Renovation Costs Research Articles

The resiliency of photovoltaic applied fuelling station in Malaysia: A dynamic urban emission displacement assessment

The number of fuelling stations continue to increase with the growing population and demand. Low carbon building for the cities and communities concept has led to a reassessment of service provision and fuel station urbanisation using a safe and matured renewable system; solar photovoltaics. This study uses a dynamic urban emission displacement assessment considering spatial and temporal variables of a fuel retail building in Malaysia. The result shows that the carbon emission potency is not concentrated within the fuelling area; instead, it's redirected through vehicle emission, operation and maintenance. The annual emission displaced by the installed solar photovoltaic system is about 18,022 metric tonnes of CO 2 /year. The solar-integrated building has its monthly electricity cost reduced by 20% with only 70% of its roof space usage. The life cycle cost of a 50kW photovoltaic system refurbishment translates to around RM22,000 of savings per year. However, the return on investment may take about eight years. In reality, fossil fuel divestment is impossible due to its reliability, but renewable technology can improve the built environment and air quality management in the city. • Annual vehicle fuel emission is about 18 x 10 6 metric tonnes of CO 2 per station. • Vehicle displaced urban spatial-independent dynamic CO 2 emission potency. • The integrated solar photovoltaic system improves the fuelling station BEI by 90%. • A 20% reduction of commitment cost with only 70% available space occupation. • A 50kW system installation is equal to RM22,750 of savings per year.

Decision-Making Approach based on Multi-objective Optimization to Achieve Net-Zero Energy Neighborhoods through Retrofit in a Tropical Climate

Among the main causes of environmental deterioration worldwide, buildings are among those responsible for a large percentage of energy-related CO2 emissions. Because of this, finding solutions to this problem is necessary. This research project involves building the energy model of a neighbourhood located in Panama, Herrera province. The main elements were classified and systematized using DesignBuilder and then implemented in an optimization analysis that seeks to approximate the NZED standard. The optimization’s main objectives were to maintain or improve thermal comfort, reducing energy consumption to the lowest possible. The best design options were those given by the method of essential design variables determined in the sensitivity analysis. It was possible to conclude that combining changes in occupant behavior with specific changes in the envelope leads to a more efficient reduction in electricity consumption. Because they lead to a significant reduction in consumption without involving the cost of the total modification of the envelope, with these modifications, a reduction in electricity consumption of 52,852 kWh/year was obtained at a renovation cost of B/.19,890.00 with a recovery period of seven years.

Benefit assessment of second-life electric vehicle lithium-ion batteries in distributed power grid applications

Lithium-ion batteries in electric vehicles (EVs) are typically replaced after they lose about 20% of their capacity. With the rapid growth in EVs, there will be a tremendous potential to re-use the remaining EV battery capacities in power systems. Hence, this work focuses on capturing the economic benefits of using such second-life (SL) EV batteries. While previous works mainly focus on bulk storage applications, we demonstrate that the most beneficial route for SL batteries lies in distributed applications in power systems. Specifically, refurbishment and grouping of SL battery packs pose technical and operational challenges, thereby incurring significant costs and risks when large battery packs are adopted in bulk applications.Instead, when distributed at the residential and micro-grid level, such refurbishment costs and operation risks can easily be avoided as only small-size battery packs are required. An experimentally-validated model is incorporated to capture the battery capacity degradation and used to compare fresh batteries and SL-batteries. Using a model predictive control scheme and a 33-bus power network, the benefits of SL-batteries are quantified and verified.

