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Predicting the urban solar fraction: a methodology for energy advisers and planners based on GIS
journal contribution
posted on 2013-06-07, 12:41 authored by Stuart J. Gadsden, Mark Rylatt, Kevin LomasKevin Lomas, Darren RobinsonThis paper describes the development of the underlying methodology of a solar energy planning (SEP) system for energy advisers and policy makers. The methodology predicts the baseline energy consumption of domestic properties and determines the potential for reducing this using the three key solar technologies of passive solar design, solar water heating and photovoltaic (PV) systems. A new dwelling classification system has been developed to address the major problem of data collection for city-wide domestic energy modelling. The system permits baseline energy demands to be estimated using assumed values or more accurately calculated using dwelling survey data. The methodology integrates existing models with new approaches to both identify suitable dwellings for installing solar water heating and PV systems and to quantify the potential energy savings and reductions in carbon dioxide emissions. Guidance on improving estate layouts to enhance passive solar conditions is also given. Results can be presented using a geographical information system (GIS). The paper concludes with a discussion of possible planning scenarios to illustrate how the methodology may enable planners to consider the urban-scale application of solar energy with greatly increased confidence.
History
School
- Architecture, Building and Civil Engineering
Citation
GADSDEN, S.J. ... et al, 2003. Predicting the urban solar fraction: a methodology for energy advisers and planners based on GIS. Energy and Buildings, 35 (1), pp. 37 - 48Publisher
© ElsevierVersion
- NA (Not Applicable or Unknown)
Publication date
2003Notes
This article is restricted access. The article was published in the journal, Energy and Buildings [© Elsevier]. It is available at: http://dx.doi.org/10.1016/S0378-7788(02)00078-6ISSN
0378-7788Publisher version
Language
- en