Ph.D. thesis on on optimization of building retrofit in an integrated energy system based on RE, with the title: Urban-scale building energy modelling for stochastic retrofit analysis (Framework for analysing the impact of energy-retrofit of homes on district scale energy supply).
A scalable archetype-based urban building energy modeling platform is proposed for simulating the hourly dynamic heating energy use of residential buildings in a district heating network. The framework employs a novel data-driven calibration methodology to infer uncertain technical building parameters that are shared by similar archetype-buildings. This enables forecasts of energy use time series of unseen buildings using only publicly available building characteristics supplemented by archetype-calibrated parameters as inputs for the simulations. On a spatially aggregated urban level of neighborhoods or city districts, these predictions shows to be very accurate. The modeling platform is especially applicable for estimating the current and future heat demand of buildings in existing district heating systems. Other applications include 1) analysis of the effect of retrofitting the existing building stock on the dynamic heat load and thus DH operation, 2) forecasting the dynamic heat load of new buildings, and 3) analysis of the flexibility potential of buildings in DH networks.
Want to know more?
Please contact: Mrs. Kirsten Dyhr-Mikkelsen, Aarhus Municipality, firstname.lastname@example.org