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2017 | OriginalPaper | Buchkapitel

16. Partitioning Approaches for Large-Scale Water Transport Networks

verfasst von : Carlos Ocampo-Martínez, Vicenç Puig

Erschienen in: Real-time Monitoring and Operational Control of Drinking-Water Systems

Verlag: Springer International Publishing

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Abstract

Large-scale systems (LSS), such as WTNs, present control theory with new challenges due to the large size of the plant and of its model. In order to apply decentralized or distributed control approaches to LSS, there is a prior problem to be solved: the system decomposition into subsystems. The importance of this issue has already been reported in the general literature of decentralized control of LSS. The decomposition of the system into subsystems could be carried out during the modelling of the process by identifying subsystems as parts of the system on the basis of physical insight, intuition or experience. But, when a large-scale complex system with many states, inputs and outputs is considered, it may be difficult, even impossible, to obtain partitions by physical reasoning. A more appealing alternative is to develop systematic methods, which can be used to decompose a given system by extracting information from its structure and representing it as a graph. Then, this structural information can be analysed by using methods coming from graph theory. This chapter discusses partitioning approaches towards the development of subsystem decomposition methods for LSS by reviewing automatic decomposition algorithms and techniques based on graph partitioning. The general aim of the discussed methods is to provide decompositions consisting of sets of non-overlapping subgraphs whose number of vertices is as similar as possible and the number of interconnecting edges between them is minimal. The real case study based on the Barcelona WTN in Chap. 2 is used to exemplify the discussed decomposition methodologies.

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Fußnoten
1
The incidence matrix of a directed graph \(G(\mathcal {V},\mathcal {E})\), denoted as \(\mathbf {B}_{ij}\), is defined such that
$$\begin{aligned} {\mathbf {B}}_{ij} = \left\{ \begin{array}{ll} -1&{} \text {if the edge} z_j \text {leaves vertex} v_i,\\ 1&{} \text {if the edge} z_j \text {enters vertex} v_i,\\ 0&{} \text {otherwise}. \end{array}\right. \end{aligned}$$
This matrix has dimensions \(\varphi \times \eta _e\), where \(\varphi \) corresponds with the total number of vertices and \(\eta _e\) denotes de total number of edges [2]. Additionally, the weight of the j-th vertex, denoted as \(\omega ^j\), for \(j=1,2, \dots ,\varphi \), where \(\varphi ~\triangleq ~|\mathcal {V}|\), is computed. The weight \(\omega ^j\) represents the number of edges connected to this vertex. Moreover, \(\omega ^j\) is also known as the vertex degree [5].
 
2
See Problem 16.1.
 
3
Two subgraphs are called neighbours if they are contiguous and share edges (see, e.g., [1] among many others).
 
4
Consider a variable to be masked when it does not belong to any set since it has already been classified in a previous iteration.
 
5
Notice that increasing the parameter \(\delta \) implies that \(\sigma ^2_{\varepsilon _i}\) becomes bigger.
 
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Metadaten
Titel
Partitioning Approaches for Large-Scale Water Transport Networks
verfasst von
Carlos Ocampo-Martínez
Vicenç Puig
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-50751-4_16

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