Analyzing residential weatherization decisions using hybrid simulation modeling

Huang, Wanyu; Krejci, Caroline C.; Dorneich, Michael C.; Passe, Ulrike; Shenk, Linda; Stonewall, Jacklin

doi:10.1007/s12273-019-0518-4

Cited by 7 publications

(17 citation statements)

References 59 publications

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“…Social influences are included in almost every energy-efficient technology diffusion study using ABMs. The social influence can be described as the subjective norm (in TPB), the peer pressure (Huang et al, 2019), or the neighbourhood effect (Mohandes et al, 2018). The social influence originates from physical social interaction or online interaction (Boumaiza, Abbar, Mohandes & Sanfilippo, 2018;Huang, Dorneich, Krejci & Passe, 2017).…”

Section: Social Networkmentioning

confidence: 99%

“…It is generated from a regular network, and then a degree of the disorder increases randomness (Schiera et al, 2019). The scale-free network starts with the random network, and preferential attachments are incorporated (Huang et al, 2019). Communications on the internet are often regarded as a scale-free network (Wang et al, 2018).…”

Section: Social Networkmentioning

confidence: 99%

“…Scenario simulations in the reviewed papers have different focuses. These scenarios include different technology features (Guo, Zhang, Dong, Shen & Yin, 2014), social influences (Huang et al, 2019;Khansari & Hewitt, 2020), and policy scenarios. This section elaborates on the policy scenarios of these papers.…”

Section: Evaluated Interventionsmentioning

confidence: 99%

“…It could address the heterogeneous nature of households (Moglia, Cook & McGregor, 2017). For example, Huang et al (2019) used agent-based modelling (ABM) to simulate the upscaling process of energy-efficient technology amongst different households. Literature in this field studied the impact of policy interventions.…”

Section: Introductionmentioning

confidence: 99%

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Modelling energy-efficient renovation adoption and diffusion process for households: A review and a way forward

Hua

Han

Vries

2022

Sustainable Cities and Society

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Section: Social Networkmentioning

confidence: 99%

Section: Social Networkmentioning

confidence: 99%

Section: Evaluated Interventionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modelling energy-efficient renovation adoption and diffusion process for households: A review and a way forward

Hua

Han

Vries

2022

Sustainable Cities and Society

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“…Currently, the ABM is being used to determine the effects of different policy levers on residential weatherisation adoption. In particular, the availability and characteristics of government-funded assistance programmes are being tested (Huang et al 2019), as well as the impact of community events that emphasise the value of weatherisation and response options during extreme heat events.…”

Section: Future Workmentioning

confidence: 99%

An urban modelling framework for climate resilience in low-resource neighbourhoods

Passe¹,

Dorneich²,

Krejci³

et al. 2020

Buildings and Cities

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Climate predictions indicate a strong likelihood of more frequent, intense heat events. Resourcevulnerable, low-income neighbourhood populations are likely to be strongly impacted by future climate change, especially with respect to an energy burden. In order to identify existing and new vulnerabilities to climate change, local authorities need to understand the dynamics of extreme heat events at the neighbourhood level, particularly to identify those people who are adversely affected. A new comprehensive framework is presented that integrates human and biophysical data: occupancy/behaviour, building energy use, future climate scenarios and near-building microclimate projections. The framework is used to create an urban energy model for a low-resource neighbourhood in Des Moines, Iowa, US. Data were integrated into urban modelling interface (umi) software simulations, based on detailed surveys of residents' practices, their buildings and near-building microclimates (tree canopy effects, etc.). The simulations predict annual and seasonal building energy use in response to different climate scenarios. Preliminary results, based on 50 simulation runs with different variable combinations, indicate the importance of using locally derived building occupant schedules and point toward increased summer cooling demand and increased vulnerability for parts of the population. Practice relevance To support planning responses to increased heat, local authorities need to ascertain which neighbourhoods will be negatively impacted in order to develop appropriate strategies. Localised data can provide good insights into the impacts of human decisions and climate variability in low-resource, vulnerable urban neighbourhoods. A new detailed modelling framework synthesises data on occupant-building interactions with present and future urban climate characteristics. This identifies the areas most vulnerable to extreme heat using future climate projections and community demographics. Cities can use this framework to support decisions and climate-adaptation responses, especially for low-resource neighbourhoods. Fine-grained and locally collected data influence the outcome of combined urban energy simulations that integrate human-building interactions and occupancy schedules as well as microclimate characteristics influenced by nearby vegetation.

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Network dynamics of solar PV adoption: Reconsidering flat tax-credits and influencer seeding for inclusive renewable energy access in Albany county, New York

Sundaram,

Gonçalves,

Ghorbani

et al. 2024

Energy Research & Social Science

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Analyzing residential weatherization decisions using hybrid simulation modeling

Cited by 7 publications

References 59 publications

Modelling energy-efficient renovation adoption and diffusion process for households: A review and a way forward

Modelling energy-efficient renovation adoption and diffusion process for households: A review and a way forward

An urban modelling framework for climate resilience in low-resource neighbourhoods

Network dynamics of solar PV adoption: Reconsidering flat tax-credits and influencer seeding for inclusive renewable energy access in Albany county, New York

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