| dc.description.abstract | Buildings account for approximately 40% of annual energy consumption and 16% of annual water withdrawals globally over their life cycle. Moreover, most building designs consider only the operational energy use of buildings during their life cycle, disregarding the contribution of embodied energy and embodied water to total energy and water consumption. Studies have indicated that minimizing operational energy may increase embodied energy. Likewise, minimizing energy use may not always mean reducing embodied water use. The most effective approach to determine the trade-offs among building design and construction decisions related to building energy and water parameters is to apply multi-objective optimization. In order to quantify the trade-offs between water and energy, this research created a multi-objective optimization model using building information modeling data to simulate energy and water use.
This study created and tested a multi-objective genetic algorithm to examine energy-water trade-offs by computing water consumption, operational energy, and embodied energy of buildings. We tested the tool by conducting a case study of a higher-education building. We applied and compared single-, double-, and triple-objective optimization approaches. First, a triple-objective optimization method was applied to target operational energy, embodied energy, and embodied water as the objective functions. Second, a double-objective optimization was applied excluding embodied water to analyze operational-embodied energy trade-offs. Third, a single-objective embodied water optimization approach was applied to target embodied water individually. We investigated the design variables contributing to total energy and embodied water consumption and the relationship between energy and water. In addition, we examined the building’s envelope material quantity and window-to-wall ratio as optimization variables. Results from the multi-objective optimizations suggest that excluding embodied water can produce a set of Pareto solutions that is quite different than when including it. In the double-objective optimization between embodied energy and operational energy, minimizing operational energy increased embodied energy and, consequently, total energy use. Embodied water and energy did not show such a relationship, though. However, in comparing window-to-wall ratios, similar connections were seen between water and energy. Optimal energy solutions had low window-to-wall ratios, while the single-objective embodied water results had significantly higher window-to-wall ratios. Average embodied water values from the triple-objective optimization, double-objective optimization, and single-objective optimization were 338,948, 59,364.3, and 24,600.7 MGal, respectively. Even though single-objective optimization showed the lowest embodied water, the corresponding embodied energy and operational energy were relatively high (8,494,700 and 13,327,000 MJ, respectively). Results clearly suggest that focusing on just one energy or water component during building design may generate solutions that worsen other components. | |
