Stock Aggregation Model and Virtual Archetype for Large Scale Retro-fit Modelling of Local Authority Housing in Ireland

Abstract

Developing representative archetypes using a bottom up approach for stock modelling is an excellent tool for evaluating the overall performance of the building stock; however it requires detailed analysis of the various building types. Currently there is no detailed housing data base for Local Authority housing in Cork City, Ireland that catalogues the housing stocks geometric properties and thermal characteristics for each typology. This study details a methodology to catalogue the LAH stock and build a detailed housing data base. The GIS web based mapping application Google Street View is used to identify 20 house typologies across 36 LAH developments; a total of 10,449 housing units are counted and information subdivided into end of terrace, mid terrace, semi-detached, orientation and elevation. The data base provides the base line assessment for building a stock aggregation model; the stock aggregation approach is used as a method to evaluate the energy performance of the building stock, beginning with analysis of individual house types; referred to as a ‘bottom up approach’.4 representative archetypes are produced and modelled using DEAP simulation software. A 6% variation is recorded when compared to an averaged 121 registered BER results from LAH in Cork City. A full estimation of total energy use and CO2 is recorded for 10,449 units resulting in 211 GWh/y and 35,477 GtCO2/y. Investment in retro-fit is highly justified in this area with large potential for reducing CO2 emissions, the number of fuel poverty sufferers and victims of seasonal mortality due to thermally inefficient homes. The study suggests the method applied has scalable potential and is modular in structure facilitating wider adaption.