| 1. |
- Aghaei, Mohammadreza, et al.
(författare)
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Collective Intelligence for Energy Flexibility - Collectief : An EU H2020 Project for Enhancing Energy Efficiency and Flexibility in Existing Buildings
- 2023
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Ingår i: 2023 International Conference on Future Energy Solutions, FES 2023. - 9798350332308
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Konferensbidrag (refereegranskat)abstract
- COLLECTiEF (Collective Intelligence for Energy Flexibility) is an EU-funded H2020 project running from June 2021 to May 2025. COLLECTiEF aims to enhance, implement, test, and evaluate an interoperable and saleable energy management system based on collective intelligence that allows easy and seamless integration of legacy equipment into a collaborative network within and between existing buildings and urban energy systems with reduced installation cost, data transfer, and computational power while increasing user comfort, energy flexibility, climate resilience, and data security. To achieve this goal, the COLLECTiEF solution requires the development of software and hardware packages to smart up buildings and their legacy equipment on a large scale while maintaining simple and robust communication with the energy grid. Here, we present the project concept, structure, objectives, and working packages. Furthermore, the main progress and achievements obtained during the first two years of the project are presented.
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| 2. |
- Deng, Zhang, et al.
(författare)
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Using urban building energy modeling to quantify the energy performance of residential buildings under climate change
- 2023
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Ingår i: Building Simulation. - 1996-3599. ; 16:9, s. 1629-1643
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Tidskriftsartikel (refereegranskat)abstract
- The building sector is facing a challenge in achieving carbon neutrality due to climate change and urbanization. Urban building energy modeling (UBEM) is an effective method to understand the energy use of building stocks at an urban scale and evaluate retrofit scenarios against future weather variations, supporting the implementation of carbon emission reduction policies. Currently, most studies focus on the energy performance of archetype buildings under climate change, which is hard to obtain refined results for individual buildings when scaling up to an urban area. Therefore, this study integrates future weather data with an UBEM approach to assess the impacts of climate change on the energy performance of urban areas, by taking two urban neighborhoods comprising 483 buildings in Geneva, Switzerland as case studies. In this regard, GIS datasets and Swiss building norms were collected to develop an archetype library. The building heating energy consumption was calculated by the UBEM tool-AutoBPS, which was then calibrated against annual metered data. A rapid UBEM calibration method was applied to achieve a percentage error of 2.7%. The calibrated models were then used to assess the impacts of climate change using four future weather datasets out of Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The results showed a decrease of 22%-31% and 21%-29% for heating energy consumption, an increase of 113%-173% and 95%-144% for cooling energy consumption in the two neighborhoods by 2050. The average annual heating intensity dropped from 81 kWh/m 2 in the current typical climate to 57 kWh/m 2 in the SSP5-8.5, while the cooling intensity rose from 12 kWh/m 2 to 32 kWh/m 2. The overall envelope system upgrade reduced the average heating and cooling energy consumption by 41.7% and 18.6%, respectively, in the SSP scenarios. The spatial and temporal distribution of energy consumption change can provide valuable information for future urban energy planning against climate change.
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| 3. |
- Hosseini, Mohammad, et al.
(författare)
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High-resolution impact assessment of climate change on building energy performance considering extreme weather events and microclimate – Investigating variations in indoor thermal comfort and degree-days
- 2022
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Ingår i: Sustainable Cities and Society. - : Elsevier BV. - 2210-6707. ; 78
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Tidskriftsartikel (refereegranskat)abstract
- Climate change and urbanization are two major challenges when planning for sustainable energy transition in cities. The common approach for energy demand estimation is using only typical meso-scale weather data in building energy models (BEMs), which underestimates the impacts of extreme climate and microclimate variations. To quantify the impacts of such underestimation on assessing the future energy performance of buildings, this study simulates a high spatiotemporal resolution BEM for two representative residential buildings located in a 600 × 600 m2 urban area in Southeast Sweden while accounting for both climate change and microclimate. Future climate data are synthesized using 13 future climate scenarios over 2010-2099, divided into three 30-year periods, and microclimate data are generated considering the urban morphology of the area. It is revealed that microclimate can cause 17% rise in cooling degree-day (CDD) and 7% reduction in heating degree-day (HDD) on average compared to mesoclimate. Considering typical weather conditions, CDD increases by 45% and HDD decreases by 8% from one 30-year period to another. Differences can become much larger during extreme weather conditions. For example, CDD can increase by 500% in an extreme warm July compared to a typical one. Results also indicate that annual cooling demand becomes four and five times bigger than 2010-2039 in 2040-2069 and 2070-2099, respectively. The daily peak cooling load can increase up to 25% in an extreme warm day when accounting for microclimate. In the absence of cooling systems during extreme warm days, the indoor temperature stays above 26°C continuously over a week and reaches above 29.2°C. Moreover, the annual overheating hours can increase up to 140% in the future. These all indicate that not accounting for influencing climate variations can result in maladaptation or insufficient adaptation of urban areas to climate change.
