Retrofit Measures Research Articles

Seismic fragility and cost-benefit analysis of a conventional bridge with retrofit implements

Fragility analysis is a well-known tool to evaluate the impact of different retrofit measures on damage probability of structures. In this study, the performances of a conventional multi-span continuous (MSC) concrete girder bridge reinforced with different seismic control devices were investigated. The original bridge is supported by both elastomeric bearings and exterior shear keys. For other retrofitting solutions, lead rubber bearings (LRB), friction pendulum systems (FPS), and buckling-restrained braces (BRB) were considered and compared to the original structure of the bridge in terms of seismic performances and economical costs. To analyze the seismic performances, the fragility curves based on the probabilistic seismic demand model were extracted under various near-field and far-field ground motions. Additionally, cost-benefit analyses were performed to determine the benefit of using each of the devices economically. The results indicated that both LRB and FPS significantly reduced the damage probability of substructure, while FPS provided the bridge with high vulnerability in abutment seat at slight and moderate levels of damage. Also, the installation of BRB seismically was an efficient solution and decreased the damage probability of the bridge system. Based on the results of fragility and cost-benefit analysis, LRB was found to be a beneficial implement for the studied bridge.

Dynamic Energy Modelling as an Alternative Approach for Reducing Performance Gaps in Retrofitted Schools in Denmark

When considering that over 80% of buildings in Denmark were built before the 1980′s, a holistic energy retrofitting of the existing building stock is a major milestone to attain the energy and environmental targets of the country. In this work, a case study of three public schools is considered for post-retrofit process evaluation. The three schools were heavily retrofitted by September 2018 with energy conservation and improvement measures that were implemented targeting both the building envelope and various energy systems. A technical evaluation of the energy retrofit process in the schools was carried out, when considering one year of operation after the completion of the retrofitting work. Actual data from the heating and electricity meters in the schools were collected and compared with the pre-retrofit design numbers which rely majorly on static tabulated numbers for savings evaluation. It was shown that the retrofit design numbers largely overestimate the attained savings, where the average performance gap between the expected and real numbers for the three schools is around 61% and 136% for annual heating and electricity savings, respectively. On the other hand, an alternative approach was proposed where calibrated dynamic energy performance models, which were developed for the three schools in EnergyPlus, were used to simulate the impact of implementing the retrofit measures. It was shown that implementing this approach could predict much better the impacts of the retrofit process with an average gap of around 17% for heating savings and 21% for electricity savings. Based on the post-retrofit process evaluation in the three schools, it was concluded that using dynamic model simulations has the potential of lowering the performance gap between the promised and real savings when compared to static tabulated approaches, although the savings are still generally over-estimated in both approaches.

A machine learning-based surrogate model to approximate optimal building retrofit solutions

The building sector has the highest share of operational energy consumption and greenhouse gas emissions among all sectors. Environmental targets set by many countries impose the need to improve the environmental footprint of the existing building stock. Building retrofit is considered one of the most promising solutions towards this direction. In this paper, a surrogate model for evaluating the necessary building envelope and energy system measures for building retrofit is presented. Artificial neural networks are exploited to build up this model in order to provide a good balance between accuracy and computational cost. The proposed model is trained and tested for the case study of the city of Zurich, in Switzerland, and is compared with one of the most advanced models for building retrofit that uses building simulation and optimization tools. The surrogate model operates on a smaller input set and the time required to derive retrofit solutions is reduced from 3.5 min to 16.4 μsec. Results show that the proposed model can provide significantly reduced computational cost without compromising accuracy for most of the retrofit dimensions. For instance, the retrofit costs and the energy system selections are approximated with an average accuracy of R2=0.9408 and f1score=0.9450, respectively. Finally, yet importantly, such surrogate retrofit models may effectively be used for bottom-up retrofit analyses for wide areas and can contribute towards accelerating the adoption of retrofit measures.