Computational Tool to Support the Decision in the Selection of Alternative and/or Sustainable Refrigerants

There have been consequences regarding the increment of the greenhouse effect, such as the rise in the planet’s global temperature, and climate change. Refrigerants have an important contribution to the aforementioned environmental impact. In particular, hydrofluorocarbons (HFCs) contribute to the destruction of the ozone layer and the increase of the greenhouse effect. Protocols, international agreements, and legislation were developed to slow down the emission of greenhouse gases. Prohibition and definition of deadlines for the gradual elimination of various refrigerants have been proposed to replace them with others that are environmentally sustainable. Soon, the refrigeration sector will have to replace some refrigerants with others that are alternative and/or sustainable with minimal or zero environmental impact. A computational tool to support decision-making regarding the selection of alternative and/or sustainable refrigerant to replace the old one is developed to be used by refrigeration companies, manufacturers, and installers. A suggestion of refrigerants with reduced environmental impact is provided, ensuring similar thermal performance and energy efficiency, considering the safety level and renovation cost of the installation and refrigerant itself. This decision support system (DSS) uses an objective function that includes the technical specifications and properties of alternative and sustainable refrigerants. The computational tool is applied in the agri-food sector in three case studies. The results show not only the consistency of the computational tool, but also its flexibility, objectivity, and simplicity. Its use allows companies to choose refrigerants with reduced environmental impact, reduced or zero ozone depletion potential and global warming impact, thus contributing to environmental sustainability.

Optimal Planning of Renovation Work in Leased Buildings under Integrated Project Delivery Method

This paper presents the development of a novel model for optimizing the planning of renovation work in leased buildings that utilize the integrated project delivery (IPD) method to maximize the income of leased units during renovation work. The present model is developed in two main phases: optimization and renovation planning. The model integrates a novel methodology that enables decision makers to select optimal crew deployment data and number of assigned crews for all renovation activities, identify an optimal unit renovation order of all leased units, generate feasible renovation schedules, and quantify and minimize total net renovation cost. A real-life case study of three renovation projects was analyzed to illustrate the use of the model and demonstrate its capabilities. The results of this analysis clearly illustrate the original contributions of the model to the body of knowledge and its novel capability in generating optimal renovation schedules for leased buildings that enable contractors to maximize their share of rewards under IPD projects while minimizing their total renovation cost.

EXAMINATION OF EFFECTIVE AND EFFICIENT METHODS OF THERMAL INSULATION RENOVATION WHEN CONSIDERING MEDICAL COSTS

The purpose of this study is to establish effective and efficient methods of thermal insulation renovation. We examined the combinations of repairs of ceilings, outer walls, windows, and floors that could reduce medical costs and heating and cooling costs, and shorten the payback period of the costs of renovation. Assuming that a 30-year-old couple and two children would live in the accommodation after its renovation, the effective and efficient renovation methods were found to be combinations of “ceiling, floor and window” and of “ceiling and window”.

An economic production quantity model with refurbishment policy in dual-channel logistics

This work considers a dual logistics model with production and refurbishment simultaneously where the manufacturer accumulates all the return items in return inventory and sends it for refurbishment. The novelty of this work is in utilizing the strategy “buying green” and defining the demand function as dependent on selling price and environmental parameters. This study also examines whether the manufacturer works better as an original equipment manufacturer (forward logistics), as a manufacturer–refurbisher or as an independent refurbisher (reverse logistics) and analyses their effect on environment through carbon emission. Most of the reverse logistics model considers production inventory and refurbished/remanufactured inventory consecutively which is not realistic at all. The new item inventory is much more higher than the refurbished inventory because of the low acceptance rate of refurbished product. So, in this model, the return time of product is random. The aim of this work is to optimize the return time and how much return quantity can be accepted for a single time planning horizon. The findings of this work reveal that the total average cost is minimized with reverse logistics, and from the environmental perspective also, the models with reverse logistics are better than the forward logistics path only. Further, we have investigated the sensitivity analysis and shows that with high quality of production process, we can minimize the carbon emission up to a certain level and refurbishment is good only when refurbishment cost is smaller than the production cost. Finally, we carry out the graphical illustrations to justify our models.

