Applied Energy, Год журнала: 2025, Номер 383, С. 125342 - 125342
Опубликована: Янв. 17, 2025
Язык: Английский
Applied Energy, Год журнала: 2025, Номер 383, С. 125342 - 125342
Опубликована: Янв. 17, 2025
Язык: Английский
Advances in Applied Energy, Год журнала: 2023, Номер 10, С. 100135 - 100135
Опубликована: Апрель 6, 2023
As one of the most important and advanced technology for carbon-mitigation in building sector, performance simulation (BPS) has played an increasingly role with powerful support energy modelling (BEM) energy-efficient designs, operations, retrofitting buildings. Owing to its deep integration multi-disciplinary approaches, researchers, as well tool developers practitioners, are facing opportunities challenges during application BEM at multiple scales stages, e.g., building/system/community levels planning/design/operation stages. By reviewing recent studies, this paper aims provide a clear picture how performs solving different research questions on varied phase spatial resolution, focus objectives frameworks, methods tools, applicability transferability. To guide future applications performance-driven management, we classified current trends into five topics that span through stages levels: (1) Simulation design new retrofit design, (2) Model-based operational optimization, (3) Integrated using data measurements digital twin, (4) Building supporting urban planning, (5) Modelling building-to-grid interaction demand response. Additionally, recommendations discussed, covering potential occupancy behaviour modelling, machine learning, quantification model uncertainties, linking monitoring systems.
Язык: Английский
Процитировано
153Building and Environment, Год журнала: 2022, Номер 217, С. 109056 - 109056
Опубликована: Апрель 8, 2022
Язык: Английский
Процитировано
110Energy and Buildings, Год журнала: 2023, Номер 282, С. 112794 - 112794
Опубликована: Янв. 11, 2023
Язык: Английский
Процитировано
90Energy and Buildings, Год журнала: 2022, Номер 279, С. 112705 - 112705
Опубликована: Дек. 5, 2022
Язык: Английский
Процитировано
89Applied Energy, Год журнала: 2022, Номер 325, С. 119806 - 119806
Опубликована: Авг. 19, 2022
Due to their high energy intensity, buildings play a major role in the current worldwide transition. Building models are ubiquitous since they needed at each stage of life buildings, i.e. for design, retrofitting, and control operations. Classical white-box models, based on physical equations, bound follow laws physics but specific design underlying structure might hinder expressiveness hence accuracy. On other hand, black-box better suited capture nonlinear building dynamics thus can often achieve accuracy, require lot data not physics, problem that is particularly common neural network (NN) models. To counter this known generalization issue, physics-informed NNs have recently been introduced, where researchers introduce prior knowledge ground them avoid classical NN issues. In work, we present novel architecture, dubbed Physically Consistent (PCNN), which only requires past operational no engineering overhead, including linear module running parallel NN. We formally prove such networks physically consistent – by even unseen with respect different inputs temperatures outside neighboring zones. demonstrate performance case study, PCNN attains an accuracy up 40% than physics-based resistance-capacitance model 3-day long prediction horizons. Furthermore, despite constrained structure, PCNNs attain similar validation data, overfitting training less retaining tackle issue.
Язык: Английский
Процитировано
80Energy and Buildings, Год журнала: 2023, Номер 303, С. 113768 - 113768
Опубликована: Ноя. 22, 2023
Stakeholders such as urban planners and energy policymakers use building performance modeling analysis to develop strategic sustainable plans with the aim of reducing consumption emissions from built environment. However, inconsistent data lack scalable models create a gap between traditional planning practices. An alternative approach is conduct large-scale usage survey, which time-consuming. Similarly, existing studies rely on machine learning or statistical approaches for calculating performance. This paper proposes solution that employs data-driven predict residential buildings, using both ensemble-based end-use demand segregation methods. The proposed methodology consists five steps: collection, archetype development, physics-based parametric modeling, analysis. devised tested Irish stock generates synthetic dataset one million buildings through 19 identified vital variables four archetypes. As part process, study implemented an method, including heating, lighting, equipment, photovoltaic, hot water, at scale. Furthermore, model's enhanced by employing approach, achieving 91% accuracy compared approach's 76%. Accurate prediction enables stakeholders, planners, make informed decisions when retrofit measures.
Язык: Английский
Процитировано
54Sustainable Cities and Society, Год журнала: 2023, Номер 100, С. 105042 - 105042
Опубликована: Ноя. 17, 2023
Язык: Английский
Процитировано
51Heliyon, Год журнала: 2024, Номер 10(3), С. e25473 - e25473
Опубликована: Фев. 1, 2024
Urban Building Energy Models (UBEMs) are useful instruments to know the energy consumption of building stocks at urban and national levels. UBEMs can be classified into different types subtypes. The current detailed physics-based bottom-up a scale play crucial role in assessing efficiency defining improvement strategies. These models heavily rely on archetypes simulations, demanding significant computational resources. We propose here new type national-scale UBEM based Performance Certificates (EPCs), other open big data, which has advantage that it automatically updated, short time, with standard computer means. In this paper, we define methodology build EPC-based UBEM. have checked model for case Spain generated updated less than 6 h computer, generates results match official data more 98 % four indicators. contains information about 10,939,801 buildings Spain, out 1,202,708 EPCs. allows us map analyse country by integrating multiple variables nature, such as geographical (Autonomous Community, municipality, municipality), physical (area, number floors, date construction), use-related (main use each its units), energy-related (climate zone, class, consumption, CO2 emissions). proven development some indicators measure progress decarbonisation trajectories whose will become mandatory European Member States soon.
Язык: Английский
Процитировано
20Heliyon, Год журнала: 2024, Номер 10(7), С. e28269 - e28269
Опубликована: Март 22, 2024
Environmental problems due to climate change, that have been affecting our planet for years, are the main issues which prompted European Union establish ambitious target of achieving carbon neutrality by 2050. This occurrence encouraged all Member States undergo significant changes their energy sectors, favouring extensive use renewable sources. In this scenario, introduced Renewable Energy Communities, innovative systems based on a new model production, consumption and sharing, guaranteeing environmental, economic, social benefits. The objective paper is twofold: firstly, examine regulatory framework and, secondly, present standardized procedure implementation Community, an aspect not yet covered in scientific literature. roadmap includes four phases: feasibility study involving analysis end users' general assessment; aggregation members as producers, consumers or prosumers forming legal entity, considering different funding opportunities; operating phase, plant construction project validation national authorities; technical economic management phase. dynamic structure allows adjustments accommodate contexts, member typologies aim.
Язык: Английский
Процитировано
20Energy and Buildings, Год журнала: 2024, Номер 319, С. 114500 - 114500
Опубликована: Июль 3, 2024
Язык: Английский
Процитировано
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