Big-data driven building retrofitting: An integrated Support Vector Machines and Fuzzy C-means clustering method

It has become a mainstream to use physical models to quantify expected energy savings from alternative retrofit methods and technologies. However, they are not suitable for predicting energy use of buildings when detailed and specified input parameters are unavailable. The overall purpose of the research is to support the stakeholders in taking decisions on refurbishments options when not all of physical information is available, in order to achieve the Swedish Energy Agency’s measurements of near-zero energy buildings. The research will transfer big data from Swedish Energy Performance Certificates for building retrofitting. A Support Vector Machines and Fuzzy C-means clustering (SVM-FCM) integrated machine learning algorithm is used directly to extract the case-specific knowledge from EPC big data regarding building characteristics and energy saving of retrofit measures. It enables to prioritize retrofit measures and compute their expected energy savings for buildings. This proposed data driven method is an attempt of taking advantage of big data for practical building retrofit selection.

Internal thermal environment and futureproofing of a newly built, naturally ventilated UK school

Research indicates that school children have lower comfort levels than adults and this exacerbates the challenge of tackling the risks of summer overheating in schools without resorting to air conditioning. UN SDG 13 calls for climate action to strengthen the resilience of our cities and reduce the impact of climate change. In this work, a modern, naturally ventilated school in Southampton, UK was used to evaluate single, “hard”, passive retrofit measures and “soft”, building management solutions that could increase the wellbeing of students and reduce current and future demand for cooling. The school was selected as it represents the current standardised design guidance for schools released in 2012 by the Department of Education (DfE). The research presents air temperature observations collected during the summer of 2015. Dynamic thermal modelling was undertaken to evaluate passive retrofit and “soft” solutions to reduce the overheating risk. The model was validated with temperature data collected from the school classrooms. The results indicate that (a) such school buildings have high likelihood of overheating, based on children’s comfort temperatures and (b) passive retrofits focused on shading and ventilation could help to reduce the classroom temperature when required. It is recommended that “soft” adaptive solutions will prove effective to reduce future air conditioning demand, but this will require a radical change in established practices. Achieving the UN Sustainable Development Goals by 2030 will require to rethink and redesign urban living and city infrastructures.

Classification of retrofit measures for residential buildings according to the global cost

Data-driven black-box surrogate models are widely used in research related to buildings energy efficiency. They are based on machine learning techniques, learn from available data, and act as a replacement for or an addition to complex and computationally intensive knowledge-based models. Surrogate models can predict energy demand, indoor air temperature, or occupants behavior, explore search space in optimization problems, learn control rules, etc. This paper analyzes surrogate models that classify building retrofit measures directly according to the global cost. In addition, they quantify the importance of each variable for the classification process. The models are based on random forest classifiers, which are fast and powerful ensemble learners. They can be applied to effectively reduce search spaces when optimizing energy renovation measures or to rapidly identify projects that deserve financial support. This approach is applied to two residential buildings and three scenarios of price development. The training process uses a small share of retrofit options assessed with standard calculations of the heating and cooling demands, as well as the global cost. The results show very high classification performance, even when the models are trained with small and imbalanced training sets. The obtained recall, precision, and F-score values are mostly above 95%, except for extremely small training sets.

A Critical Review of Façade Retrofit Measures for Minimizing Heating and Cooling Demand in Existing Buildings

The building industry is currently experiencing a myriad of challenges, including low energy performance in existing buildings. Since the façade considerably contributes to heating and cooling in buildings, façade retrofit is presumed as an effective solution to minimize cooling and heating demand in existing buildings.In-depth scrutiny in façade retrofit actions reveals different Façade Retrofit Measures (FRMs) that aim to minimize cooling and heating demand in existing buildings. They include Energy Conservation Measures (ECMs), which prevent excessive heat transmittance, and Energy Modulation Measures (EMMs), which modulate energy consumption through passive heating and cooling strategies. A Combination of Measures (CoMs) is also the state-of-the-art in the face of retrofit actions.In this paper, a further analysis elaborates on the effectiveness of each measure in Cooling-Dominated (CD) and Heating-Dominated (HD) climates. This analysis showed that façade retrofit could reduce energy consumption for heating and cooling by up to 50% through architectural interventions.The study findings also revealed that ECMs effectively minimize energy consumption in a heating-dominated climate by lowering conductive and convective heat transfer. However, EMMs are more crucial in reducing energy consumption in a cooling-dominated climate by controlling radiative heat transfer.

