Life Cycle Network Modeling Framework and Solution Algorithms for Systems Analysis and Optimization of the Water-Energy Nexus

Abstract

Abstract:The water footprint of energy systems must be considered, as future water scarcity has been identified as a major concern. This work presents a general life cycle network modeling and optimization framework for energy-based products and processes using a functional unit of liters of water consumed in the processing pathway. We analyze and optimize the water-energy nexus over the objectives of water footprint minimization, maximization of economic output per liter of water consumed (economic efficiency of water), and maximization of energy output per liter of water consumed (energy efficiency of water). A mixed integer, multiobjective nonlinear fractional programming (MINLFP) model is formulated. A mixed integer linear programing (MILP)-based branch and refine algorithm that incorporates both the parametric algorithm and nonlinear programming (NLP) subproblems is developed to boost solving efficiency. A case study in bioenergy is presented, and the water footprint is considered from biomass cultivation to biofuel production, providing a novel perspective into the consumption of water throughout the value chain. The case study, optimized successively over the three aforementioned objectives, utilizes a variety of candidate biomass feedstocks to meet primary fuel products demand (ethanol, diesel, and gasoline). A minimum water footprint of 55.1 ML/year was found, economic efficiencies of water range from −$1.31/L to $0.76/L, and energy efficiencies of water ranged from 15.32 MJ/L to 27.98 MJ/L. These results show optimization provides avenues for process improvement, as reported values for the energy efficiency of bioethanol range from 0.62 MJ/L to 3.18 MJ/L. Furthermore, the proposed solution approach was shown to OPEN ACCESSProcesses 2015, 3 515 be an order of magnitude more efficient than directly solving the original MINLFP problem with general purpose solvers.

Integrated approaches to the optimisation of regional and local food–energy–water systems

“…In other work, water footprints have been incorporated either through objective functions (e.g. maximisation of economic or energy output per unit water consumption, [11]) or constraints (e.g. water supply limit, [12]; water stress, defined as the ratio of water withdrawal rate to water availability, [13]).…”

Unraveling Optimal Biomass Processing Routes from Bioconversion Product and Process Networks under Uncertainty: An Adaptive Robust Optimization Approach

“…Thus, considering the whole network does not impede solution of the problem. Much of the data collection strategy and some data corresponding to technologies for this network can be found in previous works. − A list of technologies used in this model as well as their inputs and outputs can be found in the SI.…”

Optimization of Water Grid at Macroscopic Level Analyzing Water–Energy–Food Nexus

“…Their results showed that future increments in energy demand would require the use of alternative energy sources. Garcia and You 25 proposed a life cycle optimization framework for energy-based processes, in which the methodology was based on the assessment of the water footprint for various energy-processing pathways. The results showed that the optimization in the bioconversion technologies is crucial to reduce the water consumption.…”