Building energy simulation and its application for building performance optimization: A review of methods, tools, and case studies

Advances in Applied Energy, Journal Year: 2023, Volume and Issue: 10, P. 100135 - 100135

Published: April 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.

Language: Английский

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Data acquisition for urban building energy modeling: A review

Building and Environment, Journal Year: 2022, Volume and Issue: 217, P. 109056 - 109056

Published: April 8, 2022

Language: Английский

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AutoBPS: A tool for urban building energy modeling to support energy efficiency improvement at city-scale

Energy and Buildings, Journal Year: 2023, Volume and Issue: 282, P. 112794 - 112794

Published: Jan. 11, 2023

Language: Английский

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Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting

Energy and Buildings, Journal Year: 2022, Volume and Issue: 279, P. 112705 - 112705

Published: Dec. 5, 2022

Language: Английский

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Physically Consistent Neural Networks for building thermal modeling: Theory and analysis

Applied Energy, Journal Year: 2022, Volume and Issue: 325, P. 119806 - 119806

Published: Aug. 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.

Language: Английский

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Predicting solar radiation in the urban area: A data-driven analysis for sustainable city planning using artificial neural networking

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 100, P. 105042 - 105042

Published: Nov. 17, 2023

Language: Английский

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Urban building energy performance prediction and retrofit analysis using data-driven machine learning approach

Energy and Buildings, Journal Year: 2023, Volume and Issue: 303, P. 113768 - 113768

Published: Nov. 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.

Language: Английский

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A new approach for national-scale Building Energy Models based on Energy Performance Certificates in European countries: The case of Spain

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e25473 - e25473

Published: Feb. 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.

Language: Английский

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A roadmap for the implementation of a renewable energy community

Heliyon, Journal Year: 2024, Volume and Issue: 10(7), P. e28269 - e28269

Published: March 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.

Language: Английский

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Evaluation of the impact of input uncertainty on urban building energy simulations using uncertainty and sensitivity analysis

Applied Energy, Journal Year: 2022, Volume and Issue: 311, P. 118691 - 118691

Published: Feb. 16, 2022

The energy consumption of cities is increasing fast due to growing global population and rapid urbanization. Urban Building Energy Models (UBEMs) are promising tools simulate the demand buildings under different urban scenarios. Nowadays, major barriers effective use UBEMs uncertainty related their input parameters lack good-quality, open data. latter make deterministic UBEM simulations unreliable, calibration approaches unsuitable for most in world. present work proposes combine physics-based with Uncertainty Sensitivity Analysis on main using aggregated data from regional/national statistics. proposed procedure selects influential characterizes through Forward obtain stochastic load profiles space heating cooling. method was first tested against hourly thermal power metered a heterogeneous sample Verona (Italy). average profile obtained significantly improved compared deterministic, archetype-based terms needs peak loads. overestimation residential reduced 80% 25%, deviation calculation drops 18% 10%. simulation then applied district Milan (Italy), including more than 600 buildings, resulting similar variations. Overall, results demonstrate that considering operational, geometrical physical utmost importance reliable simulations.

Language: Английский

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