Towards demand flexibility in buildings and improving indoor air quality

Developing an environmental justice focused approach to improving indoor air quality

Dr Douglas Booker

How patterns of air pollution vary across an array of social characteristics has been of longstanding interest for the environmental justice (EJ) movement. This has largely been in terms of outdoor air quality, while indoor air quality (IAQ) remains both under theorised and studied. This presentation will draw on an AHRC/EPSRC Impact Acceleration Account project with Lancaster University. In the project we are outlining a framework to develop an EJ focused approach to improving IAQ, including how IAQ policy, practice, and research can contribute to achieving EJ. In doing so, we take an understanding of EJ beyond simply who is exposed more/less to poor IAQ, to also focus on the processes through which unequal distributions of poor IAQ are created and sustained.

Leveraging semantic models for scalable demand flexibility applications in buildings

Flavia de Andrade Pereira

The transition towards decarbonisation requires a tenfold increase in Demand Flexibility (DF) by 2030 compared to 2020 levels, with around 50% coming from buildings. DF involves actively managing loads to support grid demands, particularly during high demand, low supply, or renewable curtailment risks. Despite its significance, the widespread adoption of DF applications in buildings remains limited. This is partly because the heterogeneous nature of the building stock often requires bespoke solutions, leading to a lack of interoperability and portability. Deploying new applications across different buildings entails resource-intensive onboarding processes. In this webinar, we will explore the use of semantic models to address these challenges and enhance the scalability of DF applications. We will discuss how these models describe the meaning of data, facilitate its exchange among diverse sources, and enable applications to be portable across various buildings. We will also address the benefits, limitations, and challenges associated with semantics-driven approaches.