Sensitivity analysis of building energy models due to the shading effect of surrounding buildings to support building renovation

Building energy simulation is an analytical process to help building owners and designers evaluate the energy performance of the building. Uncertainty in the building energy modelling influences the building renovation from two perspectives: 1) calculating as-built energy consumption, 2) analysing the energy performance of renovation alternatives. Energy models can enhance by incorporating contextual and surrounding data. To this aim, we conducted a systematic study to investigate the effect of surrounding buildings in different distances, heights, and orientations in studying the as-built energy consumption of an example building. The research also investigates the impact of a specific surrounding building on the energy performance of three different renovation alternatives, namely the modification of windows, external walls, and roofs. The results demonstrate that a higher height to distance ratio of the surrounding buildings influences the energy consumption more dramatically. In addition, a surrounding building located in the south direction causes more effect on the energy result than other directions when the building is in the northern hemisphere. For renovation scenarios, if there is a specific building in the south of the building under renovation, the window modification leads to less energy consumption than other renovation scenarios. The paper discusses that for renovation projects, an initial examination of surrounding buildings before selecting the renovation alternative is crucial; since different placements of surrounding buildings can affect the performance of renovation scenarios differently, which can cause a variation in the cost of renovation.

Energy efficiency at what cost? Unjust burden-sharing of rent increases in extensive energy retrofitting projects in Sweden

Although renovation costs can lead to rent increases in energy retrofitting, it is often assumed that reductions in energy costs will counterbalance the rent increase. In Swedish multifamily housing, energy costs for heating are however generally included as a fixed component in the monthly rent, meaning that the rent increase after energy retrofitting corresponds to the net change in rent level as well as energy costs for heating. This makes Sweden a methodologically advantageous setting for studying tenants' cost burden of energy retrofitting. The aim of this study was thus to investigate how energy performance improvement has affected rent increases in Swedish renovation projects between 2013 and 2019. Utilising a national database of multifamily housing, it was found that energy retrofitting entailed a cost relief for tenants in renovation projects with smaller investments. However, in renovation projects with larger investments, energy retrofitting entailed a cost burden for tenants. Moreover, public housing companies had conducted a high share of the extensive energy retrofits, leading to low-income tenant groups being disproportionately subjected to cost burdens of energy retrofitting. On the contrary, light energy retrofits with a cost relief for energy efficiency had been rather evenly distributed across income groups. These results indicate ongoing conflicts with the ability-to-pay principle in the energy transition of Swedish multifamily housing, and suggest that if low-investment energy retrofits are not sufficient for upcoming objectives and requirements, subsidies could be needed to compensate low-income tenants for the cost burden of extensive energy retrofitting.

Life Cycle Cost Analysis of rooftop gardens using openLCA

Most innovative and eco-friendly project alternatives are rejected due to higher initial costs. This problem arises due to the general cost analysis that considers only the initial costs. It can be solved using Life Cycle Cost Analysis (LCCA) approach because LCCA helps the decision makers to select the project alternative with more economic benefits by considering the costs incurred in it throughout the life cycle. In this paper, the life cycle cost analysis of the rooftop garden was carried out and compared with the conventional roof using openLCA software. The rooftop garden includes many environmental benefits such as the reduction of the urban heat island effect, reduction of noise pollution, improvement in quality of air, management of surface runoff and conservation of biodiversity. Still, the use of rooftop gardens is not common in the projects due to their higher initial costs. Thus, LCCA was carried out to evaluate its economic feasibility. A model was developed using openLCA software to carry out the analysis. The costs considered in the analysis include the initial costs, maintenance costs, renovation costs and energy costs. The cost data were collected for extensive rooftop gardens laid in commercial buildings in and around Chennai city. The results indicate that the initial cost of the rooftop garden was 5.2 times higher than that of the conventional roof but due to the prolonged life period and the energy savings of the rooftop garden, the life cycle cost was 5.25% lower than that of the conventional roof.

