Affordable housing and the cost-of-living crises are challenges that require diverse interventions across different domains of city planning and management. Yet effective mitigation of the structural roots of the crisis, such as increasing housing and energy costs, often exceed the capacities of local governments. As the city of Thessaloniki frames their challenge, 25% of the city’s housing stock remains uninhabited, primarily due to overwhelming operational costs intensified by widespread energy poverty. A similar issue is evident in Tallinn, albeit in the context of public assets, where buildings’ heating loads and resultant costs render many otherwise functional assets unusable. This is particularly pressing for heritage buildings that pose additional challenges, related to interventions’ restrictions for habitation, maintenance and energy efficiency. As a result, the disuse of heritage assets strips the city of potentially usable residential and civic spaces, alongside the decay of valuable architectural heritage and loss of collective memory. Our solution fuses smart energy optimisation with architectural conservation and citizen engagement, to minimise operational costs and maximise the potential of public assets. By mitigating the availability of spaces and energy poverty, the capacities of diverse urban stakeholders can be enhanced and catalysed by local heritage to reinvigorate how we approach urban resilience and sustainable living.
Our proposal synthesises smart modelling capabilities with community-driven organisational innovations to improve energy performance of heritage-protected buildings. On the tech side, we aim to deploy Artificial Intelligence (AI) in building automation systems integrated with digital twin energy models, by modelling weather, consumption, and user load forecasts to proactively operate the building. Such systems have achieved large absolute energy savings in some of the least insulated and most inefficient buildings, like heritage assets, where physical insulation is usually prohibited. The model can match a building’s peak heating loads to the cheapest energy source of variable supply to optimise the cost of energy consumption. Especially with renewables, where production and relevant costs fluctuate significantly. Smart energy systems are only part of the solution for fluctuating energy supply. More important are the changes in consumption patterns from the demand side, and the flexibility of how and when energy is used. Demand-side flexibility (DSF) is crucial but often overlooked in optimisation. Further, DSF is not always equally distributed, creating pressures on the least privileged. Moreover, all smart systems have substantial societal and ecological impact, especially when applied at scale, while concerns are raised concerning the control and governance of smart energy data. These lead to lack of trust and resistance to the energy transition, hindering the impact of energy efficiency and optimisation technologies. We aim to include user
communities in the deployment of the proposed smart energy solution to coordinate DSF through collective action. Heritage sites are fertile ground for connecting to embodied practices of the past and revitalising more resilient forms of working and living. The proposed pilot harnesses smart energy modelling and forecast as a means of empowering citizens to better anticipate community needs and self-organise.
