(361e) Systematic Design and Optimization of Water-Energy Nexus for Sustainable Regional Planning
In this work, we introduce a novel Water-Energy Nexus (WEN) superstructure for the optimal regional energy-water planning. The superstructure is comprised of energy and water resources, energy sources (acting also as water sinks), water sources (acting also as energy sinks), and energy and water consumers. The sources are the intermediate facilities that receive water and energy from the resources, exchange streams with each other and provide upgraded products to the consumers . The formulation considers, (i) finite resource availabilities, (ii) consumer demands to be satisfied, (iii) conversion, intensity and capacity factors of potential sources, (iv) location-allocation of the sources and, (v) water reclaim from the consumers and reuse by extensive water treatment . Optimizing the superstructure allocates the appropriate energy and water sources (combination of generating technologies, generating capacities, connectivity, location), to minimize the total resource supply, generation, and transportation cost. This problem constitutes a generalized instance of Capacitated Multi-facility Weber Problem (CMWP) , which also considers, (i) economic objective, (ii) existence of two products (energy and water), and (iii) flows and distances between non-fixed energy and water sources.
The problem is formulated as a mixed-integer nonlinear program (MINLP). The existence of nonlinearities arises from the Euclidean distance definitions. To address the nonconvexity and the poor solution scaling with increasing number of entities (resources, consumers, potential sources), we develop a bilevel decomposition algorithm as an extension from Lara et al. (2018) . The 2D location space is discretized, yielding a lower bounding MILP master problem. Then, by fixing the binary variables of selection of sources, streams, and discretized cells, the original problem is reduced to an NLP subproblem of reduced dimensionality with tighter bounds for distance and coordinate variables. An additional challenge exists due to the stream exchange between non-fixed intermediate sources, which makes the MILP problem of even larger size, especially with refined partitioning. The performance of the algorithm is demonstrated in example problems, and the applicability of the WEN superstructure is demonstrated in regional case studies of Texas Counties of different size.
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