Water Network Design Using a Multiobjective Real Options Framework

Abstract

Water distribution networks (WDNs) are an essential element of urban infrastructure. To achieve a good level of performance, the traditional design of WDNs based on expected future conditions should be replaced by a flexible design, using real options (ROs), that accounts for uncertainty by taking a broader view of possible future options. This work proposes a multiobjective ROs framework that sets out to reduce costs, minimize hydraulic pressure deficiency, and a third objective for minimizing carbon emissions. A multiobjective simulated annealing algorithm is used to identify the Pareto-optimal solutions, thus enabling a trade-off analysis between solutions. These trade-offs show that a low pressure deficit solution is achieved by increasing investment at a much faster rate after a certain pressure deficit threshold (60 m). Also, the pressure deficits can only be reduced by increasing carbon emissions. Finally, this work also emphasizes the importance of including carbon emissions as a specific objective by comparing the results of the proposed model and another one that did not cover the environmental objective. The results show that it is possible to reduce CO2 for the same level of capital expenditure or the same level of network pressure deficits if carbon emissions are minimized in the optimization process.

Circular Economy and Value Creation: Sustainable Finance with a Real Options Approach

“…Additionally, a typology of real options was initially available in the work by [60]: defer option, abandon option, expansion option, and contract option, among others. Far from being exhaustive, theoretical and practical applications are numerous in fields such as mining investment (see [61] for a review), water utilities ( [62,63]), power transmission investment ( [64]), wireless network management ( [65]), pharmaceutical R&D valuation ( [66]), oil investments ( [67]), carbon capture and storage investment ( [68]), solar photovoltaic power generation ( [69]), among many others. To our knowledge, however, papers combining real options and the circular economy are still to come.…”

“…To determine the option value at a previous date, T 3 -h, we first compute the continuation value at each node of the value tree, then the value with flexibility, which is compared with the value without flexibility, thereby obtaining the option value. Notice that Equations ( 61) and (62) involve both the remanufacture value with flexibility and the recycle value. This procedure is repeated backward up to reach the origin of the value tree.…”

Robust Design of a Real-Life Water Distribution Network under Different Demand Scenarios

“…Flexible design [52][53][54][55][56][57][58] Multi-criteria decision analysis [9] Stochastic, deterministic equivalent, surrogate, and fuzzy logic approaches deal with uncertainty by generating random demands according to a probability distribution with defined mean and variance. In a stochastic approach, for instance, a system is designed to meet a certain level of reliability, e.g., 99%.…”

Functional Feasibility in Optimal Evaluation of Water Distribution Network Performances

“…This approach was tested on the Anytown and New York Tunnels networks, and the results demonstrate that the flexible design can lead to lower economic costs and a better hydraulic performance when compared with the corresponding deterministic staged design. Marques et al used simulated annealing to solve a two-objective optimization model, including flexible design [29], and then considering the three-objective optimization problem, they minimized the costs, pressure deficits and carbon emissions [30].…”