| 1. |
- Nik, Vahid, 1979, et al.
(författare)
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Investigating the importance of future climate typology on estimating the energy performance of buildings in the EPFL campus
- 2017
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Ingår i: Energy Procedia. - : Elsevier BV. - 1876-6102. ; 122, s. 1088-1093
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Konferensbidrag (refereegranskat)abstract
- Climate changes induce warmer climate with stronger and more frequent extreme events. Due to the uncertain nature of climate, accurate simulation of future conditions is impossible and a major challenge is the selection of climate data in the impact assessment. This work compares application of three climate data sets in an energy simulation of the EPFL campus: i) Regional Climate Models (RCM data), ii) statically representative RCM data, and iii) morphed data. The energy behavior of the campus is analyzed, including its future thermal behavior, as well as its dynamic hourly variation due to the climatic data. The objective of this paper is to understand and quantify the energy transition, from 2010 to 2100, by focusing on the thermal behavior of buildings, as well as their energy demand for heating and cooling. Results explain the difference between three cases, underling the important impact related to a sound selection of the weather data.
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| 2. |
- Gou, Shaoqing, et al.
(författare)
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Passive design optimization of newly-built residential buildings in Shanghai for improving indoor thermal comfort while reducing building energy demand
- 2018
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 169, s. 484-506
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Tidskriftsartikel (refereegranskat)abstract
- The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay's theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice.
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| 3. |
- 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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| 4. |
- Javanroodi, K., et al.
(författare)
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Quantifying the impacts of urban morphology on modifying microclimate conditions in extreme weather conditions
- 2021. - 1
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Ingår i: Journal of Physics: Conference Series : CISBAT 2021 Carbon-neutral cities - energy efficiency and renewables in the digital era 8-10 September 2021, EPFL Lausanne, Switzerland - CISBAT 2021 Carbon-neutral cities - energy efficiency and renewables in the digital era 8-10 September 2021, EPFL Lausanne, Switzerland. - : IOP Publishing. - 1742-6588. ; 2042
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Konferensbidrag (refereegranskat)abstract
- It is well-known that the morphology of urban areas modifies the variations of climate variables at microscale; known as microclimate conditions. The complexity of urban morphology can lead to undesired wind conditions or excessive air temperature; particularly in extreme weather conditions. This study attempts to quantify the impacts of urban morphology on the evolution of wind speed and air temperature at the urban canopy layer using Computational Fluid Dynamic (CFD) simulations. In this regard, three urban neighbourhoods are generated based on a novel urban morphology parameterization method and assessed in two extreme low and high wind conditions. Results showed that wind speed (up to 75%) and air temperature (up to 28%) at the microscale can get amplified or dampened in extreme conditions. A negative correlation was observed between wind speed and air temperature variations indicating a great potential to reduce outdoor air temperature through heat removal in urban canyons. The findings of the study are categorized based on the morphological parameters to present a series of design-based strategies for the newly-built urban neighbourhoods.
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| 5. |
- Mauree, D., et al.
(författare)
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A new framework to evaluate urban design using urban microclimatic modeling in future climatic conditions
- 2018
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Ingår i: Sustainability. - : MDPI AG. - 2071-1050. ; 10:4
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Tidskriftsartikel (refereegranskat)abstract
- Building more energy-efficient and sustainable urban areas that will both mitigate the effects of climate change and anticipate living conditions in future climate scenarios requires the development of new tools and methods that can help urban planners, architects and communities achieve this goal. In the current study, we designed a workflow that links different methodologies developed separately, to derive the energy consumption of a university school campus for the future. Three different scenarios for typical future years (2039, 2069, 2099) were run, as well as a renovation scenario (Minergie-P). We analyzed the impact of climate change on the heating and cooling demand of buildings and determined the relevance of taking into account the local climate in this particular context. The results from the simulations confirmed that in the future, there will be a constant decrease in the heating demand, while the cooling demand will substantially increase. Significantly, it was further demonstrated that when the local urban climate was taken into account, there was an even higher rise in the cooling demand, but also that a set of proposed Minergie-P renovations were not sufficient to achieve resilient buildings. We discuss the implication of this work for the simulation of building energy consumption at the neighborhood scale and the impact of future local climate on energy system design. We finally give a few perspectives regarding improved urban design and possible pathways for future urban areas.
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| 6. |
- Mauree, D., et al.
(författare)
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A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities
- 2019
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Ingår i: Renewable and Sustainable Energy Reviews. - : Elsevier BV. - 1879-0690 .- 1364-0321. ; 112, s. 733-746
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Tidskriftsartikel (refereegranskat)abstract
- The current climate change is calling for a drastic reduction of energy demand as well as of greenhouse gases. Besides this, cities also need to adapt to face the challenges related to climate change. Cities, with their complex urban texture and fabric, can be represented as a diverse ecosystem that does not have a clear and defined boundary. Multiple software tools that have been developed, in recent years, for assessment of urban climate, building energy demand, the outdoor thermal comfort and the energy systems. In this review, we, however, noted that these tools often address only one or two of these urban planning aspects. There is nonetheless an intricate link between them. For instance, the outdoor comfort assessment has shown that there is a strong link between biometeorology and architecture and urban climate. Additionally, to address the challenges of the energy transition, there will be a convergence of the energy needs in the future with an energy nexus regrouping the energy demand of urban areas. It is also highlighted that the uncertainty related to future climatic data makes urban adaptation and mitigation strategies complex to implement and to design given the lack of a comprehensive framework. We thus conclude by suggesting the need for a holistic interface to take into account this multi-dimensional problem. With the help of such a platform, a positive loop in urban design can be initiated leading to the development of low carbon cities and/or with the use of blue and green infrastructure to have a positive impact on the mitigation and adaptation strategies.
