Abstract
The optimization of energy, environmental and economic (3E) outcomes is the principal approach to identifying retrofit solutions for a sustainable built environment. By applying this approach and defining a set energy performance target, this study proposes a makeshift decision framework that integrates a data mining procedure (agglomerative hierarchical clustering (AHC)) into the decision-making process to provide a simplified 3E assessment of building retrofits on a macro-scale. The framework comprises of three model layers: (1) a building stock aggregation model, (2) an individualistic 3E model that provides the sensitivity analysis for (3) a life cycle cost-environmental assessment model. The framework is demonstrated and validated with a case study aimed at achieving the set energy targets for low-rise office buildings (LOB) in Shanghai. The model defines 4 prototypical buildings for the existing LOB blocks, which are used for the individual evaluation of 12 commonly applied retrofit measures. Subsequently, a simplified LCC-environmental assessment was performed to evaluate the 3E prospects of 2048 possible retrofit combinations. The results uniquely identify retrofit solutions to attain the set energy performance targets and optimal building performance. Furthermore, the decision criteria for different investment scenarios are discussed. Overall, this study provides building investors an innovative framework for a facile and holistic assessment of a broader range of retrofit alternatives based on set performance targets.
Highlights
The study describes the proposed prototypical low-rise office buildings (LOB) used in this present study
The construction year, window-wall (W/W) ratio and the number of floors are identified as the key performance indexes (KPIs) of LOB in Shanghai, which are used to classify LOB into four prototypes based on the Chinese building codes and standards
The approach provides a methodological contribution that enables decision-makers to select the most reasonable retrofit solution by defining rational decision criteria based on the set performance targets
Summary
Utilizing building retrofits has emerged as the primary concept for achieving a sustainably conscious society [1]. Recent studies have demonstrated that a multi-objective optimisation approach is more suited to establish an optimal retrofit solution [8]. In this approach, the universal concept of optimising the energy, environmental and economic (3E) variables is emphasised to promote the interpretability, applicability and comparability between outcomes [1, 9, 10]. The jointly considered decision variables in this field are electricity consumption, CO2 emission and cost indicators (investment, energy, life-cycle or payback period (PBP)) The optimization of these variables are defined by a set of objective functions, which commonly involve minimising the life-cycle costs (LCC) [6, 13]; maximising energy conservation (energy reduction impact), renewable sources adaptability and conservation compatibility [6, 7, 14]; and minimising CO2 and in some cases, other greenhouse gas (GHG) emissions [3, 5]. The model should proffer decisions based on investors’ priority and set performance targets within that city/area
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