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  1. AU="Griego, Danielle"
  2. AU="Guedes-Guedes, Isabel"
  3. AU="Xiaoli Chang"
  4. AU="Jang, Joonseong"
  5. AU="Sergio Lafuente-Arroyo"
  6. AU="Löppönen, Heikki"
  7. AU="Santos, Maria Leonor"
  8. AU=Saluja Bharat
  9. AU="Nezhadi, Akram"
  10. AU=Dhar Debojyoti
  11. AU="Chandrappa S"
  12. AU="Cole, Kevin"
  13. AU=De Ceukelaire Wim
  14. AU=Tomatis L
  15. AU=Chandra Sharad
  16. AU="Mishra, Malvika"
  17. AU="Bruggemann, Kira"
  18. AU="Miura, Tanya A."
  19. AU="Kobeasy, Mohamed I."
  20. AU="Sonthonnax, Florian" AU="Sonthonnax, Florian"
  21. AU="Wang, Rongzu"

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  1. Artikel ; Online: Let it grow: How community solar policy can increase PV adoption in cities

    Nuñez-Jimenez, Alejandro / Mehta, Prakhar / Griego, Danielle

    Energy Policy. 2023, p.113477-

    2023  , Seite(n) 113477–

    Abstract: Decarbonizing urban energy consumption is critical for addressing climate change, yet renewable power installations in cities are rare due to limited space and economic unattractiveness. Community solar, where multiple electricity users share the ... ...

    Abstract Decarbonizing urban energy consumption is critical for addressing climate change, yet renewable power installations in cities are rare due to limited space and economic unattractiveness. Community solar, where multiple electricity users share the electricity generated by their rooftop PV systems, could help overcome these barriers and accelerate PV adoption in cities. Using an agent-based model, we simulated the decision-making of nearly 5000 building owners in a city district in Zurich, Switzerland, and assessed three locally relevant policy scenarios: no community solar, community solar with adjacent buildings, and community solar with buildings within a 100-m radius. The results show that allowing community solar with adjacent buildings increases the installed PV capacity in 2035 by 1%, as greater economies of scale and higher self-consumption make PV adoption more economically attractive. A more permissive policy, allowing community solar with buildings within a 100-m radius, provides more opportunities to communities to grow over time and results in 21% more PV installed capacity in 2035 than without community solar. These findings demonstrate the potential of community solar to accelerate PV adoption in cities and underscore the significant role of policy design in achieving this goal.
    Schlagwörter climate change ; decision making ; electricity ; energy ; energy policy ; models ; Switzerland ; Community solar ; PV ; Cities ; Policy design ; Agent-based model ; Energy system model
    Sprache Englisch
    Erscheinungsort Elsevier Ltd
    Dokumenttyp Artikel ; Online
    Anmerkung Pre-press version ; Use and reproduction
    ISSN 0301-4215
    DOI 10.1016/j.enpol.2023.113477
    Datenquelle NAL Katalog (AGRICOLA)

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  2. Artikel: Examining Trade-Offs between Social, Psychological, and Energy Potential of Urban Form

    Bielik, Martin / Schneider, Sven / Kuliga, Saskia / Griego, Danielle / Ojha, Varun / König, Reinhard / Schmitt, Gerhard / Donath, Dirk

    ISPRS international journal of geo-information. 2019 Jan. 24, v. 8, no. 2

    2019  

    Abstract: Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the ... ...

    Abstract Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal methods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility. For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages.
    Schlagwörter case studies ; empirical research ; energy ; geometry ; models ; planning
    Sprache Englisch
    Erscheinungsverlauf 2019-0124
    Erscheinungsort Multidisciplinary Digital Publishing Institute
    Dokumenttyp Artikel
    ZDB-ID 2655790-3
    ISSN 2220-9964
    ISSN 2220-9964
    DOI 10.3390/ijgi8020052
    Datenquelle NAL Katalog (AGRICOLA)

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    Dieser Service ist kostenpflichtig (siehe Lieferbedingungen von subito). Bestellungen, die einen Artikel nebst Supplementary Material umfassen, werden grundsätzlich wie mehrfache Bestellungen bearbeitet. Gebühren fallen in diesen Fällen für jede einzelne Bestellung an.

  3. Artikel ; Online: Machine learning approaches to understand the influence of urban environments on human’s physiological response

    Ojha, Varun Kumar / Griego, Danielle / Kuliga, Saskia / Bielik, Martin / Buš, Peter / Schaeben, Charlotte / Treyer, Lukas / Standfest, Matthias / Schneider, Sven / Koenig, Reinhard / Donath, Dirk / Schmitt, Gerhard

    Information Sciences, 474

    2019  

    Abstract: This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency ... ...

    Abstract This research proposes a framework for signal processing and information fusion of spatial-temporal multi-sensor data pertaining to understanding patterns of humans physiological changes in an urban environment. The framework includes signal frequency unification, signal pairing, signal filtering, signal quantification, and data labeling. Furthermore, this paper contributes to human-environment interaction research, where a field study to understand the influence of environmental features such as varying sound level, illuminance, field-of-view, or environmental conditions on humans’ perception was proposed. In the study, participants of various demographic backgrounds walked through an urban environment in Zürich, Switzerland while wearing physiological and environmental sensors. Apart from signal processing, four machine learning techniques, classification, fuzzy rule-based inference, feature selection, and clustering, were applied to discover relevant patterns and relationship between the participants’ physiological responses and environmental conditions. The predictive models with high accuracies indicate that the change in the field-of-view corresponds to increased participant arousal. Among all features, the participants’ physiological responses were primarily affected by the change in environmental conditions and field-of-view.

    ISSN:0020-0255

    ISSN:1872-6291
    Schlagwörter machine learning ; Data science ; Urban design ; urbanism ; Environmental change ; climate information ; Physiology ; perception
    Thema/Rubrik (Code) 150
    Sprache Englisch
    Verlag Elsevier
    Erscheinungsland ch
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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