고령자 커뮤니티케어 실현을 위한 BIM활용 공동주택개조 시뮬레이션 개발

Recently, housing renovation support has been strengthened to improve the residential environment of elderly households through integrated community care projects. Although the support is mainly concentrated on the disadvantaged in housing, it is evaluated as a desirable effort in terms of reinforcing the welfare system to provide aging residents with housing remodeling support, and revitalizing the housing recycling industry through these projects. However, the housing renovation support has very low accessibility due to the lack of public relation efforts, limited eligibility, and the insecurity and uncertainty of the system. The most efficient way to increase its accessibility can be an approach using actual cases. However, as few cases have been recorded to date and there is a limitation in face-to-face contact with all eligible residents, access via an online virtual experience can be an effective alternative. This study therefore focused on collective housing buildings where the majority of the elderly currently reside and spatial information can be easily acquired. The objectification process used to construct a Building Information Model (BIM) was performed by reflecting the physical obstacles and body functions of the elderly specific to each lifestyle. A simulation system based on this model was established by setting and applying views by space. This would enable the system to generate comparative images of the conditions before and after the construction to enhance the user’s understanding as well as the drawings and details of the construction. Since construction details are also part of object information, estimates can be created by linking them with unit price information. This virtual simulation system is expected to reduce the waste of renovation costs and resident dissatisfaction, and increase the accessibility of the support project by reaching a wide range of users via an online approach.

Evaluation of energy-saving retrofit projects of existing rural residential envelope structures from the perspective of rural residents: the Chinese case.

The existing residential envelope in rural areas has low energy efficiency, with low energy utilization and serious energy waste for winter heating. However, in recent years, farmers have not undertaken energy efficiency retrofit projects for existing buildings in rural areas. This study proposed an evaluation model based on the logistic-AHP-TOPSIS method from the perspective of farmers. First, this study conducted a questionnaire survey of 208 rural households and used logistic models to determine which existing evaluation indicators significantly impact farmers' willingness to participate in energy efficiency retrofit projects. Second, the weights of the eight indicators were determined using AHP. Finally, this study evaluated the retrofit program of a case in Gansu Province using the TOPSIS method. In the analysis, total investment, annual winter heating costs and energy efficiency improvements were found to be the most important factors for farmers. The highest score for existing buildings was 0.3747 because there is no additional investment required; the option of partial retrofitting according to the actual needs of households scored 0.3350 because it balances economic performance with energy efficiency performance; The entire retrofit program has the highest investment and a long payback period, and its score is the lowest with 0.2904. Furthermore, the study recommended that a self-build and self-repair organization led by village collectives be developed to unify the retrofit design and construction and lower renovation costs. Bulk purchases could enable farmers to increase their power in negotiations.

Comprehensive evaluation and analysis of low-carbon energy-saving renovation projects of high-end hotels under the background of double carbon

Under the background of “double carbon”, the low-carbon and energy-saving renovation of existing public buildings has become an effective way to reduce greenhouse gas emissions and achieve energy conservation and emission reduction. This paper analyzes the cost of energy-saving and low-carbon renovation of existing public buildings and the composition of energy-saving benefits, comprehensively evaluates the case projects through the benefit-cost-cost ratio, net present value, and environmental benefits, and conducts evaluation and verification through the case of high-end hotels, in order to provide existing public buildings. Provide reference for building low-carbon and energy-saving renovation decisions. According to the calculation of the case project, a total of 670 kg of standard coal was saved, 1670 kg of carbon dioxide and 455.6 kg of carbon were reduced, which effectively reduced the emission of pollutants, and played a very positive role in reducing carbon emissions and protecting the environment.

Life cycle assessment of methanol vehicles from energy, environmental and economic perspectives

As a new alternative fuel vehicle for energy reserve strategy, the development of methanol vehicles in China has been at the forefront. Completed pilot projects have demonstrated that methanol vehicles can effectively reduce fuel costs and pollutant emissions during driving. In addition to methanol vehicles, alternative fuel vehicles such as electric vehicles and compressed natural gas vehicles also maintain a sound development momentum in China. It is essential to understand which one has more advantages from sustainable development. This paper uses the Energy, Environment, and Economy (3E) evaluation method to analyze the energy consumption, environmental emission, and economy of methanol, electric, gas, and gasoline vehicles from the whole life cycle perspective. A comprehensive index evaluation model was constructed, and the development potential of the three alternative fuel vehicles was ranked under four different scenarios (energy-oriented, environment-oriented, economic-oriented, and equilibrium scenarios). This research shows that methanol vehicles have higher total energy consumption than gasoline vehicles in the whole life cycle. In terms of greenhouse gas emissions, compared with gasoline vehicles, methanol, and compressed natural gas vehicles decreased by 8.79 tons and 12.45 tons, respectively. At the same time, methanol vehicles have a better economic benefit than gasoline vehicles (37%), which is the same as the completed pilot projects. In addition, results also show that due to the advantages of low renovation cost and fuel price, the user’s cost of methanol vehicles is more down than blade electric vehicles, which makes them have better development potential compared with electric and compressed natural gas vehicles in the economic-oriented and equilibrium scenario. Therefore, methanol vehicles can be used as alternative fuel vehicles for long-term development in China.

