Journal
RENEWABLE ENERGY
Volume 173, Issue -, Pages 544-560Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.03.144
Keywords
Urban building energy modelling; Lumped-capacitance thermal networks; Semantic georeferenced data; EUReCA; District simulation
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This article introduces a new open-source tool that uses electrical analogy to simulate energy demand in buildings and cities with low computational resources. The results show that simplified models are consistent with detailed simulations of single buildings in predicting urban energy demand, and accuracy can be improved by splitting building surfaces into two capacitors.
Recently, the attention towards Urban Building Energy Modelling has been growing due to the large contribution of cities on the worldwide energy consumption rate. In fact, many models have been developed to simulate buildings and urban energy systems. This article presents a new open-source tool for city-scale simulations. The platform implements the electrical analogy to model buildings thermal behaviour through resistance-capacitance networks, thus predicting the energy demand of urban areas with a bottom-up approach and low computational re-sources. The model has been applied to two urban areas: a small and well-known neighbourhood and a broader urban district. Results show the accordance of simplified models with respect to single building detailed simulations in the evaluation of the seasonal energy demand. When comparing results at hourly resolution, the accuracy is increased by considering a thermal network that splits buildings' surfaces into two capaci-tances. A model based on a single capacitance leads to a higher deviation, especially on the daily peak power. Regarding the district simulation, these simplified networks show a good prediction of the buildings energy demand according to relevant European references, thus demonstrating the reliability of the proposed approach despite their low computational effort. (c) 2021 Elsevier Ltd. All rights reserved.
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