Optimal pathway towards building EPC rating improvements align with building energy performance certificate programme

This dissertation investigates an optimal pathway for commercial buildings to improve their Energy Performance Certificate (EPC) ratings by efficiently adopting Energy Efficiency Measures (EEMs). With buildings contributing approximately 40\% of global energy consumption and 36\% of carbon dioxide emissions, enhancing energy performance is critical. EPCs have been introduced globally to assess and promote energy efficiency in buildings. However, the uptake of EPCs and adherence to the recommended EEMs have been limited, especially in countries like South Africa and Scotland. In South Africa, only 1\% of the commercial buildings requiring EPCs have obtained them, and many building owners are hesitant to implement the recommended measures due to lack of trust, financial, and time constraints. This research addresses these challenges by proposing a model that optimises the selection and implementation of EEMs to achieve higher EPC ratings cost-effectively. The optimisation model, developed using MATLAB’s Genetic Algorithm (GA) solver, minimises the investment required while improving the energy performance of buildings step-by-step. The model considers key EEMs such as lighting system upgrades, HVAC improvements, and the integration of renewable energy sources like solar panels and battery storage. The approach allows building owners to make gradual improvements, balancing cost and time, leading to higher EPC ratings over time. To validate the proposed pathway, the study applied the model to a case study of a commercial building in Pretoria, South Africa. The results revealed that by adopting the optimal sequence of EEMs, the building could achieve significant energy savings while progressing through the EPC rating scales. The model demonstrated that a step-by-step approach can reduce the upfront financial burden compared to an aggressive all-at-once strategy. The study also makes recommendations for policymakers to refine EPC standards and support measures that incentivise building owners to participate in energy saving projects.

Grantor dc:publisher

University of Pretoria

Year dc:date.issued

2024

Advisor dc:contributor.advisor

• Ye, Xianming

• UCTD
• Sustainable Development Goals (SDGs)
• Mixed integer non linear programming
• Energy performance certificate
• MATLAB
• Renewable energy sources
• Retrofitting
• Pathway
• Energy efficiency measures

Statement dc:rights

• © 2023 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.

Language dc:language.iso

en

DOI

10.25403/UPresearchdata.28052789

Dc Identifier Other

A2025

OAI identifier oai:identifier

oai:repository.up.ac.za:2263/100071