Balancing Social and Economic Sustainability in Renovation with an Affordable Option for Tenants? A Pilot Study from Sweden

A public housing company has applied a new renovation strategy, comprising no standards raising and thus rent-raising measures, in 20% of its apartments. Prior to renovation, the tenants were given the opportunity to choose renovation options involving different standards and costs after renovation. The purpose of the study is to follow up and give feedback on the renovation strategy. The aim was to evaluate implementation of the strategy in practice using a case study, in terms of the tenants’ opportunity to influence and the housing company’s profitability. To follow up, two methods were used: a survey of the tenants’ perception of choosing renovation options, and a financial assessment of the profitability based on the renovation cost and rent increase for different choice scenarios. The results from the survey show that the tenants appreciate being able to choose between different renovation options as it gives them the opportunity to decide on their housing costs and standard. With more than half of the tenants choosing the maintenance option involving a very low rent increase, the dividend yield will not be high enough to make the renovation profitable, but if only 20% had chosen the maintenance option, the dividend yield would be more feasible in the long run.

Economic Benefit Evaluation Model of Urban Street Reconstruction Based on Parallel Multigrid Computing

This study draws on the relevant experience of algebraic multigrid, which effectively deals with anisotropic matrices, transforms the geometric characteristics of unstructured grids into numerical relationships, distinguishes the degree of anisotropy of geometric grids through numerical values, and forms a strong-weak coupling relationship between elements. It is used to aggregate and generate coarse grid levels, which makes up for the defect that the cell-centric calculation format cannot effectively deal with high-ductility grids. In order to reduce the computational complexity of the coarse-grid layer and adapt to the calculation requirements of different dimensions, multiple strong coupling aggregations are used for high-ductility grid cells and cell-centric aggregations are used for other grid cells. Under the RGD model, the government pays attention to the improvement of environmental quality and land fiscal revenue. Residents pay attention to the level of demolition compensation and resettlement fees and the improvement of urban landscape functions. Developers pay attention to urban renewal and renovation costs, public participation, and coordination between new and old buildings. The government pays attention to the level of demolition compensation and resettlement fees and the cost of urban renewal and transformation, residents are concerned about the improvement of cultural education and the level of rental income, and developers are concerned about the improvement of traffic conditions, land utilization, and urban landscape functions. The government pays attention to the level of demolition compensation and resettlement fees and the status of land fiscal revenue, residents pay attention to public participation, and developers pay attention to land use. The comprehensive benefit evaluation of urban renewal is multidimensional, and comprehensive evaluation is carried out from the six dimensions of the social, economic, and environmental perspectives of the government, residents, and developers that coordinate the benefits and the social, economic, and environmental aspects of the development benefits. Social and people’s livelihood, economic development, environmental support, ecological balance, and historical and cultural inheritance are the core content of the evaluation system. The social and people’s livelihood is the foundation, economic development is an important condition, the environment is an important factor, and history and culture are the connotations. Urban renewal is not only about economic development but more concerned about the sustainable development of the society and the environment. Due to many factors, before starting an urban renewal project, the implementation plan should be comprehensively evaluated from multiple perspectives and dimensions and the plan and investment scale should be reasonably formulated to achieve the best goal of sustainable development.

