A methodology for performance robustness assessment of low-energy buildings using scenario analysis

Abstract

• A novel methodology for performance robustness assessment is proposed.• Multi-criteria assessment is carried out using predicted performance and robustness.• The minimax regret method is used to identify robust designs.• A multi-criteria decision making strategy is implemented to select robust designs. A R T I C L E I N F O Keywords:Robust design Low-energy buildings Future scenarios Occupant behavior Performance assessment Robustness assessment Design decision making A B S T R A C T Uncertainties in building operation and external factors such as occupant behavior, climate change, policy changes etc. impact building performance, resulting in possible performance deviation during operation compared to the predicted performance in the design phase. Multiple low-energy building configurations can lead to similar optimal performance under deterministic conditions, but can have different magnitudes of performance deviation under these uncertainties. Low-energy buildings must be robust so that these uncertainties do not result in significant variations in energy use, cost and comfort. However, these uncertainties are rarely considered in the design of low-energy buildings and hence, the decision making process may result in designs that are sensitive to uncertainties and might not perform as intended. Therefore, to reduce this sensitivity, performance robustness assessment of low-energy buildings considering uncertainties should be assessed in the design phase. The probability of occurrences of these uncertainties are usually unknown and hence, scenarios are essential to assess the performance robustness of buildings. Therefore, a non-probabilistic robustness assessment methodology, based on scenario analysis, is developed to identify robust designs. Maximum performance regret calculated using the minimax regret method is used as the measure of performance robustness. In this approach, the preferred robust design is based on optimal performance and performance robustness.The proposed methodology is demonstrated using a case study with a policymaker as the decision maker. The proposed methodology can be used by designers and consultants to aid decision makers in the design phase to identify robust low-energy building designs that deliver preferred performance in the future operation.

Validation of the climatic zoning defined by ASHRAE standard 169-2013

“…This could be achieved by the adoption of future scenarios considering projected weather files (Drury B. Crawley, 2008;Taylor et al, 2014) and robust designs buildings alternatives (Kotireddy et al, 2018). These considerations may contribute to avoid the adoption of obsolete energy efficiency policies, which is a common challenge in many countries nowadays (Jenkins et al, 2013;Visscher et al, 2016).…”

Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings

“…In this case, the original building design configuration was considered as a baseline. Then parametric simulations were run using the Design of Experiments (DOE) methodology [58], similarly to other research studies on the variability in building performance simulation [15,16,59]. Variations and multiple runs are meant to reproduce the actual variability of the performance of envelope components, air-change rates and of occupants' behaviour and comfort preferences.…”

“…), as specified in detail in Section 3.1. The parametric approach aims at detecting critical assumptions in the preliminary design stage, to guarantee a more robust evaluation of performance [15,23]. In simpler terms, the objective of the parametric simulation is to include from the very beginning more realistic, and possibly less optimistic, assumptions, and use the simulation outcomes as boundaries for comparative performance analysis during the operation phase.…”

Integrating robustness indicators into multi-objective optimization to find robust optimal low-energy building designs

“…The probability of occurrence of many influential factors (like occupant behaviour) is largely unknown over a building's life-span, and as such it is difficult for designers to quantify their impact. For those influential factors it is possible to use scenario analysis in order to understand the impact of their uncertainty (Kotireddy, Hoes, and Hensen 2018). In scenario analysis, alternative futures for the influential factors are formulated, which can be used to identify designs that perform well (robust performing) in these formulated futures (Moss et al 2010).…”

“…As such, integration of scenario analysis into performance robustness assessment allows for a thorough investigation of uncertainties (Kim 2013;Struck and Hensen 2013). Accordingly, a non-probabilistic robustness assessment based on scenario analysis is used to identify robust designs (Hoes et al 2011;Rysanek and Choudhary 2013;Kotireddy, Hoes, and Hensen 2018). The max-min method and the minimax regret method are widely used for robustness assessment using scenario analysis (Averbakh 2000;Aissi, Bazgan, and Vanderpooten 2009).…”