Integrating Design Optimisation and Economic Sustainability in Net-Zero Energy Buildings

Buildings account for a substantial share of global carbon emissions through their operational energy use, driving climate change and intensifying extreme weather events. Energy-efficient buildings can significantly reduce the environmental footprint of the built environment. However, realising this potential is hindered by fragmented design processes that optimise individual objectives in isolation. This approach overlooks critical trade-offs, such as between thermal performance and cost, or between energy saving measures (ESMs) and photovoltaic (PV) system performance, thereby failing to provide designers and stakeholders with a comprehensive assessment of feasibility. These shortcomings, compounded by uncertain financial projections over a building’s long service life, hinder the widespread adoption of ESMs. This underscores the urgent need for an integrated, holistic decision-support system capable of delivering quantified environmental and economic metrics to guide the design of resilient, sustainable and energy efficient buildings. This research aims to develop a practical, adaptable framework for optimising energy-efficient building design that balances thermal performance, long term resilience, cost-effectiveness, and contextual relevance. It integrates open-source optimisation tools with location-specific simulation software, employs multi-criteria decision-making (MCDM) for selecting ESMs suited to local climatic and economic conditions, incorporates future uncertainties into lifecycle cost analysis (LCCA), and evaluates the trade-off between passive design strategies and PV systems. Together, these approaches provide designers with accessible, data-driven methods to create sustainable, cost-effective and energy efficient buildings tailored to diverse environments. Optimising a building’s design to maximise thermal efficiency is inherently complex and often resource-intensive, particularly for practitioners who may lack the technical capacity to develop bespoke optimisation algorithms for individual projects. Hence, the first phase of the research proposes a comprehensive and practical framework that equips designers with quantified, decision-ready information during the design stages, thereby enabling the maximisation of a building’s energy-saving potential. The resulting solutions yielded reductions in thermal load of between 25.59% and 32.64% across a range of scenarios. Additionally, by decoupling the optimisation process from the energy rating assessment, the framework offers enhanced methodological flexibility and ensures applicability to a range of local regulatory contexts. Based on the framework in the first phase, the inherent trade-offs between energy efficiency and capital expenditure are recognised. In the second phase, the framework incorporates a LCCA accounting for future uncertainties in insulation performance, renewable energy adoption, and market conditions through the selection of optimal insulation materials via multi-criteria decision analysis, incorporating local climatic and economic parameters. Next, adjustments were applied using a Building Quality Index (BQI) value to capture the effect of construction quality on the building’s energy performance. Findings indicate that BQI-adjusted insulation specifications can provide an 11.6% performance buffer without incurring significant additional costs. Furthermore, a financial modelling component was developed to examine the influence of increased renewable energy penetration on electricity pricing. The analysis revealed that aggressive renewable adoption, while environmentally beneficial, could lead to lower energy prices and thereby reduce the financial incentive for investment in capital-intensive energy-saving measures. The third phase attempts to explore the framework’s applicability with the addition of a renewable energy system. Results from the sensitivity analysis confirmed that rooftops consistently receive the highest solar insolation across all orientations and climates, whereas facade performance varied considerably depending on location-specific conditions. Comparative analyses of building energy supply and demand demonstrated that, in favourable climates, contemporary PV-battery storage technologies can meet the operational energy demands in medium-density settings. However, LCCA showed that building-integrated PV (BIPV) systems offer minimal economic advantage under current market conditions. Overall, this extended framework delivers a replicable, location-sensitive, and future-resilient approach for the design of thermally efficient and economically viable Net-zero energy buildings (NZEBs), thereby supporting the advancement of net-zero energy design strategies within sustainable urban development. Overall, this thesis delivers a practical contribution to the residential building design through a holistic, user-friendly framework that integrates energy minimisation, renewable energy generation, cost–benefit analysis, and the consideration of future uncertainties. This comprehensive system overcomes the limitations of fragmented building design methodologies by providing a user-centric, adaptable solution that is both contextually accurate and computationally accessible. Additionally, the framework equips designers with a comprehensive, resilient approach to achieve environmentally and economically sustainable buildings that remain robust against future perturbations. Using this framework as a foundation, future research in integrated energy-efficient building optimisation can be conducted.