An Econometric Model for the Analysis of the Influence of the Refurbishment Costs on Housing Prices

With reference to the Italian context, the present research intends to analyze the functional relationships between the unit cost of restructuring and the selling prices in the residential segment. The analysis has been contextualized to the three clusters (Northern Italy, Central Italy, Southern Italy and Islands) in which the Italian territory is commonly divided. The case study concerns 965 residential units sold in the first half of 2019 and located in the 103 provincial capitals. The implemented econometric technique is a data-driven method that employs a genetic algorithm and allows the identification of the most influencing factors among the explanatory variables considered. For each cluster, a model has been selected in order to study the influence of unit cost of restructuring on housing prices.

A meta-learning classification model for supporting decisions on energy efficiency investments

Energy efficiency is critical for meeting global energy and climate targets, requiring however significant investments. Due to the lack of mature decision-support systems and the utilization of traditional investment mechanisms that focus on the economical aspects of the energy efficiency projects and neglect their environmental impact, such projects can experience difficulties in being funded. In the interim, the impact of the digitization era is more apparent than ever, as algorithms and data availability and quality have significantly improved. This study aspires to bridge the gap in energy efficiency financing with the development of a data-driven methodology that labels energy efficiency investments based on their expected utility in terms of renovation cost and energy savings. Various machine learning classification methods are deployed and combined through a meta-learning model with the objective to improve overall classification performance and determine the funding that each investment should receive according to its particular characteristics. The proposed methodology is evaluated using a set of 312 projects that have been completed in Latvia. Our results indicate that the meta-learner outperforms all baseline classifiers, effectively identifying projects of high and medium potential and successfully distinguishing low from high potential ones.

Expediting the Cost Estimation Process for Aged-Housing Renovation Projects Using a Probabilistic Deep Learning Approach

Since the early 1980s, the Korean government has rapidly boosted residential buildings to cope with substantial housing shortages. However, as buildings have been aging simultaneously, the performance of a large number of residential buildings has deteriorated. A government plan to upgrade poor housing performance through renovation is being adopted. However, the difficulty of accurate construction cost prediction in the early stages has a negative effect on the renovation process. Specifically, the relationship between renovation design elements and construction work items has not been clearly revealed. Thus, construction experts use premature intuition to predict renovation costs, giving rise to a large difference between planned and actual costs. In this study, a new approach links the renovation design elements with construction work items. Specifically, it effectively quantifies design factors and applies data-driven estimation using the simulation-based deep learning (DL) approach. This research contributes the following. First, it improves the reliability of cost prediction for a data-scarce renovation project. Moreover, applying this novel approach greatly reduces the time and effort required for cost estimation. Second, several design alternatives were effectively examined in an earlier stage of construction, leading to prompt decision-making for homeowners. Third, rapid decision-making can provide a more sustainable living environment for residents. With this novel approach, stakeholders can avoid a prolonged economic evaluation by selecting a better design alternative, and thus can maintain their property holdings in a smarter way.

Data modelling and Remaining Useful Life estimation of rolls in a steel making cold rolling process

The economic cost of roll refurbishment in the steel-making industry is considerable. In a cold rolling mill, wear and damage of rolls disrupt the industrial environment, so it is critical to predict the remaining useful life early and change the roll without causing disruption to the manufacturing process. However, since cold rolling is a complex process affected by multiple variables which are operated in adverse conditions, it is very challenging to mathematically analyse the roll wear and failure. For this reason, in the present paper, a data-driven solution is proposed to predict the correct time for changing individual rolls. To develop an accurate predictive model, several datasets containing high-resolution production data and roll refurbishment data collected from a UK based steel plant have been acquired and processed in a way that the roll wear is modelled as a Remaining Useful Life (RUL) problem, where the number of coils that a roll is able to process is viewed as the remaining cycles. Then hybrid deep learning models are used to predict the Remaining Useful Life of rolls used in steel making. This novel data-driven approach achieves high prediction accuracy and has been validated on a real-world dataset. The proposed approach not only helps avoiding early failure but also can serve as a critical step towards the design of an optimal, automated maintenance schedule for the roll management.