Multivariant design and multiple criteria analysis of building refurbishments

Kaklauskas, Artūras; Zavadskas, Edmundas Kazimieras; Raslanas, Saulius

doi:10.1016/j.enbuild.2004.07.005

Cited by 264 publications

(131 citation statements)

References 5 publications

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“…Considering this level of complexity, a holistic approach is essential, which employs methodologies combined with national and international standards [4,14,15]. In Turkey, despite the ongoing accreditation of regulations to EPBD, methodological approaches for energy-efficient improvement of buildings are insufficient.…”

Section: Methodsmentioning

confidence: 99%

“…NPV approach, which is the sum of all values in a predicted lifetime, with respect to parameters such as compound interest, growth rate etc., is utilized to estimate the difference between the present value (PV) of an investment cost in the future and the cash flows obtained due to this investment. 4 For this study, investment cost is the construction cost and cash flows are cost reductions achieved in energy consumption due to ECMs. Monetary statistics such as interest rate, inflation rate are obtained from Central Bank of the Republic of Turkey website.…”

Section: Investment/payback Analysis Of Ecmsmentioning

confidence: 99%

“…Necessity to reduce fossil fuel consumption and CO 2 emissions led energy-efficient improvements of existing buildings and regulations for new building designs. These efforts developed into research areas such as monitoring and assessment of energy performance of existing buildings, further into retrofit of existing buildings due to implementation of possible energy conservation measures [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of an envelope retrofit strategy for an existing office building

Gucyeter

Günaydın

2012

Energy and Buildings

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a b s t r a c tEnergy-efficient retrofits include improvement of building envelope via insulation, employment of building integrated renewable energy technologies, and climate control strategies. Building envelope improvements with insulation is a common approach, yet decision-making plays an important role in determining the most appropriate envelope retrofit strategy. In this study, main objective is to evaluate and optimize envelope retrofit strategies through a calibrated simulation approach. Based on an energy performance audit and monitoring, an existing building is evaluated on performance levels and improvement potentials with basic energy conservation measures (ECMs). The existing building is monitored for a full year and monitoring data is used in calibrating the simulation model. In order to obtain a better-performing building envelope three retrofit strategies including several ECMs are proposed. Retrofit strategies are simulated through calibrated base-case model, and results are evaluated according to changes in indoor environmental parameters and annual energy consumption measures. The analysis of results indicated that pre-assessed strategies yield close results. Therefore, a more comprehensive evaluation based on different decisive criteria is used in optimization of the final retrofit strategy, with the intention to evaluate the effect of individual ECMs on annual end-use energy consumption and investment.

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Section: Methodsmentioning

confidence: 99%

Section: Investment/payback Analysis Of Ecmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimization of an envelope retrofit strategy for an existing office building

Gucyeter

Günaydın

2012

Energy and Buildings

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“…These contain general facts about the building considered and information of its deterioration and obsolescence. Reasons for refurbishing and their significance as well as the money to be spent on it are also included [1]. 2) Tables assessing refurbishment solutions (walls, windows (see Fig.…”

Section: A Computer Learning Subsystemmentioning

confidence: 99%

Building’s Refurbishment Computer Learning System with Augmented Reality

Kaklauskas¹

2013

IJEEEE

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Abstract-Since 1999 Vilnius Gediminas TechnicalUniversity has already introduced three e-learning Master's degree programmes. This paper proposes a way to integrate augmented reality and computer learning systems. In order to demonstrate the integration of the above systems in building refurbishment projects, the Building Refurbishment Computer Learning System with Augmented Reality (BR-CLS-AR) has been developed. The authors of this paper participated in the project "Learning Augmented Reality Global Environment" (LARGE), part of the Lifelong Learning Programme. One of LARGE's goals (on the part of Lithuania) was to integrate augmented reality and computer learning systems (i.e. to develop the BR-CLS-AR). To check the accuracy of the system, its entire solution process was reproduced manually. The results of the manual calculations matched those produced by the computer. Moreover, each individual phase in the system and its subsystems was checked with experts in this field, i.e. the underlying calculations were found to be in conformity with the experts' logical reasoning. Owing to the suggestions from these experts, some useful changes have been introduced in the system. The BR-CLS-AR consists of a computer learning subsystem and an augmented reality subsystem.

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“…Furthermore, this makes energy efficiency projects competitive with other projects. A decision can be made using the following two approaches [5]- [9]:…”

Section: Introductionmentioning

confidence: 99%

A multiple objective optimisation model for building energy efficiency investment decision

Malatji

Zhang

Xia

2013

Energy and Buildings

122

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A multiple objective optimisation model is formulated to help decision makers to make an optimal decision when investing in energy-efficient building retrofitting.The objectives are to maximise the energy savings and minimise the payback period for a given fixed initial investment. The model is formulated as a multiobjective optimisation problem with the net present value (NPV), initial investment, energy target and payback period as constraints and it is solved using genetic algorithms (GAs). The optimal decision is reached by choosing the most optimal actions during energy retrofit in buildings. The model is applied to a case study of a building with 25 facilities that can be retrofitted that illustrates the potential of high energy savings and short payback periods. The sensitivity analysis is also performed by analysing the influence of the auditing error of the facilities, wrongly specified energy savings, the initial investment, changes in interest rate and the changes of electricity prices on the payback period, the maximum energy saved and NPV of the investment. The outcome of this analysis proves that the model is robust.

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Multivariant design and multiple criteria analysis of building refurbishments

Cited by 264 publications

References 5 publications

Optimization of an envelope retrofit strategy for an existing office building

Optimization of an envelope retrofit strategy for an existing office building

Building’s Refurbishment Computer Learning System with Augmented Reality

A multiple objective optimisation model for building energy efficiency investment decision

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