A Monte-Carlo assessment of the effects of long-term changes on residential energy supply systems

Abstract

Space heating accounts for approximately one third of the global final energy consumption in both the residential and the commercial building sub-sectors. Including hot water, the 2010 IPCC report on buildings attributes 53% of the total final energy demand of the worldwide building sector to the demand for low temperature heat. At the same time, according to the IEA, the share of renewable energy supply in 2019 only met 11% of the global heat demand, leading to a domination of fossil fuels in this sector, contributing 40% (13.3 Gt) of global CO2 emissions. While these facts underline the need for fast changes, in particular integrating the sectors of heat and electricity, decisions should also include long foresight: Once installed, such systems typically operate for decades. This contribution presents a risk analyses of long-term changes on the national scale on different energy supply systems at the district scale. For example, the effect on changing capacity of renewable electricity generation on the CO2 emissions caused by the residential energy demand is assessed. To evaluate the uncertain characteristic of the future, a probabilistic scenario space is spanned instead of working with distinct scenarios. This space is then sampled using the Monto Carlo method, resulting in probability density functions for previously defined key performance indicators.