(220a) 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.