A bottom-up spatially explicit methodology to estimate the space heating demand of the building stock at regional scale
| Autor: | Pietro Zambelli, Roberto Vaccaro, Rossano Albatici, Valentina D'Alonzo, Corrado Diamantini, Daniele Vettorato, Antonio Novelli |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
020209 energy 0211 other engineering and technologies Energy balance 02 engineering and technology Civil engineering Energy planning Spatial decision support system 021105 building & construction Space heating demand Building stock analysis 0202 electrical engineering electronic engineering information engineering Information system Electrical and Electronic Engineering Stock (geology) Civil and Structural Engineering business.industry Mechanical Engineering Building and Construction Top-down and bottom-up design Renewable energy Sustainable energy business |
| Zdroj: | Energy and Buildings. 206:109581 |
| ISSN: | 0378-7788 |
| Popis: | The paper presents a spatially explicit and “bottom-up” methodology for the building stock analysis of the residential sector. It integrates different input data in a Geographical Information System (GIS), without using the “archetypes approach” and simulation tools. In particular, the energy balance at the building level (BL) for the whole Valle d'Aosta region (Italy) is addressed, using the Italian Ministerial Decree 26/06/2009 and the UNI/TS 11300-1:2014 standard. Main outputs are the estimation of the geo-referenced heating demand of the residential buildings for the case study area (almost 42,000 buildings), and the development of a methodology that can be applied at different scales. The application of the methodology to the case study slightly overestimates the total thermal demand of the residential building stock, especially referring to the more energy demanding buildings. However, being the method influenced by data availability, the quality is expected to improve with newly available data. The proposed GIS-based methodology is designed to be part of a broader Spatial Decision Support System (SDSS) for sustainable energy plans that integrate renewable sources in the building stock energy renovation. |
| Databáze: | OpenAIRE |
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