A modular optimisation model for reducing energy consumption in large scale building facilities

Petri, Ioan; Li, Haijiang; Rezgui, Yacine; Yang, Chunfeng; Yüce, Barış; Jayan, Bejay

doi:10.1016/j.rser.2014.07.044

Cited by 44 publications

(29 citation statements)

References 14 publications

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“…Although according to some thermal regulations the energy consumption of a building is expected to not exceed a given limit, the real energy performance is usually lower. One means to reduce the gap between prediction and reality is to improve the entire process, from the early design phase to the operation phase [8,9]. Practitioners who use BIM during the design phase, the construction phase or the maintenance phase will contribute to improving the quality of the building's performance.…”

Section: Bim For Energy Efficiency In Buildingsmentioning

confidence: 99%

“…BIM has a number of socio-technological advantages not only at the technological level, but also the process level, and can complement the way that architectural design artefacts are created, but also can profoundly change the collaborative process associated with the act of building. As the construction industry is facing increased pressure from regulations calling for significant gains in energy efficiency, increased economic pressure and competition, and a dramatic evolution of working culture and practices, BIM can represent a gamechanging factor that would support the transition to more energy and cost-efficient practices [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Energy Efficiency in Operating Built Environment Assets through Building Information Modeling: A Case Study

et al. 2017

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Abstract:Reducing carbon emissions and addressing environmental policies in the construction domain has been intensively explored with solutions ranging from energy efficiency techniques with building informatics to user behavior modelling and monitoring. Such strategies have managed to improve current practices in managing buildings, however decarbonizing the built environment and reducing the energy performance gap remains a complex undertaking that requires more comprehensive and sustainable solutions. In this context, building information modelling (BIM), can help the sustainability agenda as the digitalization of product and process information provides a unique opportunity to optimize energy-efficiency-related decisions across the entire lifecycle and supply chain. BIM is foreseen as a means to waste and emissions reduction, performance gap minimization, in-use energy enhancements, and total lifecycle assessment. It also targets the whole supply chain related to design, construction, as well as management and use of facilities, at the different qualifications levels (including blue-collar workers). In this paper, we present how building information modelling can be utilized to address energy efficiency in buildings in the operation phase, greatly contributing to achieving carbon emissions targets. In this paper, we provide two main contributions: (i) we present a BIM-oriented methodology for supporting building energy optimization, based on which we identify few training directions with regards to BIM, and (ii) we provide an application use case as identified in the European research project "Sporte2" to demonstrate the advantages of BIM in energy efficiency with respect to several energy metrics.

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Section: Bim For Energy Efficiency In Buildingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimizing Energy Efficiency in Operating Built Environment Assets through Building Information Modeling: A Case Study

et al. 2017

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“…Moreover, a simulation system-based solution requires continuous calibration processes and long processing times to achieve energy saving objectives. An ANN-based energy management system is more efficient compared to a simulation based system and can easily reflect and factor in changes through an adequate learning process [12][13].…”

Section: Artificial Neural Network For Building Energy Managementmentioning

confidence: 99%

“…Options to speed up the calculation include simplifying the model or using high throughput computing techniques. A preferred option however is to use artificial intelligence methods such as neural network with historical or simulated data sets [12][13].…”

Section: Introductionmentioning

confidence: 99%

ANN–GA smart appliance scheduling for optimised energy management in the domestic sector

Yüce

Rezgui

Mourshed

2016

Energy and Buildings

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“…Esta similaridade é possível devido a adequação do método proposto ao protocolo International Performance Measurement and Verification Protocol (IPMVP) [26], que também é utilizado pela Norma ISO 50001. IPMVP consiste em um conjunto de termos e boas práticas, que visam padronizar e quantificar os resultados sobre eficiência de uso de recursos naturais, como a energia elétrica, possibilitando uma maior confiabilidade na interpretação dos dados coletados [27]. O protocolo está organizado em quatro opções de medição e avaliação (A, B, C e D), adequadas às características de cada PEE [28].…”

Section: Método De Harmonização Meharcenunclassified

MeHarCEn: Um Método de Harmonização do Consumo de Energia em Data Centers

Camargo

Miers

Pillon

et al. 2017

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Resumo: O consumo energético controlado e eficiente é um desafio enfrentado diariamente pelos gestores de Data Centers (DCs) de pequeno, médio e grande porte. A literatura especializada e técnica define diversos guias, equipamentos e mecanismos para essa finalidade. Entretanto, a aplicação combinada dessas soluções é uma tarefa complexa, que, em muitos casos, requer um elevado investimento financeiro. Nesse contexto, o presente trabalho propõe MeHarCEn, uma iniciativa para gerenciamento combinado e harmônico do consumo de energia em DCs. MeHarCEn não depende de soluções proprietárias e pode ser adaptado a DCs com configurações distintas. Aplicado a um estudo de caso, em um DC de pequeno porte, o MeHarCEn resulta em uma economia de 52, 7% no consumo de energia com climatização.Abstract: Controlled and efficient power consumption is a challenge faced daily by small, medium, and large data center (DC) administrators. Specialized and technical literature defines several guides, equipment, and mechanisms for this purpose. However, the combined application of these solutions is a complex task, which in several cases implies on high financial investment. In this context, we present MeHarCEn, a method for combined and harmonic management of energy consumption in DCs. MeHarCEn does not depend on proprietary solutions and can be adapted on DC's based on different configurations. Applied to a case study, a small DC, MeHarCEn results in a savings of 52.7% in energy consumption with air conditioning.Palavras-chave: Data centers, eficiência energética, gerenciamento de data center.

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A modular optimisation model for reducing energy consumption in large scale building facilities

Cited by 44 publications

References 14 publications

Optimizing Energy Efficiency in Operating Built Environment Assets through Building Information Modeling: A Case Study

Optimizing Energy Efficiency in Operating Built Environment Assets through Building Information Modeling: A Case Study

ANN–GA smart appliance scheduling for optimised energy management in the domestic sector

MeHarCEn: Um Método de Harmonização do Consumo de Energia em Data Centers

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