A cost-effective building retrofit decision-making model – Example of China’s temperate and mixed climate zones

Sustainable building retrofitting has attracted serious research attention in recent years as it can significantly reduce energy consumption and thus help achieve energy reduction targets set by governments around the world. In this paper, a sustainable retrofit decision-making model is developed to uncover the optimal set of retrofit solutions according to local climatic conditions, building features, and retrofit costs. Net present value (NPV), a common method for analyzing the feasibility of a building retrofit solution, is used to determine the optimal retrofit solution of existing high-rise residential buildings in a temperate zone and hot summer-cold winter zone, involving prototypical 1990s apartments of 116 and 53 m2 floor areas respectively. This reveals that the lighting system, wall insulation, and upgraded window glazing are essential optimal retrofit measures for the temperate zone, whereas the heating system and shading devices are also essential for the hot summer-cold winter zone. The results indicate that the optimal NPV can be obtained by pursuing a 40% energy saving, as it can result in energy saving of up to 50 kWh/m2/year and 95 kWh/m2/year at an average retrofit cost of approximately USD 1.30 and 3.20 m2/year in the temperate and hot summer-cold winter zones respectively. The sensitivities associated with the most influential optimal NPV and energy savings input parameters are critically analyzed; these can be used by decision-makers to determine the risks and uncertainties related to various cost-effective retrofit measures. The model can help in devising the most suitable sustainable retrofit measures for existing buildings commensurate with the energy reduction targets of policy and decision-makers in the two climate zones. It is also amenable to being adapted for other climatic zones to identify the most appropriate sustainable building retrofit for particular local climatic conditions and building characteristics.

Sustainable building retrofit model for high-rise, high-density city: a case in Hong Kong

Considering the significant consumption of energy in existing building stocks, effective retrofitting has great potential for reducing such consumption and promoting sustainability in existing buildings. This study aims to develop a sustainable retrofit decision-making mechanism for high-rise buildings in Hong Kong, China, by uncovering the optimum set of retrofit solutions based on the local climatic conditions, building features and cost. Based on a prototype building in Hong Kong, the study employed the net present value (NPV) to unveil the most suitable solutions to maximise the energy efficiency of existing buildings and minimise their retrofit costs, integrating the energy simulation. This study revealed that it is desirable to adopt an optimal set of measures for achieving a 40% energy improvement since the energy conservation can be as much as 82 (kWh/m2)/year with the optimal NPV of more than US$3300 over a 20 year life span. However, the cooling system, building energy management system and thickness of wall insulation are the most influential factors to the optimum NPV and energy conservation in Hong Kong. The identified optimal set of cost-effective retrofit measures can be effectively implemented for sustainable retrofit projects in the existing building, and the developed methodological framework can be suitably adapted for sustainable building retrofit projects in different climatic zones. The decision-making model is validated by the process of calculating energy consumption, selecting practical retrofit measures and analysing retrofit benefits when taking the local building standards into account.

Analysis and application of a lumped-capacitance model for urban building energy modelling

Buildings are one of the major responsible of energy consumption and carbon emissions worldwide. Due to the continuous growth of cities, researchers moved their focus from single buildings to urban scale analyses.The present work aims at demonstrating the reliability of a lumped-capacitance model in the evaluation of heating and cooling demand at urban level. The model presented extends a previous one with different modules for solar radiation pre-processing, HVAC systems and photovoltaic production estimation. A case-study district of 13 buildings in Padua (Italy) has been analysed, considering detailed single buildings simulations with EnergyPlus as benchmark.Results show that the model leads to good accuracy in the evaluation of the district energy demand for both space heating and cooling. The major sources of error are geometrical simplifications, shadowing and thermal zoning effects, thus showing the importance of high-quality input data in urban modelling. However, results highlight how simple corrections may enhance the accuracy when detailed geometrical information is not available. Finally, the model has been used to assess the cost and energy saving potential of several building retrofit measures and PV installations on the considered district, providing an important indication in the investment priority for decision makers.

