Abstract
As regulations regarding energy use and emissions of CO2 equivalents in buildings become more stringent, the need for more accurate tools and improved methods for predicting these parameters in building performance simulations increases. In the first part of this project, a probabilistic method was developed and applied to the transient energy calculations and evaluated using a single-family dwelling case study. The method was used to successfully predict the variation of the energy use in 26 houses built in the same residential area and with identical building characteristics and services. This project continues the development and testing of the probabilistic method for energy calculations by applying it to a multi-family building. The complexity of the building model increases as the multi-family model consists of 52 zones, compared to the single-zone model used for the single-family dwelling. The multi-family model also includes additional parameters that are evaluated, such as the domestic hot water circulation losses. This paper presents the probabilistic method applied to the building performance simulations used to predict the energy use for the multi-family building and discusses the differences between the previous and new method used in this study.
Highlights
1.1 Summary of phase one of this projectIn phase one of this project, a method of doing probabilistic energy calculations was developed, hereafter called “the method” using a single-family house by applying Monte Carlo methods on input data with different probability distributions
The energy use for space heating, Domestic Hot Water (DHW), and electricity for building services, hereafter known as “results” were compiled and presented as a histogram and compared with the measured energy use values for 26 houses built in the same geographical area near Gothenburg, Sweden
The results from phase 1 showed that the method gave energy use distributions which were very similar to the actual measured energy use in the 26 houses. [2, 3]
Summary
In phase one of this project, a method of doing probabilistic energy calculations was developed, hereafter called “the method” using a single-family house (one zone) by applying Monte Carlo methods on input data with different probability distributions. Rezaee et al [4] have described several methods related to probabilistic energy calculations, the method that most describes what was done in phase 1, and what will be done in phase 2, is called “probabilistic forward modelling” This is done in practice by defining the distributions of different parameters, running the different cases and scenarios using an energy model and compile the results using a statistical tool to produce a histogram. Their proposed method using “probabilistic inverse modelling” [4] can be applied to the tools being developed in this project in future work by linking the energy calculation results to the individual input parameters. The input data in the final energy calculation are never fixed and are distributions based on variations found in specific materials, products, and methods instead of distributions used when the materials, solutions or methods are unknown
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