Multi-Objective Optimization Applied to Energy Efficient-Buildings

Multi-objective optimization applied to energy efficient-buildings.

ABSTRACT

E. Antipova^a , D. Boer^b, L. Cabeza^c, G. Guillén-Gosálbez^a, L. Jiménez^a

a. Department of Chemical Engineering, University Rovira i Virgili

b. Department of Mechanical Engineering, University Rovira i Virgili

c. Edifici CREA, Universitat de Lleida, Pere de Cabrera s/n, 25001-Lleida, Spain

The growth of population implies the growth in construction speed and housing cost. Affordable housing is one of the global problems in the world. Though the term “affordable” implies some compliance with the environmental regulations, the main target of the construction is to make the housing cheaper. However, cost reduction is not the unique criterion that should be taken into account when projecting a new building. Buildings are considered to be responsible for up to 50% of the total CO₂ emissions worldwide (if we consider both direct and indirect impacts). Hence, this is a sector with large potential for environmental improvements that demands adequate measures for mitigating global warming. The problem of energy efficient buildings is equally relevant for cold and hot climates. In the former, it is necessary to insulate the building properly to keep it warm in winter months, while in the latter, we need to cool it down in summer and to maintain a comfortable temperature in winters as the insulation of the buildings in these regions is usually poor because of the large-scale tendency to build low-cost housing.

When we talk about direct contribution of the construction to the environmental impact, we refer to the use of energy during operation of buildings (heating, cooling, ventilation, lightening and etc.), while indirect contribution accounts for the construction and maintenance of the buildings (embodied energy). It is important to make preliminary estimations to balance both constituents: operation and maintenance, as sometimes reduction in the operation impact causes the growth of the impact related to construction. This might happen, for instance, when we decrease the use of fossil fuels to heat the spaces by increasing the insulation of the building, thereby offsetting the savings in operation by the additional impact due to the production of isolating materials.

In this work we propose a systematic method for the retrofit of buildings considering economic and environmental aspects. The design is posed mathematically as a multiobjective mixed-integer nonlinear programming model (MINLP) that considers the simultaneous minimization of cost and environmental impact given a certain house to be retrofitted. Our model accounts for a set of retrofit measures to make a building more energy efficient, such as incorporation of alternative types of windows, variation of insulation of walls and roof, and employment of different types of solar collectors for hot water generation, among some others. The environmental performance is quantified following life cycle assessment (LCA) principles. A case study based on existing facilities of cubicles located in Lleida (Spain) is used to illustrate the capabilities of the approach. By applying the epsilon constraint method, a set of Pareto solutions representing the optimal trade-off between both conflicting objectives is generated. The systematic tool presented herein is intended to guide decision-makers towards the achievement of economic and environmental viability of the construction processes.