: Blackout risk reduction by segmenting large power grids with controllable HVDC lines

  Abstract: Large electrical transmission networks are susceptible to undergo very large blackouts due to cascading failures, with a very large associated economical cost. We analyze the effect of segmenting large power grids using controllable lines, such as high-voltage direct-current lines, to reduce the risk of blackouts. During a blackout, the power flowing through these lines is controlled in order to minimize the load shed. As a result, the segmented grids have a substantially lower risk of blackouts than the original network. The control method is shown to be specially efficient in reducing blackouts affecting more than one zone. As a case study we consider the continental European grid with two possible segmentations: one through the Pyrenees separating the Iberian peninsula from the rest of Europe and the other dividing the network in approximately two halves, Eastern and Western Europe.

• 15:40–15:55: Coffee Break
• 15:55–16:20: Contributed Talk by Philipp Böttcher

  Title: Cascading Failures and Critical Infrastructures in Future Renewable Power Systems

  Abstract: Mitigating the effects of climate change by reducing the emission of greenhouse gases is the key challenge of the coming decades. To this end, the world’s power systems are undergoing a rapid transformation, shifting away from carbon-intensive power generation by thermal power plants to renewable power sources, which is mainly provided by wind and solar power generation. As a result, there is a growing importance of long-distance power transmission, while the intrinsic system inertia provided by thermal power plants decreases. This poses several challenges to the system such as an accelerated dynamics and a higher loaded power grid, which might lead to a higher control effort to keep the system operating within safe margins. These developments make power grids more vulnerable to cascading failures, which may result in a splitting of the grid and eventually in a large-scale blackout. A system split is one of the worst contingencies a power system can experience as it results in the power system being separated into several desynchronized components. This might have far reaching consequences for the power system like, for instance, the system split in November of 2006 that left millions of people without electricity. While such large system splits are rare, several smaller splits were observed in recent years, which underlines the need to understand how these system splits can occur and what their impact is. In this work, we use the state-of-the-art open energy system model PyPSA to generate future energy systems for different carbon reduction targets. Subsequently, we trigger line failures to investigate the likelihood of cascading failures that lead to systems splits in the European power grid. We determine which splits are most likely and dangerous to highlight their impact on the European power system. Additionally, we identify critical infrastructure elements, i.e., transmission lines that either trigger a system split or are involved in a cascade that leads to a system split. Understanding how the triggers, impact, and likelihood of system splits change for future renewable power systems, is a first step towards finding mitigation strategies that guarantee safe and reliable power systems.

• 16:20–16:45: Contributed Talk by Tobias Ohlinger

  Title: Assessing the Ability of Graph Neural Networks to Predict Power Outages of Cascading Failures In a Power Grid

  Abstract: Cascading power failures are a serious problem in the operation of power grids. These failures can lead to significant economic losses, social disruption, and even loss of life. Predicting the occurrence of cascading power failures and their extent is essential for power grid operators to take appropriate preventive and corrective actions. Recently, Graph Neural Networks (GNNs) have shown great potential in solving complex problems related to graph-structured data. This Presentation aims to assess the ability of GNNs to predict power outages resulting from cascading failures in a power grid.

• 16:45–17:10: Contributed Talk by Alex Schmauss

  Title: Influence of Complex Networks on Ride-Pooling Systems

  Abstract: Ride-pooling is an efficient technique to lower negative aspects of individual traffic by cars like CO2-emissions or noise. Ride-pooling services bundle similar rides together, implying that the number of required vehicles and the overall number of rides decreases in the service area. Since the necessary infrastructure is already in place, ride-pooling can be implemented quickly. It can work as door-to-door service or use stops. However, since studies show that the first case is inefficient, we work with discrete stop networks. Here we study, which stop networks perform the best at minimizing the average passenger travel time ts. To draw the most efficient networks from the infinite set of possible networks that can be created on every road network, a Markov Chain Monte Carlo algorithm (MCMC) is used. Starting from an initial network, in each step of the MCMC, a proposal network is generated from the last accepted network by pooling or splitting stops. The efficiency of a network is determined by evaluating ts from a ride-pooling simulation. The proposed network is then accepted with a probability, ensuring more efficient networks are always accepted, while less efficient ones only have a small acceptance probability. In the result networks, stops at intersections are preferred. Stops that lead to detours are ignored and the area served by the system is reduced. Furthermore, it can be deduced from the result networks that the average travel time can be approximated from the networks themselves.

• 17:10–17:15: Conclusion

Organizers

Simona Olmi

Institute for Complex Systems, Florence, Italy

Mehrnaz Anvari,

Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Germany

Fakhteh Ghanbarnejad

Ghanbarnejad, Potsdam Institute for Climate Impact Research (PIK),Germany

Sandipan Sikdar

Leibniz University Hannover, Germany

Soumajit Pramanik

Indian Institute of Technology Bhilai, India

History

The first Dynamics On and Of Complex Networks (DOOCN I) took place in Dresden, Germany, on 4th October 2007, as a satellite workshop of the European Conference on Complex Systems 07. The workshop received a large number of quality submissions from authors pursuing research in multiple disciplines, thus making the forum truly inter-disciplinary. There were around 20 speakers who spoke about the dynamics on and of different systems exhibiting a complex network structure, from biological systems, linguistic systems, and social systems to various technological systems like the Internet, WWW, and peer-to-peer systems. The organizing committee has published some of the very high quality original submissions as an edited volume from Birkhauser, Boston describing contemporary research position in complex networks.

After the success of DOOCN I, the organizers launched Dynamics On and Of Complex Networks – II (DOOCN II), a two days satellite workshop of the European Conference of Complex Systems 08. DOOCN II was held in Jerusalem, Israel, on the 18th and 19th September 2008.

DOOCN III was held as a satellite of ECCS 2009 in the University of Warwick, UK on 23rd and 24th of September. In continuation, DOOCN IV was held again as a satellite of ECCS 2010 in the University Institute Lisbon, Portugal on 16th September.

DOOCN V was held as a satellite of ECCS 2011 in the University of Vienna on 14th – 15th September 2011.

DOOCN VI took place in Barcelona, as a satellite to ECCS 2013, and focused on Semiotic Dynamics in time-varying social media. As DOOCN I, the other five DOOCN workshops counted with a large number participants and attracted prominent scientist in the field.

DOOCN VII, held in Lucca as a satellite to ECCS 2014, focused on Big Data aspects. DOOCN VIII was held in Zaragoza with focus also on BigData aspects.

The 9th edition of DOOCN was held in Amsterdam at Conference on Complex Systems (CCS) with the theme “Mining and learning for complex networks”.

The 2017 edition of DOOCN was held in Indianapolis USA in conjunction with NetSci 2017.

The 2018 edition of DOOCN XI was held in Thessaloniki, Greece at Conference on Complex Systems (CCS) with the theme “Machine learning for complex networks”.

The 2019 edition of DOOCN XII was held in Burlington, Vermont, USA in conjunction with NetSci 2019 with the theme “Network Representation Learning”.

The 2020 edition of DOOCN XIII was held online in conjunction with NetSci 2020 with the theme “Network Learning”.

DOOCN Book Series

The organizing committees of the DOOCN workshop series have published three Birkhäuser book volumes, from selected talks from the series.

• Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences
• Dynamics On and Of Complex Networks, Volume 2: Applications to Time-Varying Dynamical Systems
• Dynamics On and Of Complex Networks III: Machine Learning and Statistical Physics Approaches