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Energies
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Energy Efficiency of Buildings at the District Scale
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Energy Efficiency of Buildings at the District Scale

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "G: Energy and Buildings".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 16484

Special Issue Editors

Prof. Dr. Benoit Delinchant

E-Mail Website
Guest Editor
G2Elab, Grenoble INP, CNRS, Université Grenoble Alpes, F-38000 Grenoble, France
Interests: optimal design and operation of energy systems for building and districts; modeling (knowledge based, numerical and data-driven); (co-)simulation; multilevel optimization; uncertainties and robustness
Prof. Dr. Francois Garde

E-Mail Website
Guest Editor
PIMENT laboratory, 117 avenue Général Ailleret, Campus universitaire Sud. 97430 Le Tampon, La Réunion
Interests: design of low consumption and net zero energy buildings and neighborhoods in tropical environments; renewable energy applied to the building; thermal comfort and user behavior

Special Issue Information

Dear Colleagues,

The major challenges in reducing fossil fuel consumption involve the development of innovative energy-efficient solutions at the scale of buildings and districts. In addition to their efficiency, these solutions must also guarantee operational resilience and maximum environmental sustainability. Many topics are to be considered, such as the optimization of passive design and the reduction of the urban heat island effect, the introduction of decentralized renewable energy, the recovery of waste energy, and the introduction of storage, pooling, and interaction between different energy carriers (electricity, heat, gas). The increasing complexity of the systems also requires optimized energy management strategies, including data-based forecasting, as well as methodologies to aid the overall design with multiple stakeholders and communities.

Prof. Dr. Benoit Delinchant
Prof. Dr. Francois Garde
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

  • Low carbon building design
  • Energy system design
  • Energy management system
  • Passive design of districts
  • Net zero energy communities
  • Urban microclimate
  • Life cycle assessment
  • Smart grids and buildings
  • Methodology and tools
  • Optimization
  • Uncertainties
  • Monitoring
  • Data forecasting

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Published Papers (5 papers)