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| 4. |
- Javanroodi, Kavan, 1988, et al.
(författare)
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A multi-objective optimization framework for designing climate-resilient building forms in urban areas
- 2020
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Ingår i: IOP Conference Series: Earth and Environmental Science. - : IOP Publishing. - 1755-1307 .- 1755-1315. ; 588:3
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Konferensbidrag (refereegranskat)abstract
- With the increasing global awareness about the impacts of climate change on the built environments, the need for improving the climate resilience of buildings is being more acknowledged. Despite the high number of relevant studies, there is a lack of frameworks to assess the resiliency of buildings and urban areas. This study presents a multi-objective framework to optimize the form of buildings against its energy performance and thermal comfort considering its resiliency to the uncertainties of climate change during three thirty-years periods (2010-2099) of a warm region. Three performance sections related to building's form are identified and categorized for the impact assessment including (1) urban form, (2) orientation, and (3) transparency with ten influencing parameters. The analysis of non-dominated solutions out of the optimization process showed that the annual energy performance (cooling and heating demand) of the urban areas can improve about 34% in both typical and extreme weather conditions whilst maintaining thermal comfort by optimizing the overall form of the buildings with similar built density and heights. Moreover, Buildings with 15 to 30-degree rotations and 33% glazing ratio showed the highest energy performance. Finally, the top 20 resilient building forms with the highest energy performance and climate resiliency were selected out of the database of results to derive design suggestions.
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| 5. |
- Javanroodi, Kavan, 1988, et al.
(författare)
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A novel design-based optimization framework for enhancing the energy efficiency of high-rise office buildings in urban areas
- 2019
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Ingår i: Sustainable Cities and Society. - : Elsevier BV. - 2210-6707. ; 49
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Tidskriftsartikel (refereegranskat)abstract
- Designing high-rise buildings is a complex and challenging task involving several parameters and variables. Recently, there have been major attempts to design the overall form of these buildings based on optimization approaches. This paper introduces a multi-objective optimization framework based on Genetic Algorithm, namely Energy Efficient Form-finder (EEF), consisting four main steps of Form-Generation, Form-Simulation, Form-Optimization and Form-Solutions. The EEF with a comprehensive design-based approach is evaluated through five functions considering objectives of minimizing cooling and heating demand and thermal discomfort time while maintaining operative temperature on the defined thermal comfort zone. This work studies the form combination of five reference buildings based on a new technique called “Building Modular Cell” in five different urban areas, resulting in twenty-five distinct design problems. According to the results, there is a great potential to adopt EEF in newly-built projects with a rectangular layout; while it can reduce the annual energy demand and thermal discomfort time of the optimal form combinations around 34% and 12% respectively. Finally, a series of qualitative and quantitative design-aid recommendations are presented based on 1998 best design solutions, which can be used as form-finding rules of thumb by architects and urban designers at the early design stages.
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| 6. |
- Javanroodi, Kavan, 1988, et al.
(författare)
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Combining computational fluid dynamics and neural networks to characterize microclimate extremes: Learning the complex interactions between meso-climate and urban morphology
- 2022
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Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697 .- 1879-1026. ; 829
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Tidskriftsartikel (refereegranskat)abstract
- The urban form and extreme microclimate events can have an important impact on the energy performance of buildings, urban comfort and human health. State-of-the-art building energy simulations require information on the urban microclimate, but typically rely on ad-hoc numerical simulations, expensive in-situ measurements, or data from nearby weather stations. As such, they do not account for the full range of possible urban microclimate variability and findings cannot be generalized across urban morphologies. To bridge this knowledge gap, this study proposes two data-driven models to downscale climate variables from the meso to the micro scale in arbitrary urban morphologies, with a focus on extreme climate conditions. The models are based on a feedforward and a deep neural network (NN) architecture, and are trained using results from computational fluid dynamics (CFD) simulations of flow over a series of idealized but representative urban environments, spanning a realistic range of urban morphologies. Both models feature a relatively good agreement with corresponding CFD training data, with a coefficient of determination R2 = 0.91 (R2 = 0.89) and R2 = 0.94 (R2 = 0.92) for spatially-distributed wind magnitude and air temperature for the deep NN (feedforward NN). The models generalize well for unseen urban morphologies and mesoscale input data that are within the training bounds in the parameter space, with a R2 = 0.74 (R2 = 0.69) and R2 = 0.81 (R2 = 0.74) for wind magnitude and air temperature for the deep NN (feedforward NN). The accuracy and efficiency of the proposed CFD-NN models makes them well suited for the design of climate-resilient buildings at the early design stage.
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| 7. |
- Javanroodi, Kavan, et al.
