Decision-Support for Low-Temperature Renovations

Abstract

The current Dutch building sector is heavily dependent on natural gas for its energy consumption, of which a very significant part is used to meet the space heating demand. To mitigate the climate crisis, a transition from fossil fuels to renewable energies has to be made. However, renewable energy sources are usually low-temperature heating sources, prompting the need for renovation. There are often multiple renovation solutions per project, with each their unique effect. Determining the optimal solution out of those renovation concepts that enable low-temperature heating (LTH) is challenging due to the varying performance of the renovation scenarios, multi-stakeholder involvement with each their own preferences and the lack of a clear decision-making process.
This research aims to provide holistic decision-support and aid in the identification of the most suitable renovation alternative. The research question central to this study is: ‘How can the decision-making process of selecting an energy renovation concept be supported that aims to make existing residential buildings compatible with low-temperature heating?’. This research focuses on multi-family buildings in the Netherlands and considers a temperature range of 30-55 °C to be LT.
To answer the research question, an extensive literature research is conducted on the topics of LTH and decision-support in energy renovations. Based on the results from the literature study, a LTH decision-support framework and tool is developed. The MCDM TOPSIS method is used to evaluate the performance of the renovation alternatives and is combined with the pairwise comparison method to capture the stakeholders preferences. The framework and tool is validated on its function and usability through a case study application on a 1979 apartment building and a workshop with 4 expert stakeholders. In addition to the evaluation of the 4 renovation scenarios from the case study, 9 additional renovation scenarios are developed and compared. A LTH-Rhino/grasshopper tool is used to simulate the heating demand and thermal comfort for all 13 scenarios to evaluate the LT-readiness of the alternatives.
One of the key findings of this research is that the developed framework and tool can support the decision-making process on LT-renovation scenarios. This support is provided by structuring the decision-making process through aiding in the identification of decision parameters, making the stakeholders’ preferences explicit through pairwise comparison and ranking the renovation alternatives based on quantified performance values and criteria weights representing the stakeholders’ preferences through TOPSIS. The framework evaluates LT-readiness to identify if there is a need for renovation, and filters non-suitable scenarios based on the LTH-grasshopper simulation results.
The framework ensures that all relevant decision-making aspects are considered systematically, and the tool facilitates a transparent and data-driven selection process. Together, they provide holistic decision-support, leading to better-informed decisions. This research motivates to enable LTH, thereby mitigating climate change and ensuring a sustainable future.