The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.

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Water distribution systems (WDSs) as critical infrastructures are subject to demand peaks due to daily consumption fluctuations, as well as long term changes in the demand pattern due to increased urbanization. Resilient design of water distribution systems is of high relevance to water suppliers. The challenging combinatorial problem of high-quality and, at the same time, low-cost water supply can be assisted by cost-benefit optimization to enhance the resilience of existing main line WDSs, as shown in this paper. A Mixed Integer Linear Problem, based on a graph-theoretical resilience index, is implemented considering WDS topology. Utilizing parallel infrastructures, specifically those of the urban transport network and the water distribution network, makes allowances for physical constraints, in order to adjust the existing WDS and to enhance resilience. Therefore, decision-makers can be assisted in choosing the optimal adjustment of WDS depending on their investment budget. Furthermore, it can be observed that, for a specific urban structure, there is a convergence of resilience enhancement with higher costs. This cost-benefit optimization is conducted for a real-world main line WDS, considering also the limitations of computational expenses.

Abstract

Water distribution networks are the backbone of any municipal water supply. Their task is to supply the population regardless of the respective demand. High resilience of these infrastructures is of great importance and has brought these infrastructures into the focus of science and politics. At the same time, the data collected is highly sensitive and often openly unavailable. Therefore, researchers have to rely on models that represent the topology of these infrastructures. In this work, a model is developed that allows the topology of an urban water infrastructure to be mapped using the example of Cologne, Germany by combining freely available data. On the one hand, spatial data on land use (local climate zones) are used to disaggregate the water demand within the city under consideration. On the other hand, the parallelism of water and urban transportation infrastructures is used to identify the topology of a network by applying optimization methods. These networks can be analyzed to identify vulnerable areas within urban structures.