Design of energy efficiency retrofitting projects for districts based on performance optimization of District Performance Indicators calculated through simulation models

Hernández, Gema; Serna, Víctor; García-Fuentes, Miguel Á.

doi:10.1016/j.egypro.2017.07.386

Cited by 9 publications

(3 citation statements)

References 2 publications

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“…The intensity of importance is therefore represented by a scale of numbers, where 1 shows equal importance, 3: moderate importance, 5: strong importance, 7: very strong or demonstrated importance, and 9: extreme importance [27].…”

Section: Turning Subjective Information Into a Mathematical Problemmentioning

confidence: 99%

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

García-Fuentes¹,

Álvarez²,

Serna³

et al. 2019

Sustainability

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The evident need for improving the existing building stock still suffers from important barriers, such as the fragmentation of the value chain, the lack of information regarding some solutions, and the lack of confidence with respect to energy savings, which prevent unlocking investments, and the difficult communication among stakeholders. Therefore, new processes based on exploiting the potential of existing and new tools are required. In this framework, the OptEEmAL project has developed a tool that integrates stakeholders, data and tools in order to ease the process of designing energy efficient retrofitting projects at building and district scale. This tool works around an optimisation framework in order to evaluate, compare and optimise candidate retrofitting scenarios against a set of indicators showing the performance of the district. This evaluation and optimisation method is based on aggregating indicators through transforming the priorities of stakeholders into a mathematical weighting scheme, which makes it possible to provide scenarios within their expectations. Therefore, the generation of these scenarios is driven by their design parameters, being thus flexible and adapted to their needs. This paper shows the implementation of this tool and specifically 3 different prioritisation schemes, analysing how they impact into the decision making process and selection of the retrofitting strategy.Buildings account for approximately 40% of energy consumption and 36% of GHG emissions in the context of the EU [1]. When analysing the stock of existing buildings, around 30% of the building stock is more than 50 years old [2] and almost 75% is energy inefficient [3,4]. The implications of this energy inefficiency not only result in an energy and environmental cost, but also provoke other impacts, such as health problems due to the low levels of comfort within these buildings [5]. It is then imperative to focus on upgrading an ageing building stock, whose current renovation rates are low, at~1.2%. To achieve these targets, this rate should increase to 3% [6].On the other hand, the retrofitting market is quite fragmented, with multiple stakeholders with different and often conflicting interests. This is mirrored in the communication and information exchanges between them. This strong barrier is added to others, such as the lack of knowledge of some technologies among construction professionals, the varying ambition of performance requirements present within regulations, lack of awareness, and uncertainty as to the expected savings, which make

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Section: Turning Subjective Information Into a Mathematical Problemmentioning

confidence: 99%

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

García-Fuentes¹,

Álvarez²,

Serna³

et al. 2019

Sustainability

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“…This process (see Figure 3) represents the core element of the platform, where scenarios are generated from different combinations of ECMs and the DPIs are calculated by launching simulations with external tools. These results are evaluated to be able to have as an outcome a series of optimised scenarios and the data generated along this process (García-Fuentes, et al, 2018) (Hernández, et al, 2017).…”

Section: Scenarios Generation and Optimisation Processmentioning

confidence: 99%

OptEEmAL: IT-Supported design tool for the generation of optimised energy retrofitting scenarios at district level

Martín¹,

Serna²,

Álvarez³

et al. 2019

Proceedings of the 2019 European Conference on Computing in Construction

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The EU strategies to reduce the carbon emissions highlight the importance of renovating the existing building stock as one of the major contributing sectors to these undesired emissions to the atmosphere. The existing practices to design energy efficient retrofitting projects are still too time consuming, unprecise and provoke, therefore, a lack of trust within the sector; especially to investors. There is a need to improve these practices through reducing the errors and the time required to evaluate retrofitting alternatives in order to select those most appropriate according to the stakeholders' priorities. In order to give an answer to this challenge, the EU funded project OptEEmAL has designed and deployed an integrated platform that delivers automatically some of the steps that belong to this process reducing thus time, errors and therefore costs, which will lead to increasing efficiency and creating confidence among the stakeholders.

