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Optimization of a residential district with special consideration on energy and water reliability

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  • Campana, Pietro Elia
  • Quan, Steven Jige
  • Robbio, Federico Ignacio
  • Lundblad, Anders
  • Zhang, Yang
  • Ma, Tao
  • Karlsson, Björn
  • Yan, Jinyue

Abstract

Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. From an engineering and architecture perspective it is mandatory to design cities taking into account energy and water issues to achieve high living and sustainability standards. The aim of this paper is to develop an optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability through dynamic simulations. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint.

Suggested Citation

  • Campana, Pietro Elia & Quan, Steven Jige & Robbio, Federico Ignacio & Lundblad, Anders & Zhang, Yang & Ma, Tao & Karlsson, Björn & Yan, Jinyue, 2017. "Optimization of a residential district with special consideration on energy and water reliability," Applied Energy, Elsevier, vol. 194(C), pages 751-764.
    • Handle: RePEc:eee:appene:v:194:y:2017:i:c:p:751-764
    DOI: 10.1016/j.apenergy.2016.10.005
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    2. Lago, Jesus & De Ridder, Fjo & Mazairac, Wiet & De Schutter, Bart, 2019. "A 1-dimensional continuous and smooth model for thermally stratified storage tanks including mixing and buoyancy," Applied Energy, Elsevier, vol. 248(C), pages 640-655.
    3. Hussain, Akhtar & Bui, Van-Hai & Kim, Hak-Man, 2019. "Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience," Applied Energy, Elsevier, vol. 240(C), pages 56-72.
    4. Zhang, Yang & Campana, Pietro Elia & Yang, Ying & Stridh, Bengt & Lundblad, Anders & Yan, Jinyue, 2018. "Energy flexibility from the consumer: Integrating local electricity and heat supplies in a building," Applied Energy, Elsevier, vol. 223(C), pages 430-442.
    5. Adefarati, T. & Bansal, R.C., 2017. "Reliability and economic assessment of a microgrid power system with the integration of renewable energy resources," Applied Energy, Elsevier, vol. 206(C), pages 911-933.
    6. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    7. Ferrari, Simone & Zagarella, Federica & Caputo, Paola & D'Amico, Antonino, 2019. "Results of a literature review on methods for estimating buildings energy demand at district level," Energy, Elsevier, vol. 175(C), pages 1130-1137.
    8. Fuentes-Cortés, Luis Fabián & Flores-Tlacuahuac, Antonio, 2018. "Integration of distributed generation technologies on sustainable buildings," Applied Energy, Elsevier, vol. 224(C), pages 582-601.
    9. Angelo Algieri & Pietropaolo Morrone & Sergio Bova, 2020. "Techno-Economic Analysis of Biofuel, Solar and Wind Multi-Source Small-Scale CHP Systems," Energies, MDPI, vol. 13(11), pages 1-21, June.
    10. Younesi, Abdollah & Shayeghi, Hossein & Wang, Zongjie & Siano, Pierluigi & Mehrizi-Sani, Ali & Safari, Amin, 2022. "Trends in modern power systems resilience: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    11. Fu, Xueqian & Zhang, Xiurong & Qiao, Zheng & Li, Gengyin, 2019. "Estimating the failure probability in an integrated energy system considering correlations among failure patterns," Energy, Elsevier, vol. 178(C), pages 656-666.
    12. Song, Chunhe & Jing, Wei & Zeng, Peng & Rosenberg, Catherine, 2017. "An analysis on the energy consumption of circulating pumps of residential swimming pools for peak load management," Applied Energy, Elsevier, vol. 195(C), pages 1-12.

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