MATCASC: A tool to analyse cascading line outages in power grids

Blackouts in power grids typically result from cascading failures. The key importance of the electric power grid to society encourages further research into sustaining power system reliability and developing new methods to manage the risks of cascading blackouts. Adequate software tools are required to better analyze, understand, and assess the consequences of the cascading failures. This paper presents MATCASC, an open source MATLAB based tool to analyse cascading failures in power grids. Cascading effects due to line overload outages are considered. The applicability of the MATCASC tool is demonstrated by assessing the robustness of IEEE test systems and real-world power grids with respect to cascading failures

Context-Independent Centrality Measures Underestimate the Vulnerability of Power Grids

Power grids vulnerability is a key issue in society. A component failure may trigger cascades of failures across the grid and lead to a large blackout. Complex network approaches have shown a direction to study some of the problems faced by power grids. Within Complex Network Analysis structural vulnerabilities of power grids have been studied mostly using purely topological approaches, which assumes that flow of power is dictated by shortest paths. However, this fails to capture the real flow characteristics of power grids. We have proposed a flow redistribution mechanism that closely mimics the flow in power grids using the PTDF. With this mechanism we enhance existing cascading failure models to study the vulnerability of power grids. We apply the model to the European high-voltage grid to carry out a comparative study for a number of centrality measures. `Centrality' gives an indication of the criticality of network components. Our model offers a way to find those centrality measures that give the best indication of node vulnerability in the context of power grids, by considering not only the network topology but also the power flowing through the network. In addition, we use the model to determine the spare capacity that is needed to make the grid robust to targeted attacks. We also show a brief comparison of the end results with other power grid systems to generalise the result.Comment: Pre-Proceedings of CRITIS '1

Identifying public values and spatial conflicts in urban planning

Identifying the diverse and often competing values of citizens, and resolving the consequent public value conflicts, are of significant importance for inclusive and integrated urban development. Scholars have highlighted that relational, value-laden urban space gives rise to many diverse conflicts that vary both spatially and temporally. Although notions of public value conflicts have been conceived in theory, there are very few empirical studies that identify such values and their conflicts in urban space. Building on public value theory and using a case-study mixed-methods approach, this paper proposes a new approach to empirically investigate public value conflicts in urban space. Using unstructured participatory data of 4,528 citizen contributions from a Public Participation Geographic Information Systems in Hamburg, Germany, natural language processing and spatial clustering techniques are used to identify areas of potential value conflicts. Four expert workshops assess and interpret these quantitative findings. Integrating both quantitative and qualitative results, 19 general public values and a total of 9 archetypical conflicts are identified. On the basis of these results, this paper proposes a new conceptual tool of Public Value Spheres that extends the theoretical notion of public-value conflicts and helps to further account for the value-laden nature of urban space

Time Dynamics of the Dutch Municipality Network

Based on data sets provided by Statistics Netherlands and the International Institute of Social History, we investigate the Dutch municipality merging process and the survivability of municipalities over the period 1830-2019. We examine the dynamics of the population and area per municipality and how their distributions evolved during the researched period. We apply a Network Science approach, where each node represents a municipality and the links represent the geographical interconnections between adjacent municipalities via roads, railways, bridges or tunnels which were available in each specific yearly network instance. Over the researched period, we find that the distributions of the logarithm of both the population and area size closely follow a normal and a logistic distribution respectively. The tails of the population distributions follow a power-law distribution, a phenomenon observed in community structures of many real-world networks. The dynamics of the area distribution are mainly determined by the merging process, while the population distribution is also driven by the natural population growth and migration across the municipality network. Finally, we propose a model of the Dutch Municipality Network that captures population increase, population migration between municipalities and the process of municipality merging. Our model allows for predictions of the population and area distributions over time.Comment: 48 pages, 26 figure

Supplemental Material - Disadvantaged communities have lower access to urban infrastructure

Supplemental Material for Disadvantaged communities has lower access to urban infrastructure by Leonardo Nicoletti, Mikhail Sirenko and Trivik Verma in Environment and Planning B: Urban Analytics and City Science</p

Supplemental Material - A multi-city study on structural characteristics of bicycle networks

Supplemental Material for A multi-city study on structural characteristics of bicycle networks by Giulia Reggiani, Trivik Verma, Winnie Daamen and Serge Hoogendoorn and Linda Theron in Environment and Planning B: Urban Analytics and City Science</p

Extracting spatiotemporal commuting patterns from public transit data

Public transit networks in cities are crucial in addressing the transforming mobility needs of citizens for work, services and leisure. The rapid changes in urban demographics pose several challenges for the efficient management of transit services. To forecast transit demand, planners often resort to sociological investigations, modelling or population data that are either difficult to obtain, inaccurate or outdated. How can we then estimate the variable demand for mobility? We propose a simple method to identify the spatiotemporal demand for public transit in a city. Using a Gaussian mixture model, we decompose empirical ridership data into a set of temporal demand profiles representative of ridership over any given day. A case of ≈ 4.6 million daily transit traces of the primary mode of underground services from the Greater London region reveals distinct commuting profiles. We find that a weighted mixture of these profiles can generate any station traffic remarkably well, uncovering spatially concentric clusters of mobility needs. Our results also suggest that heavily used stations that exhibit mixed-use commuting patterns are generally located in the cluster of the central business district and stations away from the centre of the city are largely single use residential areas. Overall, identifying mixed temporal and spatial use of stations diverging from macro mobility patterns in public transit indicates that our approach may be useful in a detailed understanding of integrated transit planning for heterogeneous needs of travellers