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Energy modelling of existing residential buildings and optimization of retrofitting strategies

Javier Casco Company
Göteborg : Chalmers tekniska högskola, 2018.
[Examensarbete på avancerad nivå]

project aims to create a simple yet accurate tool that can be used to: 1. Calculate the space heating demand , and, 2. Identify the optimal retrofitting scenario of an existing residential building in a time-efficient manner. Climate change is one of the main challenges to overcome nowadays. Energy consumption in buildings, especially in dwellings, makes a significant contribution to this problem, emitting a considerable amount of greenhouse effect gases. One way with a high potential to reduce these emissions is making already existing buildings more energy efficient by retrofitting them. However, money is a substantial limitation to implementing retrofitting strategies, as renovation projects are costly. Therefore, cost-efficient retrofit measures should be found. In this context, several studies are proposing different ways of achieving an optimal retrofitting strategy. Some of them are based in databases of measures that are combined optimallyy. Others more studies use more accurate methods for simulating the energy usage when different retrofit measures are involved, but rely on very time-consuming optimization strategies such as the genetic algorithm. This Master Thesis aims to find a time-efficient tool that is able to simulate specific buildings and takes into consideration the effect of retrofitting different parts of the building envelope accurately, not relying on databases, but on actual simulations. The energy modelling will be based on ISO 52016:1-2017 and developed in Matlab. The model will be validated with well-known commercial software. Using the capabilities of Matlab and considering the original goal regarding time-efficiency, non-linear optimization will be performed. This optimization strategy presents some limitations regarding the data input since cost functions are created from available commercial data, and the search for a local minimum, instead of using time-consuming global optimization tools. After the energy model validation has been carried out and the optimization strategy selected, a case study based on a real building will be analyzed. From the case study, it can be observed that the tool gives coherent results in a reduced time.

Nyckelord: energy, space heating, existing buildings, residential buildings, retrofitting, renovation, optimization.

Publikationen registrerades 2018-10-01. Den ändrades senast 2018-10-02

CPL ID: 256050

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