Retrofit Planning Research Articles

Transforming homes, transforming lives: The role of property logbooks in scaling retrofit

The pace of good quality retrofit must be urgently scaled up across the UK, in order to tackle fuel poverty, improve the health and comfort of our homes, increase energy security and build climate resilience. Currently, however, incomplete information is used when designing retrofit policies and plans. There are barriers to the scale-up of good quality retrofit including citizen engagement, finance, supply chain uncertainty, a lack of trust and low uptake of quality assurance frameworks. This paper discusses the potential of enhanced, interoperable and democratised building, local and systems data to unlock many of these barriers. It will explore how the adoption of property logbooks across the UK can enable the aggregation of projects and drive access to finance. A retrofit plan for every home has the potential to engage and empower citizens and small to medium enterprise (SME) builders to act locally. This paper describes how the right packages of data can inform better decisions, what work has already been done to date, and how you can get involved in creating transformational change.

Energy-saving and economic analysis of the data center cooling system using magnetic bearing chillers under different climate conditions

Magnetic bearing chiller has excellent Coefficient of Performance, but the high initial investment makes it challenging to find a balance between energy-saving efficiency and economic potential. This paper proposes two energy-saving retrofits with water-side economizers, using efficient centrifugal chillers (Plan 1) and magnetic bearing chillers (Plan 2), respectively, to replace the existing cooling system of a case data center in Nanchang. Energy models of three cooling systems are developed to analyze the energy efficiency and performance. Compared to the existing cooling system, the operation time of Full free cooling and Partial free cooling for Plan 1 and Plan 2 reach 2489 and 1324 h, respectively. Result in energy savings of 63.19 % and 64.54 %, and power usage effectiveness reduce 0.341 and 0.349, respectively. Because the annual chiller COP of Plan 2 is 6.7 % higher than that of Plan 2, Plan 2 saves additional 3.96 % annual energy consumption compared to Plan 1. Furthermore, the energy-savings and economy of the retrofit plans in five typical climate cities in China are discussed. The energy savings rates for Plan 1 and Plan 2 are 61.4%–64.7 % and 62.1%–65.6 %, respectively, and their dynamic payback periods are 2.02–5.15 years and 2.16–5.6 years.

Simulating urban energy use under climate change scenarios and retrofit plans in coastal Texas

Rapid urbanization, climate change, and aging infrastructure pose significant challenges to achieving sustainability and resilience goals in urban building energy use. Although retrofitting offers a viable solution to mitigate building energy use, there has been limited analysis of its effects under various weather conditions associated with climate change in urban building energy use simulations. Moreover, certain parameters in energy simulations necessitate extensive auditing or survey work, which is often impractical. This research proposes a framework that integrates various datasets, including building footprints, Lidar data, property appraisals, and street view images, to conduct neighborhood-scale building energy use analysis using the Urban Modeling Interface (UMI), an Urban Building Energy Model (UBEM), in a coastal neighborhood in Galveston, Texas. Seven retrofit plans and three weather conditions are considered in the scenarios of building energy use. The results show that decreasing the U-value of building envelopes helps reduce energy use, while increasing the U-value leads to higher energy consumption in the Galveston neighborhood. This finding provides direction for coastal Texas cities, like Galveston, to update building standards and implement retrofit measures.

An Expert View on Data and Modelling for Planning Domestic Retrofit

The transition to Net Zero rests partly on the widespread adoption of energy-efficient retrofit measures for domestic dwellings. The scale of retrofit efforts is extensive, as up to 80% of the UK’s domestic housing stock for 2050 has already been built. To address the scope, data and models will play a crucial role in informing design decisions and optimising retrofit strategies. While new methods and tools for data and modelling in retrofit continue to be developed, the perspectives of professionals using these tools on their quality remain mainly absent from discussion across academia and practice. This study investigated the experiences and perceptions of data and modelling from professionals working in the planning stages of domestic retrofit, serving as a needs-finding exercise driving retrofit planning. Through semi-structured interviews and qualitative coding, the results highlight a critical trade-off between precision, confidence, and the burden of data collection. These findings underscore the need to balance precision, ease of use, and adaptability in data and modelling retrofit tools. Issues around data availability and wider access to data and modelling results across stakeholders emerged as a missed opportunity.

Rapid rehabilitation of damaged UHPC-NSC composite pier after earthquake

Resilience-oriented earthquake engineering requires that engineering structures can recover rapidly after earthquakes. However, the rehabilitation time of bridge piers is strongly dependent on the structure and retrofit plan. Although an ‘ultra-high-performance concrete (UHPC) – normal strength concrete (NSC)’ composite pier, with a cross-section of an outer UHPC tube and inner NSC core, can deliver satisfactory damage control, its post-earthquake rehabilitation has not been reported. This study investigated the rehabilitation performance of damaged UHPC-NSC composite piers. Six damaged composite piers were retrofitted, and cyclic tests were conducted to compare the performance of the retrofitted and original specimens. The actual compressive strength of the re-poured UHPC significantly affected the performance of the retrofitted composite piers. Parametric analysis was conducted based on the validated numerical model to investigate the impact of the rehabilitation time on the retrofitted performance quantitatively. The functions of the critical rehabilitation time were derived with respect to the strength and thickness of the re-poured UHPC, considering the full recovery of the initial stiffness and peak strength as the criteria.