Environmental and economic benefits of building retrofit measures for the residential sector by utilizing sensor data and advanced calibrated models

ABSTRACT The present paper investigates the energy savings associated with the implementation of retrofitting measures on Irish residential buildings. A detached residential dwelling, representative of approximately 40% of the residential stock in Ireland, was selected as experimental test bed. The building was progressively retrofitted to an all-electric dwelling. Retrofit measures included the installation of a photovoltaic array, a geothermal heat pump, an electric vehicle charging point, along with building fabric upgrades. The building was equipped with a home area network with more than 30 sensors with 15 min monitoring resolution. The experimental data collected during the experimental campaign aided the comprehensive calibration of an EnergyPlus model. This model was used to investigate the effectiveness of the implemented retrofit measures in terms of energy savings and CO2 reductions. Real-time data from the Irish power system operator was used to calculate the building carbon footprint for different levels of renewable energy penetration to the national grid. Results show that the all-electric retrofitted building can achieve energy savings of up to 45%, with CO2 reductions of approximately 29%, compared to the pre-retrofitted building. Implementing the retrofit measures at scale could potentially lead to carbon emission reductions up to 14% for rural areas in Ireland.

Factors influencing existing medium-sized commercial building energy retrofits to achieve the net zero energy goal in the United States

ABSTRACT Despite the increased awareness of benefits and opportunities resulting from energy retrofits, there is a lack of information regarding the factors influencing the success of energy retrofits – especially deep energy retrofits – aiming to achieve a net zero energy goal. The aim of this study is to identify factors and variables that could contribute to the successful implementation of energy retrofit measures in buildings with the goal of achieving net zero energy. A database of 34 small- and medium-sized commercial building retrofit projects was developed for this analysis, which was derived from the New Buildings Institute’s Net Zero Energy Building Database. Five factor categories were investigated: physical, technical, environmental, economic, and policy. A total of 11 variables from the 5 categories were analysed. The results show that success stems from a combination of certain variables: the number of floors, the climate zone, and the building cost. In general, the results indicate a trend: compact buildings with a construction cost range between $19/m2 and $42/m2 in a mild climate have a higher likelihood of achieving a net zero energy goal. Also, the analysis provides new evidence toward the importance of understanding a building’s physical characteristics in an existing building energy retrofit.

Probabilistic Seismic Resilience-Based Cost–Benefit Analysis for Bridge Retrofit Assessment

This paper explores a probabilistic resilience-based cost–benefit model that can be used to identify the best retrofit measures for bridges. In the model, the increase in resilience is considered to be the benefit of seismic retrofit. A bridge functionality assessment model is also proposed to evaluate resilience. The functionality is estimated based on the appropriate seismic loss and exponential recovery function models. Then, the functionality assessment model is validated with the field data of the post-earthquake recovery process of bridges. The whole proposed methodology is applied to a non-seismically designed multi-span simply supported concrete girder bridge located in Charleston. Seven retrofit measures, including steel jackets, seat extenders and elastomeric isolation bearings, are applied to the as-built bridge in order to assess their cost-effectiveness. The results show that the cost-effectiveness of retrofit measures varies with the ground motion intensity, and the best retrofit is seat extenders followed by elastomeric isolation bearings when considering the seismic hazard of Charleston. Sensitivity analysis is also performed to identify major uncertain parameters to which the resilience-based cost–benefit ratios are most sensitive. Statistical analysis of resilience-based cost–benefit ratios obtained through random sampling of major uncertain parameters reveals that normal distribution can be used to describe their uncertain nature. The 90% confidence intervals of resilience-based cost–benefit ratios estimated from random sampling also indicate the high cost-effectiveness of seat extenders and elastomeric isolation bearings to enhance bridge performance.