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| 7. |
- Perera, A. T. D., et al.
(författare)
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An integrated approach to design site specific distributed electrical hubs combining optimization, multi-criterion assessment and decision making
- 2017
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Ingår i: Energy. - : Elsevier BV. - 0360-5442. ; 134, s. 103-120
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Tidskriftsartikel (refereegranskat)abstract
- An integrated approach is presented in this study to design electrical hubs combining optimization, multi-criterion assessment and decision making. Levelized Energy Cost (LEC), Initial Capital Cost (ICC), Grid Integration Level (GI), Levelized CO2 emission (LCO2), utilization of renewable energy, flexibility of the system, loss of load probability (LOLP) are considered as criteria used to assess the design. The novel approach consists of several steps. Pareto analysis is conducted initially using 2D Pareto fronts to reduce the dimensions of the optimization problem. Subsequently, Pareto multi objective optimization is conducted considering EEC, GI and ICC which were identified as the best set of objective functions to represent the design requirements. Next, fuzzy TOPSIS and level diagrams are used for multi-criterion decision making (MCDM) considering the set of criteria and the boundary matrix that represents the design requirements of the application. Pareto analysis shows that 5D optimization problem can be reduced to a 3D optimization problem when considering LEC, ICC and GI as the objective functions. Finally, results obtained from the case study shows that the novel method can be used design distributed energy systems considering a set of criteria which is beyond the reach of Pareto optimization with different priority levels.
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| 8. |
- Perera, A. T. D., et al.
(författare)
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Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid
- 2017
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Ingår i: Applied Energy. - : Elsevier BV. - 1872-9118 .- 0306-2619. ; 190, s. 232-248
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Tidskriftsartikel (refereegranskat)abstract
- A paradigm change in energy system design tools, energy market, and energy policy is required to attain the target levels in renewable energy integration and in minimizing pollutant emissions in power generation. Integrating non-dispatchable renewable energy sources such as solar and wind energy is vital in this context. Distributed generation has been identified as a promising method to integrate Solar PV (SPV) and wind energy into grid in recent literature. Distributed generation using grid-tied electrical hubs, which consist of Internal Combustion Generator (ICG), non-dispatchable energy sources (i.e., wind turbines and SPV panels) and energy storage for providing the electricity demand in Sri Lanka is considered in this study. A novel dispatch strategy is introduced to address the limitations in the existing methods in optimizing grid-integrated electrical hubs considering real time pricing of the electricity grid and curtailments in grid integration. Multi-objective optimization is conducted for the system design considering grid integration level and Levelized Energy Cost (LEC) as objective functions to evaluate the potential of electrical hubs to integrate SPV and wind energy. The sensitivity of grid curtailments, energy market, price of wind turbines and SPV panels on Pareto front is evaluated subsequently. Results from the Pareto analysis demonstrate the potential of electrical hubs to cover more than 60% of the annual electricity demand from SPV and wind energy considering stringent grid curtailments. Such a share from SPV and wind energy is quite significant when compared to direct grid integration of non-dispatchable renewable energy technologies.
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| 9. |
- Perera, Amarasinghage Tharindu Dasun, et al.
(författare)
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Introducing reinforcement learning to the energy system design process
- 2020
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Ingår i: Applied Energy. - : Elsevier BV. - 1872-9118 .- 0306-2619. ; 262
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Tidskriftsartikel (refereegranskat)abstract
- Design optimization of distributed energy systems has become an interest of a wider group of researchers due the capability of these systems to integrate non-dispatchable renewable energy technologies such as solar PV and wind. White box models, using linear and mixed integer linear programing techniques, are often used in their design. However, the increased complexity of energy flow (especially due to cyber-physical interactions) and uncertainties challenge the application of white box models. This is where data driven methodologies become effective, as they demonstrate higher flexibility to adapt to different environments, which enables their use for energy planning at regional and national scale. This study introduces a data driven approach based on reinforcement learning to design distributed energy systems. Two different neural network architectures are used in this work, i.e. a fully connected neural network and a convolutional neural network (CNN). The novel approach introduced is benchmarked using a grey box model based on fuzzy logic. The grey box model showed a better performance when optimizing simplified energy systems, however it fails to handle complex energy flows within the energy system. Reinforcement learning based on fully connected architecture outperformed the grey box model by improving the objective function values by 60%. Reinforcement learning based on CNN improved the objective function values further (by up to 20% when compared to a fully connected architecture). The results reveal that data-driven models are capable to conduct design optimization of complex energy systems. This opens a new pathway in designing distributed energy systems.
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| 10. |
- Perera, Amarasinghage Tharindu Dasun, et al.
(författare)
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Linking Neighborhoods into Sustainable Energy Systems
- 2019
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Ingår i: Energy, Environment, and Sustainability. - Singapore : Springer Singapore. - 2522-8366. ; , s. 93-110
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Improving the energy efficiency and sustainability in the urban sector plays a vital role in the energy transition. Hence, it is important to consider promising ways to design sustainable urban energy hubs linking neighborhoods into energy systems. Improving the efficiency and sustainability of urban energy infrastructure is a process with multiple steps. This chapter presents the workflow that is required to be followed in this process. A brief overview about the methods that can be used to consider urban climate, urban simulation, and energy system design are presented in this chapter highlighting the crosslinks among these topics. Finally, the chapter presents the research gaps and promising areas to conduct future research.
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