Integrating energy and water optimization in buildings using multi-objective mixed-integer linear programming

Abstract

Energy and water are humans’ most significant needs, and many countries confront numerous problems in supplying water and energy resources. Some approaches to rendering these resources increase the emission of greenhouse gases. Concerning the high water and energy consumption in buildings and high energy and water loss and CO2 emission in the concentrated energy generation and water treatment, a presentation of an unconcentrated combined system considering water and energy use optimization and emission reduction in greenhouse gases is needed. While previous studies employed renewable technologies to optimize water and energy consumption separately, this study integratively used the renewable energy generation, energy storage, building smartening, zero energy building standards, and ground source heat pump technologies to decrease energy consumption and CO2 emission. It also exploited the rainwater harvesting and greywater recycling composition to decrease water consumption. Using MILP, we presented a mathematical model to examine the economic conditions besides reductions in energy and water use and CO2 emission, and we solved it by the epsilon constraint method and GAMS software. The results in 4 scenarios revealed that energy use, water use, and CO2 emission decreased by 47–94.7 %, 20–100 %, and 52–96 %. Besides, the model economically experienced reduced costs and yielded monetization possibility.