Smart City Gnosys
Smart city article details
| Title | A Multi-Objective Optimization Approach To Identify Robust Intervention Strategies To Improve The Sustainability And The Efficiency Of Urban Water Systems |
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| ID_Doc | 2833 |
| Authors | Morandi S.; Mancusi L.; Volonterio M.; Giudici F.; Garofalo E. |
| Year | 2019 |
| Published | World Environmental and Water Resources Congress 2019: Watershed Management, Irrigation and Drainage, and Water Resources Planning and Management - Selected Papers from the World Environmental and Water Resources Congress 2019 |
| DOI | http://dx.doi.org/10.1061/9780784482339.023 |
| Abstract | The urban water system (UWS) is a highly energy-consuming sector and its efficiency is important for an integrated planning of smart cities towards decarbonisation and in order to ensure in general its sustainability over time due to the risk of having a lack of such resources because climate change and demographic growth may strongly affect the water availability in future. This study focuses on the strategic planning of the UWS with special reference to water and energy saving and greenhouse gas (GHG) emissions reduction. The methodology proposed allows to identify the more efficient and robust intervention strategies by coupling an optimization algorithm to the metabolic model WaterMet2, which evaluate each solution with respect to different sustainability objectives and over multiple climate and socio-economic future scenarios. The optimal intervention strategies are compared to a business as usual strategy (BAU) in order to quantify the benefits of the identified solutions in terms of system performance and trajectories. This methodology is applied to the Italian case study of the city of Bresso (Milan, Italy), in the framework of a collaboration with the urban water utility “CAP Holding”. Results show the effectiveness of the optimal intervention strategies in considerably reducing the total cost and the GHG emissions by consequently increasing the overall efficiency of the UWS. © ASCE. |
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