Decision-making model for optimum energy retrofitting strategies in residential buildings

Existing buildings consume an inordinate amount of energy globally. The consumption negatively affects the environment and economy; therefore, it is necessary to improve energy performance in buildings by retrofitting the existing ones. Several energy retrofitting strategies are proposed in the energy efficiency programs, and hence, the selection of optimal and efficient solutions is a complex task. Several factors affect the implementation of energy retrofitting measures such as budget, comfort requirement, and reliable economic value. To this end, the study was conducted to develop a decision-support model for residential building owners based on Mixed Integer Linear Programming. The model was designed to select optimum energy retrofitting strategies. The objective function involves minimizing the total Life Cycle Cost of the energy retrofitting plan to achieve economic benefit while considering the budget, thermal comfort, and recommended illumination level as primary constraints. To test the validity of the model, a case study of a residential building was conducted. The findings of the study suggest an energy retrofitting plan that decreases approximately 70% of energy consumption. A sensitivity analysis was conducted to examine the effect of the change in the cost component on the Life Cycle Cost and energy saving.

Operability and Technical Implementation Issues Related to Heat Integration Measures—Interview Study at an Oil Refinery in Sweden

In many energy-intensive industrial process plants, significant improvements in energy efficiency can be achieved through increased heat recovery. However, retrofitting plants for heat integration purposes can affect process operability. The aim of this paper is to present a comprehensive overview of such issues by systematically relating different types of heat recovery retrofit measures to a range of technical barriers associated with process operability and practical implementation of the measures. The paper presents a new approach for this kind of study, which can be applied in the early-stage screening of heat integration retrofit measures. This approach accounts for the importance of a number of selected operability factors and their relative significance. The work was conducted in the form of a case study at a large oil refinery. Several conceptual heat exchanger network retrofit design proposals were prepared and discussed during semi-structured interviews with technical staff at the refinery. The results show that many operability and practical implementation factors, such as spatial limitations, pressure drops and non-energy benefits, influence the opportunities for implementation of different types of heat exchanger network retrofit measures. The results indicate that it is valuable to consider these factors at an early stage when designing candidate heat exchanger network retrofit measures. The interview-based approach developed in this work can be applied to other case studies for further confirmation of the results.

Laboratory Validation of Integrated Lighting Systems Retrofit Performance and Energy Savings

Light-emitting diodes (LED) fixtures and lamps have emerged as leading technologies for general illumination and are a well-established energy efficiency retrofit measure in commercial buildings (from around 2% of installed fixtures and lamps in 2013 to 28% by 2020). Retrofit approaches that integrate elements, such as networked controls, daylight dimming, and advanced shade technologies lag in comparison. Integrated retrofits have been shown to increase savings over single end-use retrofits, but are perceived as higher complexity and risk. More validation of integrated lighting system performance is needed. This study presents results from laboratory testing of three packages combining fixtures, networked controls, task tuning, and daylight dimming, advanced shades, and lighting layout changes. We characterize performance in perimeter open-office zones, finding energy savings from 20% for daylight dimming and automated shades (no LED retrofit) to over 70% for LED retrofits with advanced controls and shades or lighting layout changes. We present some implementation details, including lessons learned from installation and commissioning in the laboratory setting. We also discuss cost-benefit analysis approaches for the types of packages presented, including the need to quantify and incorporate energy and non-energy benefits for advanced shades packages, which enhance occupant comfort but add significant cost.

Impact of climate change in cultural heritage: from energy consumption to artefacts’ conservation and building rehabilitation

Historic artefacts must be properly preserved if they are to be transmitted to future generations. Indeed, several methodologies and guidelines that aim to safeguard artefacts by limiting the ranges in which the indoor temperature and relative humidity vary exist, which means energy consumption. This paper aims to quantify the energy consumption associated to three different setpoints and respective financial cost, as well as their future trend to demonstrate the positive outcome of passive retrofit measures, since they will be responsible for decreasing the building’s energy consumption and mitigating the effects of climate change in artefacts’ preservation. A validated whole-building hygrothermal model of a historic building was used coupled to climate change weather files to obtain the expected future indoor conditions for three types of climates, which were also assessed using a risk-based analysis. The positive potential of passive retrofit measures on the building’s energy consumption was shown, but the risk-based analysis showed that the measures performance are not universal since, for example, whilst the selected measures decrease the risk of chemical decay for Seville, they have the contrary behaviour for Oslo. To achieve these goals more than 1400 simulations were run in WUFI®Plus, which took more than 1600 h.