Influence of urban density on energy retrofit of building stock: case study of Spain

ABSTRACT Energy retrofitting of existing buildings plays a key role in the European targets of Green House Gas reduction. The addition or substitution of construction materials is needed to improve energy performance of buildings and its environmental impact must be considered. This paper proposes a model for the assessment of the environmental impact of neighborhood retrofit in relation with urban density. The model is based on the decomposition of buildings into functional elements and the quantification of construction materials used in building energy retrofitting. As a novelty, the need of road rehabilitation was also considered. The environmental impact was assessed in terms of Embodied Energy (EE) and Embodied Carbon (EC). The operational energy after retrofit was also calculated. The results bring the evidence of the relation between the urban density and the EE and EC derived from building retrofit, which can be up to 60% higher in low density areas. The sensitivity analysis carried out demonstrates the influence of the urban compactness on the environmental assessment results. The model proposed can assist in the design of retrofit plans at urban level by highlighting those retrofit measures with most significant environmental impact depending on the urban density.

Key Performance Indicators for Decision Support in Building Retrofit Planning: An Italian Case Study

To achieve climate and energy goals in the building sector, the current pace of renovating existing structures must double, overcoming prevailing barriers. Key Performance Indicators play a pivotal role in science-based decision making, emphasizing both direct and indirect benefits of building retrofits. The authors aim to contribute to proper metric identification for multi-perspective building performance assessment and formulate a methodology supporting energy planning decisions. They introduce the Global Cost per Emission Savings (GCES), an aggregated indicator encompassing both public (CO2 emissions) and private (global cost) perspectives of diverse retrofit technologies for building HVAC systems. Applied to the Italian residential building stock via the Reference Building approach, the methodology is tested using condensing gas boilers, biomass boilers, and electric heat pumps, revealing diverse environmental and economic performances. Addressing the establishment of effective decision-support tools for policymakers, the paper explores the potential impact of various policies on the favorability of technologies. Different policy scenarios are delineated to analyze how distinct approaches may influence the attractiveness of technologies. Notably, in the baseline scenario, biomass boilers hold an advantage over heat pumps according to the GCES index. However, scenarios involving technology-specific incentives or a greenhouse gases emission tax failed to alter the technological ranking, leaving heat pumps financially uncompetitive. In contrast, the TXPM scenario positions heat pumps as the most financially appealing option, penalizing biomass boilers for high particulate matter emissions.

Retrofit Planning and Flexible Operation of Coal-Fired Units Using Stochastic Dual Dynamic Integer Programming

The continuous growth of wind power requires greater power system operational flexibility owing to the variability and uncertainty of wind power generation. Retrofitting existing coal-fired units is a demonstrated cost-effective method for improving system flexibility. This study proposes a decision support tool that provides optimal investment decisions to enhance power system operational flexibility. A novel flexibility retrofit planning (FRP) model is proposed in which the embedded operational problem is a stochastic mixed-integer nonlinear programming (SMINLP) unit commitment problem. In the operational unit commitment model, novel mixed-integer nonlinear formulations are proposed to represent the coal-fired unit attribute (minimum power output, startup and shutdown times, and maximum ramp rate) modifications after retrofitting. A new solution method based on the Benders decomposition (BD) and stochastic dual dynamic integer programming (SDDIP) algorithms is proposed to solve the proposed FRP model. The modified IEEE 39-bus, 57-bus, and 118-bus test systems were used to verify the effectiveness of the proposed model and solution method. The results demonstrate that the proposed FRP model can balance the retrofitting and operational costs to minimize the total cost and accommodate more wind generation. The proposed solution method is computationally efficient for solving FRP models.

Hybrid energy system calculation tool for early stage building retrofit planning

A dynamic Python-based calculation tool has been developed in the HybE project to calculate the hourly and life cycle impact of building hybrid energy systems. The model is fed with hourly energy consumption data and hourly weather data to perform parametric analysis for the emission and cost impacts of various hybrid energy systems. The tool can be used in the project definition phase to examine the potential of hybrid energy systems before a more detailed full building energy modelling with commercial tools.

