The Development of an Economic Feasibility Decision Support System for a Building Automation and Control System

The global transition toward sustainable energy practices has amplified the role of Building Automation and Control Systems (BACS) as a means of reducing building energy consumption, improving operational efficiency, and enhancing occupant comfort. Despite these advantages, the integration of BACS in developing regions such as Africa, remains limited. To address this gap, this study develops the BACS Feasibility Assessment Decision Support System (BFA DSS)—a proof-of-concept model class DSS tool, designed to estimate the financial and energy feasibility of BACS installations within the South African environment for lecture halls and office block buildings. The research thereby contributes to a wider investigation surrounding the impact of BACS in South Africa and a practical application to assist decision-makers during the conceptual phase of building automation investments. The study adopts a three-phase mixed-methods research design. Phase 1 establishes the theoretical foundation, utilising a literature review and state-of-the-art review on BACS technologies, assessment frameworks, and Decision Support Systems (DSS). The review reveals that the existing studies and evaluation frameworks are predominantly European in origin and scope, offering little adaptability to regional conditions such as South Africa’s tariff structures, climatic factors, and regulatory environments. Phase 2, focuses on the requirement specification, concept design, and detailed development of the BFA DSS, integrating both energy modelling and financial estimation modelling. The BFA DSS estimates the performance of five core building energy fields—heating, cooling, ventilation, lighting, and internal parasitic loads—while coupling these with financial indicators such as Net Present Value and Payback Period. Phase 3 involves the verification and validation, comprising requirement traceability, static code analysis, boundary testing, and an applied case study supported by expert evaluation. Verification results confirmed that the DSS performs in accordance with its functional and design requirements, with robust computational reliability across varied boundary inputs. The validation phase, using a university lecture hall building as the case study environment, demonstrated strong correlation between the DSS outputs and the measured post-installation energy data. Energy prediction accuracy across the individual energy fields exceeded 90% alignment in most instances, with financial projections falling within an acceptable deviation range for feasibility analysis. Notably however, the accuracy of the estimates varied across the energy fields with some fields performing significantly better than others. Expert validation (achieved through a questionnaire of 5 subject matter experts) further confirmed the BFA DSS’s usability and contextual relevance, noting its potential to support early-stage decision-making where uncertainty traditionally impedes investment confidence. However, the study also acknowledges certain shortfalls, including the DSSs current limitation to only lecture halls and office block environments, reliance on pre-existing frameworks not specifically developed for South Africa, and the need for more extensive testing. These constraints present clear opportunities for further development, including the continued development of the BFA DSS and frameworks in the South African landscape. Consequently, the study contributes value in two primary ways. Firstly, it advances the academic understanding of BACS feasibility within a developing country context. Secondly, it delivers an expert validated proof-of-concept DSS capable of quantifying both energy performance improvements and economic returns associated with BACS installations.

Grantor dc:publisher

Stellenbosch : Stellenbosch University

Year dc:date.issued

2026

Author dc:creator

• Nash, Sheldon Peter

Advisors dc:contributor.advisor

• Jooste, J. I.
• De Kock, I. H.
• Bitsch, G.

Language dc:language.iso

en

Repository record dc:identifier.uri

https://scholar.sun.ac.za/handle/10019.1/136117

OAI identifier oai:identifier

oai:scholar.sun.ac.za:10019.1/136117