Estimating domestic demand patterns for hydrogen-based heating technologies using temporal disaggregation

This study addresses the challenge of estimating demand profiles for low-carbon heating technologies such as hydrogen boilers, in the absence of high-resolution smart meter data. It introduces a methodology for disaggregating low-resolution gas consumption data using high-temporal-resolution temperature data to generate demand profiles for hydrogen boiler technologies for a specific region. This approach overcomes the limitations of existing methods of estimation which primarily rely on smar t meter data. The methodology is applied to a real-world case study to determine the seasonal demand profile. Additionally, the study estimates the environmental impact of transitioning from natural gas boilers to hydrogen boilers for domestic heating by comparing the carbon footprint for natural gas, grey hydrogen, blue hydrogen and green hydrogen. Results reveal that green hydrogen produced from electrolysis has the least carbon footprint. This comprehensive approach not o nly facilitates hydrogen supply chain optimisation, but also informs infrastructure planning for the decarbonisation of heat in the UK, aligning with the nation's goal of achieving net-zero emissions by 2050.