Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations

Katal, Ali; Mortezazadeh, Mohammad; Wang, Liangzhu

doi:10.1016/j.apenergy.2019.04.192

Cited by 73 publications

(30 citation statements)

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“…For buildings and their environment co-simulation, land use and building geometry data are used to initialize both building and urban canopy models. Katal et al (Katal, Mortezazadeh and Wang, 2019) introduced CityFFD (City Fast Fluid Dynamics), an urban-scale fast fluid dynamics model for microclimate modeling to couple with CityBEM (City Building Energy Model), an urban building energy model with archetype buildings for aerodynamics and heat transfer information exchange at run time to produce highresolution results of building thermal load, microclimate condition, and building behavior during extreme weather. However, limited data resources in past studies allowed co-simulation to be performed only at a limited level of detail.…”

Section: Figure 6 Coupling Schema Between Building Energy Models Andmentioning

confidence: 99%

“…Aligned with the stakeholders' interest, potential applications of UBEM are reviewed in three domains as summarized in Table 3. Qomi et al, 2016;Hong, Chen, Piette, et al, 2016) Demand energy auditing and forecasting Demand flexibility (Pezzulli et al, 2006;Fu et al, 2009;Delmastro et al, 2017;Wang et al, 2018) Urban resiliency (Gros, Bozonnet and Inard, 2014;Link, Pillich and Klein, 2014;Caro-Martínez and Sendra, 2018;Frayssinet et al, 2018;Oregi et al, 2018) Existing urban buildings retrofiting Energy savings; GHG emissions reduction; Cost effectiveness (Ward and Choudhary, 2014;Lee et al, 2015;McArthur and Jofeh, 2016;Monteiro et al, 2018;Nagpal and Reinhart, 2018) Urban energy planning Energy efficiency (Chow, Chan and Song, 2004;Fu et al, 2009;Lin et al, 2010;Koch, 2016;Delmastro et al, 2017) Urban resiliency under climate (Pisello et al, 2015;Martin et al, 2017; change effects Ciancio et al, 2018;Katal, Mortezazadeh and Wang, 2019) First of all, the formulation of energy policies for urban building stock frequently requires the evaluation of the overall building energy performance of the urban districts (Tardioli et al, 2018)…”

Section: Question 9: What Are the Example Applications Of Ubem?mentioning

confidence: 99%

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Ten questions on urban building energy modeling

Hong

Chen

Luo

et al. 2020

Building and Environment

316

121

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Buildings in cities consume up to 70% of all primary energy. To achieve cities' energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings. Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers. This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.

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Section: Figure 6 Coupling Schema Between Building Energy Models Andmentioning

confidence: 99%

Section: Question 9: What Are the Example Applications Of Ubem?mentioning

confidence: 99%

Ten questions on urban building energy modeling

Hong

Chen

Luo

et al. 2020

Building and Environment

316

121

View full text Add to dashboard Cite

show abstract

“…Another two simplified metrics that have been developed recently are Passive Survivability-Winter (PSW) and Passive Survivability-Summer (PSS) [105]. They were initially derived for building designers to evaluate the resilience level of different design solutions, but were also used to evaluate retrofit measures [80]. One limitation of PSW and PSS is that they only consider temperature, which is relatively less comprehensive for evaluating thermal resilience.…”

Section: Review Of Resilience Metricsmentioning

confidence: 99%

“…Katal et al performed a case study on an urban area to evaluate the building and city resilience against the extreme events, using a urban platform they developed. A rudimentary retrofit analysis was also conducted to evaluate the added level of resilience [80]. This is a great research that developed a useful tool for evaluating energy efficiency and resilience on urban scale.…”

Section: Introductionmentioning

confidence: 99%

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Sun

Specian

Hong

2020

Building and Environment

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Extreme weather events become more frequent and severe due to climate change. Although energy efficiency technologies can influence thermal resilience of buildings, they are traditionally studied separately, and their interconnections are rarely quantified. This study developed a methodology of modeling and analysis to provide insights into the nexus of thermal resilience and energy efficiency of buildings. We conducted a case study of a real nursing home in Florida, where 12 patients died during Hurricane Irma in 2017 due to HVAC system power loss, to understand and quantify how passive and active energy efficiency measures (EEMs) can improve thermal resilience to reduce heat-exposure risk of patients. Results show that passive measures of opening windows and doors for natural ventilation, as well as miscellaneous load reduction, are very effective in eliminating the extreme dangerous occasions. However, to maintain safe conditions, active measures such as on-site power generators and thermal storage are also needed. The nursing home was further studied by changing its location to two other cities: San Francisco (mild climate) and Chicago (cold winter and hot summer). Results revealed that the EEMs' impacts on thermal resilience vary significantly by climate and building characteristics. The study also estimated the costs of EEMs to help stakeholders prioritize the measures. Passive measures that may not save energy may greatly improve thermal resilience, and thus should be considered in building design or retrofit. Findings from this study indicate energy efficiency technologies should be evaluated not only by their energy savings performance but also by their influence on a building's resilience to extreme weather events.

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“…There are some studies to assess the resilience of buildings under natural disasters. For instance, a study is conducted to investigate the resilience of about 1500 buildings against three-days power outage due to natural disasters in the Montreal, Canada [17]. In the building energy systems, it is useful to denote the optimal tradeoff between the operating cost and system resilience [18].…”

Section: Introductionmentioning

confidence: 99%

Resilience-uncertainty nexus in building energy management integrated with solar system and battery storage

Mehrjerdi¹

2024

IEEE Access

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Application of local energy resources in the buildings encounters such systems with both uncertainties in the produced power and failures (events) of the resources. The energy planning excluding uncertainty and events may be economically efficient but it is not resilient and practical. This paper provides a platform for energy management in the building under a set of realistic failures and uncertainties. The energy resilience is improved and the energy cost is decreased at the same time while all events and uncertainties are modeled. A typical building integrated with solar-battery-grid is studied. The resilience index is to minimize the loss of demanded service following all possible events. Three objective functions are defined and compared including (i) resilience cost, (ii) energy cost, (ii) resilience and energy costs together. The stochastic mixed integer linear programming is implemented to minimize the objective functions. The results validate that the developed toolkit can cope with all events and uncertainties with minimum operating cost and maximum resilience. The optimal tradeoff between operating cost, resilience, and uncertainty is presented. The results demonstrate that the uncertainty and resilience increase the planning cost by 5.3% and 13.8%, respectively, and both of them together increase the cost by 19.5%.

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Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations

Cited by 73 publications

References 30 publications

Ten questions on urban building energy modeling

Ten questions on urban building energy modeling

Nexus of thermal resilience and energy efficiency in buildings: A case study of a nursing home

Resilience-uncertainty nexus in building energy management integrated with solar system and battery storage

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