IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v231y2018icp433-445.html
   My bibliography  Save this article

Energy modeling of urban informal settlement redevelopment: Exploring design parameters for optimal thermal comfort in Dharavi, Mumbai, India

Author

Listed:
  • Nutkiewicz, Alex
  • Jain, Rishee K.
  • Bardhan, Ronita

Abstract

Cities are of paramount importance to meeting our sustainable energy goals. In particular, the massive informal settlement or “slum” redevelopment programs occurring in many global cities of the developing world represent an incredible opportunity to design dwellings that improve living conditions while putting us on a trajectory towards more energy efficient cities. However, we currently lack an understanding of how redevelopment designs will impact occupant aspects like thermal comfort and energy usage. In this paper, we explore how early-stage design decisions for redevelopment of informal settlements would impact thermal comfort and energy implications in a highly contextualized energy simulation. Specifically, we conduct a first-of-its-kind analysis of the Dharavi informal settlement in Mumbai, India that identifies optimal redevelopment design configurations, explores spatial and temporal thermal heterogeneity and quantifies the impact that specific design parameters have on thermal comfort. In doing so, we aim to establish a novel computational energy modeling framework for exploring the impact that localized design parameters have on informal settlement redevelopment in India and the rest of the world. We model and simulate 18,900 design scenarios in the existing horizontal (M1) and two proposed vertical (M2, M3) building morphologies. Our results indicate that redevelopment plans must be designed carefully since simply replicating current materials and other parameters in a vertical form will likely worsen thermal comfort and associated energy burdens for occupants. Moreover, results revealed that the M3 vertical morphology was the most desired design case as it provided the most “compliant” days (i.e., days in which no dwelling exceeded the upper bound of Indian comfort standards) but thermal comfort equity could be an issue as significant variation exists between units at the ground floor and top floor. The M3 vertical morphology was also found to be the most sensitive form to other building design parameters (e.g., WWR, thermal insulation, ventilation) – underscoring the need for specific design guidelines on other parameters when adopting this form. Deeper sensitivity analysis revealed that window-to-wall ratio (WWR) was the most sensitive design parameter. Additionally, we found that the ventilation rate had as much of an impact on thermal comfort as other design parameters pointing to opportunities to enhance thermal comfort in the operational phase of dwellings. In the end, by establishing a computational energy modeling framework specifically for informal settlements and exploring design parameters for the largest informal settlement in Asia (Dharavi), our work has significant implications for how we can inform informal settlement redevelopment that both enhances occupant living conditions and set our cities’ on a pathway to a sustainable energy future.

Suggested Citation

  • Nutkiewicz, Alex & Jain, Rishee K. & Bardhan, Ronita, 2018. "Energy modeling of urban informal settlement redevelopment: Exploring design parameters for optimal thermal comfort in Dharavi, Mumbai, India," Applied Energy, Elsevier, vol. 231(C), pages 433-445.
  • Handle: RePEc:eee:appene:v:231:y:2018:i:c:p:433-445
    DOI: 10.1016/j.apenergy.2018.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918313035
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bhattacharyya, Subhes C., 2015. "Influence of India’s transformation on residential energy demand," Applied Energy, Elsevier, vol. 143(C), pages 228-237.
    2. Chen, Xi & Yang, Hongxing & Wang, Yuanhao, 2017. "Parametric study of passive design strategies for high-rise residential buildings in hot and humid climates: miscellaneous impact factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 442-460.
    3. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    4. Yao, Jian, 2012. "Energy optimization of building design for different housing units in apartment buildings," Applied Energy, Elsevier, vol. 94(C), pages 330-337.
    5. Kotireddy, Rajesh & Hoes, Pieter-Jan & Hensen, Jan L.M., 2018. "A methodology for performance robustness assessment of low-energy buildings using scenario analysis," Applied Energy, Elsevier, vol. 212(C), pages 428-442.
    6. Tong, Zheming & Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard B., 2016. "Energy saving potential of natural ventilation in China: The impact of ambient air pollution," Applied Energy, Elsevier, vol. 179(C), pages 660-668.
    7. Indraganti, Madhavi, 2010. "Thermal comfort in naturally ventilated apartments in summer: Findings from a field study in Hyderabad, India," Applied Energy, Elsevier, vol. 87(3), pages 866-883, March.
    8. Aklin, Michaël & Bayer, Patrick & Harish, S.P. & Urpelainen, Johannes, 2015. "Quantifying slum electrification in India and explaining local variation," Energy, Elsevier, vol. 80(C), pages 203-212.
    9. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    10. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2016. "Defining the Influence Region in neighborhood-scale CFD simulations for natural ventilation design," Applied Energy, Elsevier, vol. 182(C), pages 625-633.
    11. Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard Barry & Tong, Zheming, 2016. "Energy Saving Potential of Natural Ventilation in China: The Impact of Ambient Air Pollution," Scholarly Articles 27733689, Harvard University Department of Economics.
    12. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2017. "Estimating natural ventilation potential for high-rise buildings considering boundary layer meteorology," Applied Energy, Elsevier, vol. 193(C), pages 276-286.
    13. Chikaraishi, Makoto & Jana, Arnab & Bardhan, Ronita & Varghese, Varun & Fujiwara, Akimasa, 2017. "A framework to analyze capability and travel in formal and informal urban settings: A case from Mumbai," Journal of Transport Geography, Elsevier, vol. 65(C), pages 101-110.
    14. Mustafaraj, Giorgio & Marini, Dashamir & Costa, Andrea & Keane, Marcus, 2014. "Model calibration for building energy efficiency simulation," Applied Energy, Elsevier, vol. 130(C), pages 72-85.
    15. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    16. Urban, F. & Benders, R.M.J. & Moll, H.C., 2007. "Modelling energy systems for developing countries," Energy Policy, Elsevier, vol. 35(6), pages 3473-3482, June.
    17. Indraganti, Madhavi, 2011. "Thermal comfort in apartments in India: Adaptive use of environmental controls and hindrances," Renewable Energy, Elsevier, vol. 36(4), pages 1182-1189.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Debnath, Ramit & Bardhan, Ronita & Sunikka-Blank, Minna, 2019. "How does slum rehabilitation influence appliance ownership? A structural model of non-income drivers," Energy Policy, Elsevier, vol. 132(C), pages 418-428.
    2. Chang, Soowon & Saha, Nirvik & Castro-Lacouture, Daniel & Yang, Perry Pei-Ju, 2019. "Multivariate relationships between campus design parameters and energy performance using reinforcement learning and parametric modeling," Applied Energy, Elsevier, vol. 249(C), pages 253-264.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:231:y:2018:i:c:p:433-445. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.