A Procedure to Perform Multi-Objective Optimization for Sustainable Design of Buildings

Abstract

When dealing with sustainable design concepts in new construction or in retrofitting existing buildings, it is useful to define both economic and environmental performance indicators, in order to select the optimal technical solutions. In most of the cases, the definition of the optimal strategy is not trivial because it is necessary to solve a multi-objective problem with a high number of the variables subjected to nonlinear constraints. In this study, a powerful multi-objective optimization genetic algorithm, NSGAII (Non-dominated Sorting Genetic Algorithm-II), is used to derive the Pareto optimal solutions, which can illustrate the whole trade-off relationship between objectives. A method is then proposed, to introduce uncertainty evaluation in the optimization procedure. A new university building is taken as a case study to demonstrate how each step of the optimization process should be performed. The results achieved turn out to be reliable and show the suitableness of this procedure to define both economic and environmental performance indicators. Similar analysis on a set of buildings representatives of a specific region might be used to assist local/national administrations in the definition of appropriate legal limits that will permit a strategic optimized extension of renewable energy production. Finally, the proposed approach could be applied to similar optimization models for the optimal planning of sustainable buildings, in order to define the best solutions among non-optimal ones.

Sustainability and Optimization: From Conceptual Fundamentals to Applications

“…Moreover, China and India contribute approximately 29% and 7% of world CO2 emissions combustion in accordance with the statistics of IEA (CO₂ Emissions from Fuel Combustion, 2019) and are trying to decrease it. [81,87,91,107,110] and Italy [83,88,93,97,101]. The presence of advanced building technologies and skills in these countries and the 20% share of buildings in energy consumption as a significant contribution based on the IEA database have led these countries to have the most research and published articles on optimization of sustainable buildings.…”

A systematic review of genetic algorithm-based multi-objective optimisation for building retrofitting strategies towards energy efficiency

“…The most common set of environmental-social trade-offs, between energy consumption and thermal comfort, were explored in [71,127,[130][131][132]. While energy-related objectives represent the majority of the environmental sustainability scope, building emissions were also analysed in several PS and paired with thermal comfort in [109,110,[133][134][135]. On the other hand, the social sustainability scope gives place to a diversity of approaches that go beyond addressing thermal indoor comfort.…”

“…• As stand-alone form [10,11,12,23,25,76,89,108,110,112,113,115,[117][118][119]121,[124][125][126]128,129,[131][132][133][134]141,[143][144][145][146]151,152];…”

Building Thermo-Modernisation Solution Based on the Multi-Objective Optimisation Method

“…In [24], the Pareto front concept was applied and bi-objective optimisation was implemented by running the modified GA in order to identify low-emission cost-effective design solutions for a single-family dwelling in the cold climate of Helsinki, Finland. Moreover, Brunelli et al [25] employed the GA for achieving sustainable design by setting five objectives: minimisation of thermal energy demand, electric energy consumption, CO 2 -eq emissions, maximisation of investment net present value (NPV) and thermal comfort.…”