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Research

19 pages, 5717 KiB  
Article
A Practical Approach to Launch the Low-Cost Monitoring Platforms for Nearly Net-Zero Energy Buildings in Vietnam
by Thi Tuyet Hong VU, Benoit DELINCHANT, Anh Tuan PHAN, Van Cong BUI and Dinh Quang NGUYEN
Energies 2022, 15(13), 4924; https://doi.org/10.3390/en15134924 - 5 Jul 2022
Cited by 4 | Viewed by 3380
Abstract
Buildings with solar rooftops have become vital objects in the energy transition in Vietnam. In this context, the demand for research on energy management solutions to use energy efficiently and increase PV energy absorption capacity is rising. In this paper, we present a [...] Read more.
Buildings with solar rooftops have become vital objects in the energy transition in Vietnam. In this context, the demand for research on energy management solutions to use energy efficiently and increase PV energy absorption capacity is rising. In this paper, we present a practical route to developing a low-cost monitoring platform to meet the building energy management in the country. First, our project built a monitoring architecture with high-density wireless sensors in an office building in Vietnam. Next, we discussed the influence of significant obstacles such as technical issues, users, and cost on the resilience and reliability of the monitoring system. Then, we proposed essential solutions for data quality improvement by testing sensors, detecting wireless sensor network errors, and compensating for data losses by embedding machine learning. We found the platform’s potential in developing a rich database of building characteristics and occupants. Finally, we proposed plans exploiting the data to reduce wasted energy in equipment operation, change user behaviors, and increase auto-consumption PV power. The effectiveness of the monitoring platform was an approximate 62% energy reduction in the first year. The results are a cornerstone for implementing advanced research as modeling and real-time optimal control toward nearly zero-energy buildings. Full article
(This article belongs to the Special Issue Energy Efficiency of Buildings at the District Scale)
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22 pages, 726 KiB  
Article
Sizing and Management of an Energy System for a Metropolitan Station with Storage and Related District Energy Community
by Mircea Stefan Simoiu, Ioana Fagarasan, Stephane Ploix and Vasile Calofir
Energies 2021, 14(18), 5997; https://doi.org/10.3390/en14185997 - 21 Sep 2021
Cited by 8 | Viewed by 2161
Abstract
Future renewable energy communities will reshape the paradigm in which we design and control efficient power systems at the district level. In this manner, the focus will be fundamentally shifted towards sustainable related concepts such as self-consumption, self-sufficiency and net energy exchanged with [...] Read more.
Future renewable energy communities will reshape the paradigm in which we design and control efficient power systems at the district level. In this manner, the focus will be fundamentally shifted towards sustainable related concepts such as self-consumption, self-sufficiency and net energy exchanged with the grid. In this context, the paper presents a novel approach for optimally designing and controlling the photovoltaic plant and energy storage systems for a metro station in order to increase collective self-consumption and self-sufficiency at the district level. The methodology considers a community of several households connected to a subway station and focuses on the interaction between energy sources and consumers. Furthermore, the optimal solution is determined by using a Mixed Integer Linear Programming Approach, and the impact of different configurations on the overall district benefit is investigated by using several simulation scenarios. The work presents a detailed case study to underline the benefits and flexibility offered by the energy storage system in comparison with a scenario involving only a photovoltaic plant. Full article
(This article belongs to the Special Issue Energy Efficiency of Buildings at the District Scale)
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28 pages, 5489 KiB  
Article
Integration of Open-Source URBANopt and Dragonfly Energy Modeling Capabilities into Practitioner Workflows for District-Scale Planning and Design
by Tanushree Charan, Christopher Mackey, Ali Irani, Ben Polly, Stephen Ray, Katherine Fleming, Rawad El Kontar, Nathan Moore, Tarek Elgindy, Dylan Cutler, Mostapha Sadeghipour Roudsari and David Goldwasser
Energies 2021, 14(18), 5931; https://doi.org/10.3390/en14185931 - 18 Sep 2021
Cited by 26 | Viewed by 5394
Abstract
High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There [...] Read more.
High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There is a need for energy modeling tools that connect 3D Computer-Aided Design (CAD) platforms to simulation engines, enabling detailed energy analysis of districts within the workflows and tools used by practitioners. This paper introduces the Dragonfly and URBANoptTM combined toolset that supports the creation of urban models from a range of geometry formats typically used by designers and planners, and provides an integrated pathway to simulate district-scale energy systems. The toolset is piloted by a global architecture and master planning firm to evaluate several key urban-scale technical questions for the design of a district in Chicago. The findings indicate that, while energy savings can be achieved through traditional architectural studies and enhancements to individual building efficiency, the modeling toolset helps identify additional savings and insights that can be achieved when considering district-scale energy systems. Finally, this study demonstrates how the Dragonfly/URBANopt toolset can integrate with master planning workflows, thereby enabling an iterative performance-based design process. Full article
(This article belongs to the Special Issue Energy Efficiency of Buildings at the District Scale)
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30 pages, 3047 KiB  
Article
OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale
by Sacha Hodencq, Mathieu Brugeron, Jaume Fitó, Lou Morriet, Benoit Delinchant and Frédéric Wurtz
Energies 2021, 14(18), 5928; https://doi.org/10.3390/en14185928 - 18 Sep 2021
Cited by 13 | Viewed by 2516
Abstract
Energy modelling is key in order to face the challenges of energy transition. There is a wide variety of modelling tools, depending on their purpose or study phase. This article summarises their main characteristics and highlights ones that are relevant when it comes [...] Read more.
Energy modelling is key in order to face the challenges of energy transition. There is a wide variety of modelling tools, depending on their purpose or study phase. This article summarises their main characteristics and highlights ones that are relevant when it comes to the preliminary design of energy studies at district scale. It introduces OMEGAlpes, a multi-carrier energy modelling tool to support stakeholders in the preliminary design of district-scale energy systems. OMEGAlpes is a Mixed-Integer Linear Programming (MILP) model generation tool for optimisation. It aims at making energy models accessible and understandable through its open-source development and the integration of energy stakeholders and their areas of responsibility into the models. A library of use cases developed with OMEGAlpes is presented and enables the presentation of past, current, and future development with the tool, opening the way for future developments and collaborations. Full article
(This article belongs to the Special Issue Energy Efficiency of Buildings at the District Scale)
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26 pages, 9946 KiB  
Article
Bayesian Inference of Dwellings Energy Signature at National Scale: Case of the French Residential Stock
by Nils Artiges, Simon Rouchier, Benoit Delinchant and Frédéric Wurtz
Energies 2021, 14(18), 5651; https://doi.org/10.3390/en14185651 - 8 Sep 2021
Cited by 6 | Viewed by 1997
Abstract
Cities take a central place in today’s energy landscape. Urban Buildings Energy Modeling (UBEM) is identified as a promising approach for energy planning and optimization in cities and districts. It generally relies on the use of Building Archetypes, i.e., simplified deterministic models for [...] Read more.
Cities take a central place in today’s energy landscape. Urban Buildings Energy Modeling (UBEM) is identified as a promising approach for energy planning and optimization in cities and districts. It generally relies on the use of Building Archetypes, i.e., simplified deterministic models for categorized building typologies. However, this implies large assumptions which may accumulate and induce significant bias on energy consumption estimates. In this work, we address this issue with static stochastic models whose parameters are inferred over national thermo-energy data using Bayesian Inference. We analyze inference results and validate them with a panel of standard indicators. Then, we provide comparative results with deterministic building archetypes and stock data from the TABULA European project. Comparisons between heat loss coefficients show relative coherence between building categories, but highlight some significant bias between both approaches. This bias is also shown in the comparative result of a Monte Carlo simulation using inferred stochastic models for a 10331 dwellings stock. In conclusion, inferred stochastic models show interesting insights over the French dwellings stock and potential for district energy simulation. All code and data involved in this study are released in an open repository. Full article
(This article belongs to the Special Issue Energy Efficiency of Buildings at the District Scale)
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