Data-driven Analysis of Building Energy Performance Using Boverket Energy Declarations and real-time data

Objective/short description

This master thesis aims to analyze the energy performance of multiple BRF (Bostadsrättsförening, or housing cooperative) buildings by utilizing the energy declarations according to Swedish Boverket standards and data collected from the Digital Control Room developed within the DigiCityClimate project. The study will focus on mapping faulty systems, identifying performance degradation, evaluating CO2 footprints, and elaborating a data-driven assessment of building energy declarations.

Background

Buildings in Sweden are required to elaborate energy declarations in compliance with Boverket standards. However, this information is not fully utilized to optimize building energy performance. With the increasing importance of sustainability and energy efficiency, it becomes crucial to assess building systems for performance degradation and environmental impact.

Within the DigiCityClimate project , a Digital Control Room is under development as a web tool to provide added value to data collected from multiple buildings (i.e., BRFs), including energy consumption and system performance data. This master thesis will build on the Digital Control Room web tool to map faulty systems, evaluate CO2 emissions, compare the energy performance of different BRFs, and elaborate a data-driven assessment of building energy declarations. This project will also involve collaboration with industry partners like Bengt Dahlgren to ensure the applicability of findings to real-world cases.

Task description

The master thesis will involve the following tasks:

Utilizing the Boverket API to gather energy declaration data from BRF buildings.

Leveraging the DigiCityClimate project’s Digital Control Room web tool to collect data on energy consumption and system performance.

Mapping faulty systems and detecting performance degradation across the buildings.

Analyzing and comparing the CO2 footprint of different buildings using energy consumption data.

Developing a data-driven methodology for evaluating the energy declaration of the buildings and suggesting improvements.

Collaborating with Bengt Dahlgren and other partners to ensure the alignment of research with practical industry needs.

Learning outcomes

The student will achieve the following learning outcomes upon completion of this thesis:

Proficiency in analyzing and interpreting large datasets related to building energy performance.

Experience working with the Boverket energy declarations and Swedish energy efficiency standards.

Use of data-driven tools to detect performance degradation and faulty systems in buildings.

Understanding of how to calculate and compare the CO2 footprints of different buildings.

Experience in the design and improvement of digital tools for monitoring and managing building systems.

Prerequisites

Basic knowledge of data analysis and energy systems.

Familiarity with energy performance standards is preferred but not required.

Experience with programming and API usage is an advantage.

Swedish language skills are not mandatory but would be a plus.

Research Area

Sustainable Energy Systems / Building Energy Performance / Data Analysis

Duration

The thesis work is expected to take place over a five-month period. Intermediate progress will be reported at regular intervals.

How to apply

Interested candidates should submit their CV and academic transcript to the supervisor listed below. Applications will be reviewed on a rolling basis until a suitable candidate is found.