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“…Por lo tanto, la intensidad de la importancia está representada por una escala de números, donde 1 muestra igual importancia, 3: importancia moderada, 5: importancia fuerte, 7: importancia muy fuerte o demostrada, y 9: importancia extrema [132].…”

Section: Transformación De Información Subjetiva En Un Problema Matemáticounclassified

Aplicación de técnicas de toma de decisión multicriterio a la rehabilitación energética de áreas urbanas residenciales

Fuentes¹,

Ángel²

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Tabla 24. MAES propuestas para el caso de estudio. Código MAES Descripción AC.DE.BO.CD.01 Caldera de condensación de diésel (26 kW capacidad nominal) AC.DE.BO.CD.02 Caldera de condensación de diésel (35 kW capacidad nominal) AC.DE.BO.CD.03 Caldera de condensación de diésel (44 kW capacidad nominal) AC.DE.BO.CD.04 Caldera de condensación de diésel (58 kW capacidad nominal) AC.DE.BO.CD.05 Caldera de condensación de diésel (73 kW capacidad nominal) AC.DE.BO.NG.01 Caldera de gas natural (15 kW capacidad nominal) AC.DE.BO.NG.02 Caldera de gas natural (38 kW capacidad nominal) AC.DE.BO.NG.03 Caldera de gas natural (53 kW capacidad nominal) AC.DE.BO.NG.04 Caldera de gas natural (143 kW capacidad nominal) AC.DE.BO.NG.05 Caldera de gas natural (239 kW capacidad nominal) AC.DE.BO.NG.06 Caldera de gas natural (384 kW capacidad nominal) AC.DE.BO.NG.01 Caldera de condensación de gas natural (18 kW capacidad nominal) AC.DE.BO.CG.02 Caldera de condensación de gas natural (34 kW capacidad nominal) AC.DE.BO.CG.03 Caldera de condensación de gas natural (49 kW capacidad nominal) AC.DE.BO.CG.04 Caldera de condensación de gas natural (97 kW capacidad nominal) AC.DE.BO.CG.05 Caldera de condensación de gas natural (208 kW capacidad nominal) AC.DE.BO.CG.06 Caldera de condensación de gas natural (369 kW capacidad nominal) PA.FA.EX.CS.01 Sistema de aislamiento térmico por el exterior -EPS 50mm PA.FA.EX.CS.02 Sistema de aislamiento térmico por el exterior -EPS 100mm PA.FA.EX.CS.03 Sistema de aislamiento térmico por el exterior -EPS 120mm PA.FA.EX.CS.04 Sistema de aislamiento térmico por el exterior -EPS 150mm PA.FA.EX.CS.05 Sistema de aislamiento térmico por el exterior -EPS 200mm PA.FA.EX.CS.06 Sistema de aislamiento térmico por el exterior -EPS 250mm PA.FA.EX.CS.07 Sistema de aislamiento térmico por el exterior -Lana Mineral 80mm PA.FA.EX.CS.08 Sistema de aislamiento térmico por el exterior -Lana Mineral 100mm PA.FA.EX.CS.09 Sistema de aislamiento térmico por el exterior -Lana Mineral 120mm PA.FA.EX.CS.10 Sistema de aislamiento térmico por el exterior -XPS 100mm PA.FA.EX.CS.11 Sistema de aislamiento térmico por el exterior -XPS 120mm PA.OP.DG.DE.01 Doble acristalamiento con marco de aluminio PA.OP.DG.DE.02 Doble acristalamiento con marco de PVC con tres cámaras PA.OP.DG.DE.03 Doble acristalamiento con marco de PVC con cinco cámaras PA.RO.PI.IN.01 Aislamiento interno en cubierta inclinada -Lana mineral 40mm PA.RO.PI.IN.02 Aislamiento interno en cubierta inclinada -Lana mineral 60mm PA.RO.PI.IN.03 Aislamiento interno en cubierta inclinada -Lana mineral 80mm PA.RO.PI.IN.04 Aislamiento interno en cubierta inclinada -Lana mineral 100mm PA.RO.TS.CI.01 Aislamiento en forjado de última planta -Lana mineral 100mm Código MAES Descripción PA.RO.TS.CI.02 Aislamiento en forjado de última planta -Lana mineral 150mm PA.RO.TS.CI.03 Aislamiento en forjado de última planta -Lana mineral 200mm PA.RO.TS.CI.04 Aislamiento en forjado de última planta -Lana mineral 250mm CO.DE.PL.LF.01 Control de seguimiento de cargas CO.DE.PL.TV.01 Válvulas termostáticas en r...

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Design of energy efficiency retrofitting projects for districts based on performance optimization of District Performance Indicators calculated through simulation models

Cited by 9 publications

References 2 publications

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

Integration of Prioritisation Criteria in the Design of Energy Efficient Retrofitting Projects at District Scale: A Case Study

OptEEmAL: IT-Supported design tool for the generation of optimised energy retrofitting scenarios at district level

Aplicación de técnicas de toma de decisión multicriterio a la rehabilitación energética de áreas urbanas residenciales

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