Retrofit Methodology Based on Energy Simulation Modeling Applied for the Enhancement of a Historical Building in L’Aquila

Energy loss has not been addressed effectively by policies introduced to encourage the preservation and enhancement of historical structures. Material and other constraints, together with safety standard improvements, do not always guarantee adequate levels of environmental performance. An optimization of retrofit measures to align with new uses, new standards of comfort, and energy saving are needed, as are studies based on new best practices for the enhancement of architectural heritage. This paper presents a method that uses dynamic models tared on non-destructive surveys, and based on compatible energy and structural interventions derived from preliminary analyses integrated into special design tools. Energy simulations were carried out using Design Builder (6.1.5.002, Designbuilder Software Ltd, Stroud, UK) software. The case study is a former hospital, S. Salvatore, in L’Aquila, an architecturally important building, severely damaged by an earthquake in 2009. The methodology presented in this research includes in-depth investigations coherently systematized into a multi-scenario output using simulation software. The results guarantee a high level of compatibility with restoration and seismic guidelines, and new building environmental performance requirements.

Energetic Retrofit Strategies for Traditional Sicilian Wine Cellars: A Case Study

Sicily is characterized by rural buildings, Palmenti, destined to wine production, which are scattered along the countryside and part of the local historical heritage. There are different types of rural buildings, but all have in common the use of ancient and well-established bioclimatic techniques for wine conservation and aging. Most of them were built with the double function of living space for the owner and productive spaces for all the activities correlated to the cultivations. Indeed, many rural houses, destined to the wine production, are characterized by wineries and wine cellars (the first for the wine production, the second to store the wine for the aging process). The growing production of high-quality Sicilian wines, very appreciated all over the world, leads to upgrade the ancient Palmenti to seek optimal hygrothermal conditions and, therefore, to guarantee high performance of the produced and stored wines. The purpose of this study is to investigate how the retrofit measures taken to comply with the energy regulations could affect the thermal behavior of a wine cellar constructed with consolidated bioclimatic technics. The results show the importance of not insulating the solid ground floor for maintaining suitable temperatures for the fermentation and aging of wine. This study can be useful for future analysis when comparing the optimal hygrothermal conditions of wine cellars located in homogeneous viticultural areas (with same climate, geology, soil, physical features, and height) in other parts of the world.

Auditing and design evaluation of building automation and control systems based on eu.bac system audit – Danish case study

Abstract Improving the energy performance of buildings will prove vital for countries worldwide to reduce their energy consumption and emissions. A key player in reaching this goal is building automation and control, as having well-designed and operated building automation and control systems (BACS) provide large capabilities in optimizing the energy performance of different systems. In this regard, building owners and planners must be able to assess and evaluate the current status of their BACS and identify potential improvements. While there has been a large block of work done in Denmark along with regulations aiming to audit the overall building performance and individual systems characteristics, very little has been done in the field of auditing the building automation and control system and evaluating its structure and operation patterns. This lack of systematic BACS auditing and evaluation in Danish buildings is addressed in this work with the first implementation and evaluation of the eu.bac System methodology in a university office building. The building was found to comply with the lowest automation and control class E. Two BACS retrofit packages were proposed and evaluated, and energy savings up to 28.5% are reported. The preliminary assessment results reported demonstrate the potential of building automation and control retrofit measures in a combined holistic improvement package alongside building envelope upgrade. In addition, the impact of the eu.bac System improvements and labeling on the building's classification based on the recent Danish building regulation BR18 is evaluated. The study discusses the feasibility of eu.bac System tool implementation in Danish buildings and suggests improvements. It also correlates and compares the eu.bac System audit to the upcoming European SRI instrument. In light of the huge efforts to digitalize the Danish energy sector, ensuring proper design and operation of BACS is of great importance. Thus, a systematic and methodical BACS auditing and evaluation methodology will be a crucial part of buildings’ initial and retro-commissioning platforms.