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An optimization tool for the assessment of urban energy scenarios
Energy demand and production of neighbourhoods are central issues in the development of integrated spatial-energy strategies in the framework of recent European Policies. This study provides a comprehensive tool that combines spatial and energy issues with optimization methods to support urban plann...
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Published in: | Energy (Oxford) 2018-08, Vol.156, p.418-429 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Energy demand and production of neighbourhoods are central issues in the development of integrated spatial-energy strategies in the framework of recent European Policies. This study provides a comprehensive tool that combines spatial and energy issues with optimization methods to support urban planners in the decision-making process for urban energy strategies. By adopting an integrated approach, optimized urban energy scenarios aimed at reducing CO2 emissions are developed and results are shown in spatial-energy maps. Through the application of the proposed method, current urban energy demand is determined and potential local production of electrical energy due to the introduction of renewable energy systems is assessed. The insertion of renewable energy systems allows configuring a network of energy exchanges where buildings are considered able to share energy through physical connections. The optimization of energy exchanges among buildings is carried out by using a model based on complex networks and is represented in maps, developed in GIS, allowing the integration between energy evaluations and spatial planning. As case study, the method has been applied to a neighbourhood of the municipality of Catania in Southern Italy.
•Models to support urban planners in the development of urban energy strategies are required.•The proposed method integrates a spatial-energy model and an optimization strategy based on complex networks.•Territory-related energy demand and production of buildings are derived from data collection.•Optimized urban energy scenarios aimed at reducing CO2 emissions are developed. |
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ISSN: | 0360-5442 |
DOI: | 10.1016/j.energy.2018.05.114 |