Abstract
This paper presents a framework for the development of early-design guidance to inform architects and policy-makers using parametric whole-building energy simulation. It includes a case study of a prototype multifamily residential building, using an exhaustive search method and a total of 90,000+ simulations. The authors performed a simple sensitivity analysis to identify the most influential of the tested design parameters on energy use intensity, which included WWR, Glass Type, Building Rotation, Building Shape, and Wall Insulation, in that order. They identified synergies and trade-offs when designing for different energy objectives, including (a) decreasing Energy Use Intensity, (b) reducing peak-loads, and (c) increasing passive survivability – i.e., maintaining the safest interior temperatures in an extended power outage.This paper also investigated the effect of urban context as a source of sun shading and found it to have a substantial impact on the design optimization. Ignoring urban context in energy simulation, a common practice, would mislead designers in some cases and result in sub-optimal design decisions. Since in generalized guidelines the future building site is unknown, the authors tested a method for generating urban contexts based on the floor area ratio and maximum building heights of an urban district.
Highlights
The United Nations expects the world's urban population to nearly double by 2050, increasing from 3.3 billion in 2007 to 6.4 billion in 2050, with much of this growth occurring in developing megacities [1]
This paper investigated the effect of urban context as a source of sun shading and found it to have a substantial impact on the design optimization
The most influential and costeffective decisions occur earliest in the project's life [4], and experts suggest that building energy simulation is most effective early in the design process [5, 6, 7]
Summary
The United Nations expects the world's urban population to nearly double by 2050, increasing from 3.3 billion in 2007 to 6.4 billion in 2050, with much of this growth occurring in developing megacities [1]. The authors performed a case study of a prototype residential high-rise building They implemented a sensitivity analysis to identify the most influential of several early-stage design parameters -including building form, window-to-wall ratio, window shading, and others --considering a range of design options for each parameter. Some techniques perturb only one parameter at a time keeping other inputs constant [16] or use sampling techniques [14, 15, 17], such as Monte Carlo methods, to perturb multiple inputs while simulating only a portion of the total possible design combinations These methods prove especially valuable when computing power is limited or the set of possible combinations is very large. For this early-design investigation the authors prioritized a conceptually simple sensitivity analysis, made possible by the exhaustive search approach. The authors propose using stochastic urban context models based on neighborhood-level density and building height restrictions
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