13 research outputs found

    Designing and Expanding Electrical Networks – Complexity and Combinatorial Algorithms

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    The transition from conventional to renewable power generation has a large impact on when and where electricity is generated. To deal with this change the electric transmission network needs to be adapted and expanded. Expanding the network has two benefits. Electricity can be generated at locations with high renewable energy potentials and then transmitted to the consumers via the transmission network. Without the expansion the existing transmission network may be unable to cope with the transmission needs, thus requiring power generation at locations closer to the energy demand, but at less well-suited locations. Second, renewable energy generation (e.g., from wind or solar irradiation) is typically volatile. Having strong interconnections between regions within a large geographical area allows to the smooth the generation and demand over that area. This smoothing makes them more predictable and the volatility of the generation easier to handle. In this thesis we consider problems that arise when designing and expanding electric transmission networks. As the first step we formalize them such that we have a precise mathematical problem formulation. Afterwards, we pursue two goals: first, improve the theoretical understanding of these problems by determining their computational complexity under various restrictions, and second, develop algorithms that can solve these problems. A basic formulation of the expansion planning problem models the network as a graph and potential new transmission lines as edges that may be added to the graph. We formalize this formulation as the problems Flow Expansion and Electrical Flow Expansion, which differ in the flow model (graph-theoretical vs. electrical flow). We prove that in general the decision variants of these problems are NP\mathcal{NP}-complete, even if the network structure is already very simple, e.g., a star. For certain restrictions, we give polynomial-time algorithms as well. Our results delineate the boundary between the NP\mathcal{NP}-complete cases and the cases that can be solved in polynomial time. The basic expansion planning problems mentioned above ignore that real transmission networks should still be able to operate if a small part of the transmission equipment fails. We employ a criticality measure from the literature, which measures the dynamic effects of the failure of a single transmission line on the whole transmission network. In a first step, we compare this criticality measure to the well-used N−1N-1 criterion. Moreover, we formulate this criticality measure as a set of linear inequalities, which may be added to any formulation of a network design problem as a mathematical program. To exemplify this usage, we introduce the criticality criterion in two transmission network expansion planning problems, which can be formulated as mixed-integer linear programs (MILPs). We then evaluate the performance of solving the MILPs. Finally, we develop a greedy heuristic for one of the two problems, and compare its performance to solving the MILP. Microgrids play an important role in the electrification of rural areas. We formalize the design of the cable layout of a microgrid as a geometric optimization problem, which we call Microgrid Cable Layout. A key difference to the network design problems above is that there is no graph with candidate edges given. Instead, edges and new vertices may be placed anywhere in the plane. We present a hybrid genetic algorithm for Microgrid Cable Layout and evaluate it on a set of benchmark instances, which include a real microgrid in the Democratic Republic of the Congo. Finally, instead of expanding electrical networks one may place electric equipment such as FACTS (flexible AC transmission system). These influence the properties of the transmission lines such that the network can be used more efficiently. We apply a model of FACTS from the literature and study the problem whether a given network with given positions and properties of the FACTS admits an electrical flow provided that FACTS are set appropriately. We call such a flow a FACTS flow. In this thesis we prove that in general it is NP\mathcal{NP}-complete to determine whether a network admits a FACTS flow, and we present polynomial-time algorithms for two restricted cases

    Discrete Mathematics and Symmetry

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    Some of the most beautiful studies in Mathematics are related to Symmetry and Geometry. For this reason, we select here some contributions about such aspects and Discrete Geometry. As we know, Symmetry in a system means invariance of its elements under conditions of transformations. When we consider network structures, symmetry means invariance of adjacency of nodes under the permutations of node set. The graph isomorphism is an equivalence relation on the set of graphs. Therefore, it partitions the class of all graphs into equivalence classes. The underlying idea of isomorphism is that some objects have the same structure if we omit the individual character of their components. A set of graphs isomorphic to each other is denominated as an isomorphism class of graphs. The automorphism of a graph will be an isomorphism from G onto itself. The family of all automorphisms of a graph G is a permutation group

    Bounding robustness in complex networks under topological changes through majorization techniques

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    Measuring robustness is a fundamental task for analyzing the structure of complex networks. Indeed, several approaches to capture the robustness properties of a network have been proposed. In this paper we focus on spectral graph theory where robustness is measured by means of a graph invariant called Kirchhoff index, expressed in terms of eigenvalues of the Laplacian matrix associated to a graph. This graph metric is highly informative as a robustness indicator for several realworld networks that can be modeled as graphs. We discuss a methodology aimed at obtaining some new and tighter bounds of this graph invariant when links are added or removed. We take advantage of real analysis techniques, based on majorization theory and optimization of functions which preserve the majorization order (Schurconvex functions). Applications to simulated graphs show the effectiveness of our bounds, also in providing meaningful insights with respect to the results obtained in the literature

    Symmetry in Graph Theory

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    This book contains the successful invited submissions to a Special Issue of Symmetry on the subject of ""Graph Theory"". Although symmetry has always played an important role in Graph Theory, in recent years, this role has increased significantly in several branches of this field, including but not limited to Gromov hyperbolic graphs, the metric dimension of graphs, domination theory, and topological indices. This Special Issue includes contributions addressing new results on these topics, both from a theoretical and an applied point of view

    On the Resistance-Harary Index of Graphs Given Cut Edges

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    Cacti with Extremal PI Index

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    The vertex PI index PI(G)=∑xy∈E(G)[nxy(x)+nxy(y)]PI(G) = \sum_{xy \in E(G)} [n_{xy}(x) + n_{xy}(y)] is a distance-based molecular structure descriptor, where nxy(x)n_{xy}(x) denotes the number of vertices which are closer to the vertex xx than to the vertex yy and which has been the considerable research in computational chemistry dating back to Harold Wiener in 1947. A connected graph is a cactus if any two of its cycles have at most one common vertex. In this paper, we completely determine the extremal graphs with the largest and smallest vertex PI indices among all the cacti. As a consequence, we obtain the sharp bounds with corresponding extremal cacti and extend a known result.Comment: Accepted by Transactions on Combinatorics, 201

    On Topological Indices And Domination Numbers Of Graphs

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    Topological indices and dominating problems are popular topics in Graph Theory. There are various topological indices such as degree-based topological indices, distance-based topological indices and counting related topological indices et al. These topological indices correlate certain physicochemical properties such as boiling point, stability of chemical compounds. The concepts of domination number and independent domination number, introduced from the mid-1860s, are very fundamental in Graph Theory. In this dissertation, we provide new theoretical results on these two topics. We study k-trees and cactus graphs with the sharp upper and lower bounds of the degree-based topological indices(Multiplicative Zagreb indices). The extremal cacti with a distance-based topological index (PI index) are explored. Furthermore, we provide the extremal graphs with these corresponding topological indices. We establish and verify a proposed conjecture for the relationship between the domination number and independent domination number. The corresponding counterexamples and the graphs achieving the extremal bounds are given as well
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