LCC assessments and environmental impacts on the energy renovation of a multi-family building from the 1890s

Liu, Linn; Rohdin, Patrik; Moshfegh, Bahram

doi:10.1016/j.enbuild.2016.10.040

Cited by 34 publications

(46 citation statements)

References 15 publications

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“…A number of studies [7,[27][28][29][30][31][32][33][34][35] have investigated the effect of weather changes on building energy consumption. Amber, et al [6] investigated the effect of four weather variables, i.e., surrounding temperature, global irradiance, humidity and wind velocity on the electricity usage of different buildings.…”

Section: Weather Datamentioning

confidence: 99%

Energy Consumption Forecasting for University Sector Buildings

et al. 2017

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Reliable energy forecasting helps managers to prepare future budgets for their buildings. Therefore, a simple, easier, less time consuming and reliable forecasting model which could be used for different types of buildings is desired. In this paper, we have presented a forecasting model based on five years of real data sets for one dependent variable (the daily electricity consumption) and six explanatory variables (ambient temperature, solar radiation, relative humidity, wind speed, weekday index and building type). A single mathematical equation for forecasting daily electricity usage of university buildings has been developed using the Multiple Regression (MR) technique. Data of two such buildings, located at the Southwark Campus of London South Bank University in London, have been used for this study. The predicted test results of MR model are examined and judged against real electricity consumption data of both buildings for year 2011. The results demonstrate that out of six explanatory variables, three variables; surrounding temperature, weekday index and building type have significant influence on buildings energy consumption. The results of this model are associated with a Normalized Root Mean Square Error (NRMSE) of 12% for the administrative building and 13% for the academic building. Finally, some limitations of this study have also been discussed.

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Section: Weather Datamentioning

confidence: 99%

Energy Consumption Forecasting for University Sector Buildings

et al. 2017

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“…Five publications have been found which explicitly discuss the identification of tipping points in the context of insulation thickness [19,[23][24][25][26]. From the five publications, two are based on the same research [23,24].…”

Section: Research Question 2: Tipping Point For Insulationmentioning

confidence: 99%

“…The papers cover various climatic contexts, including a moderate climate (Belgium), a warm climate (Spain and Portugal) and a cold climate (Sweden). The papers focus either on a building element, e.g., roof [20] and floor on grade [23,24] or an entire building [23,25,26]. The service life considered is 50 years (with sensitivity analysis of 30 and 60 years) for Pombo et al [25] and Liu et al [26], and 60 years for Allacker [23,24].…”

Section: Research Question 2: Tipping Point For Insulationmentioning

confidence: 99%

“…As all studies focused on residential buildings, the influence of the function of the building on the tipping points has not been addressed through our review study. Moreover, some of the studies included an analysis of the tipping points both from an environmental and cost perspective, i.e., Allacker [23,24] and Liu et al [25]. Pombo et al [26] solely made an analysis of tipping points from a cost perspective.…”

Section: Research Question 2: Tipping Point For Insulationmentioning

confidence: 99%

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Strategies to Improve the Energy Performance of Buildings: A Review of Their Life Cycle Impact

et al. 2018

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Globally, the building sector is responsible for more than 40% of energy use and it contributes approximately 30% of the global Greenhouse Gas (GHG) emissions. This high contribution stimulates research and policies to reduce the operational energy use and related GHG emissions of buildings. However, the environmental impacts of buildings can extend wide beyond the operational phase, and the portion of impacts related to the embodied energy of the building becomes relatively more important in low energy buildings. Therefore, the goal of the research is gaining insights into the environmental impacts of various building strategies for energy efficiency requirements compared to the life cycle environmental impacts of the whole building. The goal is to detect and investigate existing trade-offs in current approaches and solutions proposed by the research community. A literature review is driven by six fundamental and specific research questions (RQs), and performed based on two main tasks: (i) selection of literature studies, and (ii) critical analysis of the selected studies in line with the RQs. A final sample of 59 papers and 178 case studies has been collected, and key criteria are systematically analysed in a matrix. The study reveals that the high heterogeneity of the case studies makes it difficult to compare these in a straightforward way, but it allows to provide an overview of current methodological challenges and research gaps. Furthermore, the most complete studies provide valuable insights in the environmental benefits of the identified energy performance strategies over the building life cycle, but also shows the risk of burden shifting if only operational energy use is focused on, or when a limited number of environmental impact categories are assessed.

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“…According to the literature, in developed and developing countries it constitutes about 40% of the total energy consumption [1][2][3][4][5][6][7][8]. Residential buildings are responsible for a major part of the energy consumption of the building sector [9].…”

Section: Introductionmentioning

confidence: 99%

Multi-Variable Optimization of Building Thermal Design Using Genetic Algorithms

Ferdyn-Grygierek

Grygierek

2017

Energies

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Abstract:The building sector is one of the largest energy consumers in the world, comprising about 40% of the total energy consumption in numerous countries. Early design decisions have a significant impact on the energy performance of buildings. The paper presents the multi-variable optimization of the selected design parameters in a single-family building in temperate climate conditions. The influence of four types of windows, their size, building orientation, insulation of external wall, roof and ground floor and infiltration on the life cycle costs (LCC) is analyzed. Optimal selection of the design parameters is carried out using genetic algorithms by coupling the building performance simulation program EnergyPlus with optimization environment. The simulations were conducted for seven optimization cases. The analysis is performed for two variants of a building with heating and cooling systems and with a heating system only. Depending on the analyzed case, the life cycle costs decreased from 7% to 34% LCC value of the reference building. In the case of temperate climate, the building optimization (in terms of heat demand only) substantially reduces the heating costs, yet the summer thermal comfort conditions deteriorate significantly.

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LCC assessments and environmental impacts on the energy renovation of a multi-family building from the 1890s

Cited by 34 publications

References 15 publications

Energy Consumption Forecasting for University Sector Buildings

Energy Consumption Forecasting for University Sector Buildings

Strategies to Improve the Energy Performance of Buildings: A Review of Their Life Cycle Impact

Multi-Variable Optimization of Building Thermal Design Using Genetic Algorithms

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