This study is focused on the optimization of the annual cost and greenhouse impact related to the supply of natural gas and electricity of an urban microgrid through the installation of components as renewable energy sources, energy storage units and converters. As input parameters of the optimization model, the energy demand of a medium density urban district was estimated, while average costs and emissions of equipment were collected in market reports and literature. The outputs of the model are the optimal size and the schedule of each component. Moreover, optimization analysis was carried out for two different scenarios, comparing Italian and Vietnamese energy system cost and environmental features, in order to understand how the optimization process is affected by different climatic and socio-economic input conditions.
Cannata, N., Cellura, M., Longo, S., Montana, F., Sanseverino, E.R., Luu, Q.L., et al. (2019). Multi-Objective Optimization of Urban Microgrid Energy Supply According to Economic and Environmental Criteria. In Proceedings of 2019 IEEE Milan PowerTech (pp. 1-6) [10.1109/PTC.2019.8810776].
Multi-Objective Optimization of Urban Microgrid Energy Supply According to Economic and Environmental Criteria
Cellura, M.;Longo, S.;Montana, F.
;Sanseverino, E. Riva;Luu, Q. L.;
2019-06-01
Abstract
This study is focused on the optimization of the annual cost and greenhouse impact related to the supply of natural gas and electricity of an urban microgrid through the installation of components as renewable energy sources, energy storage units and converters. As input parameters of the optimization model, the energy demand of a medium density urban district was estimated, while average costs and emissions of equipment were collected in market reports and literature. The outputs of the model are the optimal size and the schedule of each component. Moreover, optimization analysis was carried out for two different scenarios, comparing Italian and Vietnamese energy system cost and environmental features, in order to understand how the optimization process is affected by different climatic and socio-economic input conditions.File | Dimensione | Formato | |
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PES 2019 - Energy Hub Optimization v04.pdf
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