Climate resilient interconnected infrastructure: Co-optimization of energy systems and urban morphology

Perera, A.T.D.; Javanroodi, Kavan; Nik, Vahid M.

doi:10.1016/j.apenergy.2020.116430

Cited by 78 publications

(33 citation statements)

References 57 publications

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“…The urban morphology affects the energy performance of buildings to a great extent due to the relationship between the building and its surroundings (e.g., shading, heat exchanges between buildings) and the type of outdoor surfaces ( Ahn and Sohn, 2019 , Mangan, Koclar Oral, Erdemir Kocagil and Sozen, 2021 , Javanroodi, Mahdavinejad and Nik, 2018 ). It is possible to reduce the space heating and cooling energy demand of buildings by optimizing the urban morphology ( Perera, Javanroodi, Wang and Hong, 2021 , Perera, Javanroodi and Nik, 2021 ). The urban morphology also modifies the microclimate conditions in urban areas, particularly in extreme weather conditions ( Javanroodi and Nik, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior

Todeschi

Javanroodi

Castello

et al. 2022

Sustainable Cities and Society

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Section: Methodsmentioning

confidence: 99%

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior

Todeschi

Javanroodi

Castello

et al. 2022

Sustainable Cities and Society

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“…The average daily irradiance values for the vacant parcels in the four neighborhoods with the density from high to low are 195.833, 194.486, 196.536, and 78.734 W/m 2 , respectively. Estimation of microclimate conditions often requires complex simulation models with a heavy computational load (Perera et al, 2021). The Urban Weather Generator, microclimate simulation software that simulates microclimate conditions based on the inputs of urban canyon geometry, building and ground material, vegetation, and rural climate, is applied to simulate the UHI effect and daily average air temperatures in the four neighborhood contexts.…”

Section: Methodsmentioning

confidence: 99%

Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities

Quan

Chang

Castro‐Lacouture

et al. 2022

Environment and Planning B: Urban Analytics and City Science

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To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized energy source in urban systems, the overall performance can vary by levels of urban nutrients, solar and CO2 resources, and the transportation cost when considering its application to different urban densities, urban form, and the spatial scale of urban settings. This research explores three potential impacts on the algal system’s energy performance: (1) urban density, (2) urban form in different contexts, and (3) spatial scale. The research examines the impacts by testing urban settings given in actual contexts in Atlanta, Georgia, USA. Four neighborhoods representing the high-density urban, mid-density urban, mixed suburban, and typical suburban areas are investigated. The density-scale–performance relationships are explored through testing different urban forms of neighborhoods in both hypothetical and actual neighborhood settings. A GIS-based model is developed to estimate the overall energy performance of the decentralized renewable energy system in urban environments. Results show that the energy performance is positive mainly for high-density urban neighborhoods with small-to-medium scales, up to 0.36 MJ per ton of municipal solid wastes for actual settings and 0.37 MJ for hypothetical cases. Neighborhoods with higher density have higher energy performance while up scaling has negative effects on the energy performance with a low degree of significance. Optimal scales are found as a 1-km radius in real test beds and 1.3 km in hypothetical settings, in which the results show trade-offs between scaling effects in the system efficiency gain and the transportation cost increase.

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“…The most recent studies regarding climate change on energy demand point to the strong likelihood of lower heating demand in the future, while cooling demand may increase (e.g., [23][24][25][26]). In contrast, research on the impact of climate change on the potential of renewable energy generation in Europe is not consistent.…”

Section: Introductionmentioning

confidence: 99%

Climate Change and Renewable Energy Generation in Europe—Long-Term Impact Assessment on Solar and Wind Energy Using High-Resolution Future Climate Data and Considering Climate Uncertainties

2022

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Climate change can strongly affect renewable energy production. The state of the art in projecting future renewable energy generation has focused on using regional climate prediction. However, regional climate prediction is characterized by inherent uncertainty due to the complexity of climate models. This work provides a comprehensive study to quantify the impact of climate uncertainties in projecting future renewable energy potential over five climate zones of Europe. Thirteen future climate scenarios, including five global climate models (GCMs) and three representative concentration pathways (RCPs), are downscaled by the RCA4 regional climate model (RCM) over 90 years (2010–2099), divided into three 30-year periods. Solar and wind energy production is projected considering short-/long-term climate variations and uncertainties in seven representative cities (Narvik, Gothenburg, Munich, Antwerp, Salzburg, Valencia, and Athens). The results showed that the uncertainty caused by GCMs has the most substantial impact on projecting renewable energy generation. The variations due to GCM selection can become even larger than long-term climate change variations over time. Climate change uncertainties lead to over 23% and 45% projection differences for solar PV and wind energy potential, respectively. While the signal of climate change in solar radiation is weak between scenarios and over time, wind energy generation is affected by 25%.

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Climate resilient interconnected infrastructure: Co-optimization of energy systems and urban morphology

Cited by 78 publications

References 57 publications

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior

Impact of the COVID-19 pandemic on the energy performance of residential neighborhoods and their occupancy behavior

Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities

Climate Change and Renewable Energy Generation in Europe—Long-Term Impact Assessment on Solar and Wind Energy Using High-Resolution Future Climate Data and Considering Climate Uncertainties

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