An approach for an educational building stock energy retrofits through life-cycle cost optimization

Yılmaz, Yiğit; Oral, Gül Koçlar

doi:10.1080/00038628.2018.1447438

Cited by 17 publications

(14 citation statements)

References 19 publications

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“…Then, energy effective façade parameters were designated as indicators to be included in the optimization. In addition, ranges for the values of the façade parameters were determined through analysis of the base case and experience from a previous study, 32 so as to restrict the number of scenarios in the optimization. Energy and LCC calculations were conducted via the EnergyPlus simulation tool integrated with GenOpt for the optimization.…”

Section: Methodsmentioning

confidence: 99%

“…Among the local market products, rock wool thermal insulation material with a density of 150 kg/m 3 was selected as the case insulation material due to its thermal, environmental and fire safety performance. 32 While determining the range of thermal insulation thicknesses for optimization, the minimum thickness level was assigned according to the limit values for the second climate region of Turkey defined in TS 825:2008. 33 The maximum thickness of the thermal insulation was determined in accordance with previous studies.…”

Section: Application To Base Casementioning

confidence: 99%

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Life cycle cost optimization of building façade: A social housing case

Yılmaz

2019

Indoor and Built Environment

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In this paper, a common social housing archetype design was studied in order to improve the energy and cost performance. The focus is on evaluating the effects of some parameters of the design of the façade in particular: the size of the windows and the optical and thermo-physical properties of the components. The aim is to obtain cost optimal energy efficient scenarios in accordance with the Recast of Energy Performance of Buildings Directive (EPBD Recast) by determining efficient thicknesses of the insulation for the exterior walls and efficient window sizes and types of glazing for each orientation, simultaneously. The parameters of the façade are optimized in order to obtain the dominant values and ranges in terms of energy and cost. There are remarkable differences in the dominant options for the thickness of the insulations, as well as the type and size of windows: they depend on whether they have a north, south and east–west orientation. The decision makers should design each façade in dependence on its orientation to determine its optimal optical and thermo-physical properties in terms of its cost and its consumption of energy. A reduction by approximately 5% in the life cycle cost and 17% in the primary energy use was achieved through the optimization of the base case.

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Section: Methodsmentioning

confidence: 99%

Section: Application To Base Casementioning

confidence: 99%

Life cycle cost optimization of building façade: A social housing case

Yılmaz

2019

Indoor and Built Environment

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“…They provide measurable and straightforward parameters to quantify the cost effectiveness of each design option, and they allow for the evaluation of economic feasibility of the interventions. Economic assessment techniques, such as the Life Cycle Cost (LCC) estimation [28,[214][215][216][217][218][219] and the Discounted Cash Flow (DCF) analysis [220][221][222], rely on the same principles that property investment valuation is based on. Both LCC and DCF analyses allow the consideration of the time value of money [223], sharing the economic principle stating that future values need to be discounted back to the present in order to be compared, as described in [224,225].…”

Section: Common Decision Making Criteria In Building Portfoliosmentioning

confidence: 99%

“…Equally, in [26], the selection of the best set of actions was found through an optimization analysis, minimizing the LCC while maximizing primary energy savings. In [28], a cost-optimal approach was applied to an educational building asset in Istanbul in order to define the most convenient scenario in under the double perspective of energy and costs. In [87] the authors illustrated a cost-optimal approach to schedule maintenance and retrofit actions on a building portfolio owned by the Gothenburg municipal building company, in Sweden, with the aim of forecasting and optimizing the timing of efficiency measures.…”

Section: Cost-optimal Strategy In Building Portfoliosmentioning

confidence: 99%

Energy Retrofit in European Building Portfolios: A Review of Five Key Aspects

2020

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The research about energy efficiency in buildings has exponentially increased during the last few years. Nevertheless, both research and practice still cannot rely on complete methodologies tailored for building portfolios as a whole, because the attention has always been drawn to individual premises. Yet, energy efficiency analyses need to go beyond the single building perspective and incorporate strategic district approaches to optimize the retrofit investment. For this purpose, several aspects should be considered simultaneously, and new methodologies should also be promoted. Therefore, this paper aims to discuss energy retrofit campaigns in building portfolios, drawing an exhaustive and updated review about the challenge of jumping from the single-building perspective to a stock-based analysis. This research discusses the publications available on the topic from five key aspects that are all essential steps in achieving a complete and reliable study of energy efficiency at a portfolio level. They are energy modelling and assessment, energy retrofit design, decision-making criteria assessment, optimal allocation of (financial) resources and risk valuation. This review, therefore, advocates for joint consideration of the problem as a basis on which to structure further disciplinary developments. Research gaps are highlighted, and new directions for future research are suggested.

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“…School buildings stock in Italy According to the Governmental vision, the energy efficiency is a key driver for improvement of school buildings, in order to provide efficient and satisfactory educational facilities [8]. The school building stock amounts to 35% of the entire national building stock [9] and, most of the cases, it requires deep refurbishment and maintenance interventions.…”

Section: 1mentioning

confidence: 99%

Application of artificial neural network and geographic information system to evaluate retrofit potential in public school buildings

Cecconi

Moretti

Tagliabue

2019

Renewable and Sustainable Energy Reviews

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School buildings in Italy are outdated, in critical maintenance conditions and they often perform below acceptable service levels and quality standards. Nevertheless, data supporting renovation policies are missing or very expensive to be obtained. The paper presents a methods for evaluating building's energy savings potential, using the Building Energy Certification (Certificazione Energetica degli Edifici-CENED) open database. The aim of the research concerns the development of a data-driven set of methods, based on the use of open data, machine learning (ML) and Geographic Information Systems (GIS) to support regional energy retrofit policies on school buildings. The main advantage concerns the possibility to predict the post-retrofit energy savings, avoiding the expensive on-site Condition Assessment (CA) phase. Data have been first clustered to identify the most common thermo-physical properties of the envelope, then three retrofit scenarios have been defined to allow the retrofit of homogeneous types of buildings. The energy saving potentials have been evaluated through the implementation of eight Artificial Neural Networks. Ultimately, data have been geolocated and further processed to support the definition of the energy retrofit policies for the most critical regional areas. The Lombardy region has been chosen as case study to test the robustness of the proposed methods. The results of the case study proved that school buildings energy retrofit policies can be defined and compared using available open data, ML and GIS. The future developments of the research concern the further integration of GIS for retrofit cost assessment and scenario analysis.

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An approach for an educational building stock energy retrofits through life-cycle cost optimization

Cited by 17 publications

References 19 publications

Life cycle cost optimization of building façade: A social housing case

Life cycle cost optimization of building façade: A social housing case

Energy Retrofit in European Building Portfolios: A Review of Five Key Aspects

Application of artificial neural network and geographic information system to evaluate retrofit potential in public school buildings

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