(författare)
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Designing climate resilient energy systems in complex urban areas considering urban morphology : A technical review
- 2023
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Ingår i: Advances in Applied Energy. - 2666-7924. ; 12
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Forskningsöversikt (refereegranskat)abstract
- The urban energy infrastructure is facing a rising number of challenges due to climate change and rapid urbanization. In particular, the link between urban morphology and energy systems has become increasingly crucial as cities continue to expand and become more densely populated. Achieving climate neutrality adds another layer of complexity, highlighting the need to address this relationship to develop effective strategies for sustainable urban energy infrastructure. The occurrence of extreme climate events can also trigger cascading failures in the system components, leading to long-lasting blackouts. This review paper thoroughly explores the challenges of incorporating urban morphology into energy system models through a comprehensive literature review and proposes a new framework to enhance the resilience of interconnected systems. The review emphasizes the need for integrated models to provide deeper insights into urban energy systems design and operation and addresses the cascading failures, interconnectivity, and compound impacts of climate change and urbanization on energy systems. It also explores emerging challenges and opportunities, including the requirement for high-quality data, utilization of big data, and integration of advanced technologies like artificial intelligence and machine learning in urban energy systems. The proposed framework integrates urban morphology classification, mesoscale and microscale climate data, and a design and operation process to consider the influence of urban morphology, climate variability, and extreme events. Given the prevalence of extreme climate events and the need for climate-resilient strategies, the study underscores the significance of improving energy system models to accommodate future climate variations while recognizing the interconnectivity within urban infrastructure.
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| 8. |
- Javanroodi, Kavan, 1988, et al.
(författare)
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Evaluating the impacts of urban form on the microclimate in the dense areas
- 2019
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Ingår i: Building Simulation Conference Proceedings. - : IBPSA. - 2522-2708. - 9781713809418 ; 5, s. 3586-3593
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Konferensbidrag (refereegranskat)abstract
- Urban form is consisting of several complex parameters which can affect urban microclimate in the energy calculations; most importantly the geometry of buildings, streets andcanopies. This study with a novel design-based approach generates 400 urban forms in the context of a dense urban area to evaluate the air flow and consequently the ventilation potential with the aids of CFD simulations in the warm months. Results, indicating the impacts of urban form on microclimate showed that by adopting some design-based suggestions, ventilation potential can be increased up to 17.5% even in severe air pollution conditions.
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| 9. |
- Javanroodi, Kavan, 1988, et al.
(författare)
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Impacts of Microclimate Conditions on the Energy Performance of Buildings in Urban Areas
- 2019
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Ingår i: Buildings. - : MDPI AG. - 2075-5309. ; 9:8
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Tidskriftsartikel (refereegranskat)abstract
- Urbanization trends have changed the morphology of cities in the past decades. Complex urban areas with wide variations in built density, layout typology, and architectural form have resulted in more complicated microclimate conditions. Microclimate conditions affect the energy performance of buildings and bioclimatic design strategies as well as a high number of engineering applications. However, commercial energy simulation engines that utilize widely-available mesoscale weather data tend to underestimate these impacts. These weather files, which represent typical weather conditions at a location, are mostly based on long-term metrological observations and fail to consider extreme conditions in their calculation. This paper aims to evaluate the impacts of hourly microclimate data in typical and extreme climate conditions on the energy performance of an office building in two different urban areas. Results showed that the urban morphology can reduce the wind speed by 27% and amplify air temperature by more than 14%. Using microclimate data, the calculated outside surface temperature, operating temperature and total energy demand of buildings were notably different to those obtained using typical regional climate model (RCM)-climate data or available weather files (Typical Meteorological Year or TMY), i.e., by 61%, 7%, and 21%, respectively. The difference in the hourly peak demand during extreme weather conditions was around 13%. The impact of urban density and the final height of buildings on the results are discussed at the end of the paper.
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| 10. |
- Javanroodi, Kavan, 1988, et al.
(författare)
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Impacts of urban morphology on reducing cooling load and increasing ventilation potential in hot-arid climate
- 2018
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Ingår i: Applied Energy. - : Elsevier BV. - 1872-9118 .- 0306-2619. ; 231, s. 714-746
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Tidskriftsartikel (refereegranskat)abstract
- Cooling buildings in urban areas with hot-arid climate put huge loads on the energy system. There is an increasing trend in urban energy studies to recognize the urban design variables and parameters associated with the energy performance of buildings. In this work, a novel approach is introduced to investigate the impacts of urban morphology on cooling load reduction and enhancing ventilation potential by studying a high-rise building (target building), surrounded by different urban configurations, during six warm months of the year in Tehran at four major sections including: (1) generating 1600 urban case studies considering three parameters (Urban Density, Urban Building Form, and Urban Pattern) and modelling the urban morphology of Tehran based on a technique namely “Building Modular Cells”, (2) validation study of CFD simulation of the wind flow around buildings, (3) calculating the average cooling load and wind flow at the rooftop of the target building, and (4) investigating sixteen best urban configurations with the lowest cooling load and highest ventilation potential. Results indicate that urban morphology has a notable impact on the energy consumption of buildings, decreasing cooling load and increasing ventilation potential more than 10% and 15% respectively, compared to the typical cases. This work also proposes design solutions for architects and urban designers, based on Top 100 configurations (out of 1600), for improved energy performance and better ventilation of buildings in urban areas.
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