Evaluation of the embodied carbon of insulation in achieving a national retrofit plan in Ireland: Probono case study and the national perspective

Overall, the building and construction sector, in Ireland, was responsible for 23 % of final energy use and 37 % of carbon dioxide (CO2) emissions in 2021. Ireland boasts some of the most ambitious targets for Greenhouse Gas (GHG) emission reduction to 2030 in the world. In Ireland, emissions related to the operation of the residential sector receive particular attention, and the government have introduced a National Retrofit Plan that aims to retrofit 500,000 (~25%) of the national housing stock by 2030. However, carbon emissions related to the achievement of this retrofit have not been quantified. This paper aims to outline the initial steps in evaluating the embodied carbon input of achieving a national retrofit plan of this unprecedented scale. Also, it aims to assess the relative carbon savings resulting from the production of materials to achieve retrofit plan. In the first stage, a case study of social housing, used in Probono project within the Dun Laoghaire Rathdown (DLR) local authority of Dublin City in Ireland is investigated as a best practice template for future retrofit projects. The embodied carbon of retrofit is evaluated. Then, a large housing sample set of DLR is evaluated in terms of Building Energy Rating (BER). This sample set is compared with the BER ratings of national stock to evaluate its representativeness. The results indicate that most of the dwellings on the sample set of DLR, in line with the national stock, are C and D rated and need to be retrofit to achieve B rating or better. In the final section, four types of nominal dwellings in Ireland are selected to evaluate the required volumes of thermal insulation and the added embodied carbon of retrofit to reach the national retrofit plan. The results demonstrate that ~30 million m3 of thermal insulation will be required for the national retrofit plan and it will add ~2 MtCO2 of the embodied carbon.

Planning home energy retrofit in a social environment: The role of perceived descriptive and injunctive social norms

In the built environment, improving the energy efficiency of existing building stock through retrofitting is the top pillar to mitigate climate change. Despite the efforts made by local authorities to provide technical and financial supports, the home energy retrofit rate remains low. This study aims to improve the understanding of how homeowners make their energy retrofit plans in a social environment, thereby informing behavioural policy (re)design. Using a sample of inexperienced retrofitters among Dutch homeowners (N = 556), we investigate the relationship between perceived social norms and energy retrofit plans. The results show that homeowners who perceive a positive injunctive norm have an 11.8 percentage point higher probability of making a home energy retrofit plan compared to those with a non-positive perception. Perceived injunctive norms are also significantly associated with the number of planned retrofit measures and aligned with multiple direct barriers and motivations for retrofitting. However, perceived descriptive norms are only associated with the number of planned retrofit measures, and are even correlated with stronger perceived barriers. We conclude by discussing different social influence pathways of descriptive and injunctive norms, as well as the potential of leveraging social norms as a behavioural policy intervention to promote home energy retrofit.

Optimal decarbonization strategies for existing districts considering energy systems and retrofits

Integrated energy system planning at the district level can contribute towards the sustainable transformation of the building sector by unlocking solutions beyond individual buildings. This is particularly true for existing districts, whose older buildings have a low energy performance and for which measures to reduce the energy demand and ensure a low-emission energy supply must be implemented. In the urban context, district heating networks (DHN) are a promising way of doing the latter, especially with carbon capture and storage (CCS) on the horizon. However, investment decisions for both types of measures – energy supply and demand reduction – must consider individual buildings as part of district-scale considerations as building-level demand-side interventions affect energy demand patterns and densities. These can in turn affect energy supply decisions at the district-level.This study presents a comprehensive methodology for determining optimal decarbonization strategies for existing districts while considering building-level energy supply and retrofitting investment decisions and the expansion of existing DHN. We do so by extending the MANGOret (Multi-stAge eNerGy Optimization - retrofitting) optimization framework for the long-term investment planning of building-level multi-energy systems and envelope retrofits. In addition, the study presents an approach for modeling CCS as an emission-reduction technology for the waste incinerator supplying the marginal expansion of the district heating network.The developed optimization model considers a long-term time horizon with multiple investment stages, allowing it to represent economic and technological developments over the model time horizon. It incorporates a multi-objective perspective, capturing the trade-offs between the total system costs and emissions. The model is applied to two existing case study neighborhoods in the city of Chur, Switzerland. The long-term energy system design and operation for the two neighborhood typologies – mixed-use and residential – are analyzed as part of the DHN expansion investment decision.The results show that retrofitting is the main cost driver of any decarbonization strategy. Therefore the choice and the size of the energy systems offer better leverage for reducing emissions with a moderate increase in costs. In dense inner-city neighborhoods with high heating demands, district heating is the cost-optimal heating choice. Together with a low-emission district heating source such as a waste incinerator with CCS or biomass, it also becomes the CO2-optimal choice. Furthermore, the case studies demonstrate that a combination of heat pumps, hot water thermal storage, and solar PV is not only the CO2-optimal but also the cost-optimal decentralized heating option if no DHN is available. This highlights the attractiveness of energy-efficient heating systems already today.

Retrofit Analysis of City-Scale Residential Buildings in the Hot Summer and Cold Winter Climate Zone

The rising energy consumption in residential buildings within the hot summer and cold winter (HSCW) climate zone, driven by occupants’ pursuit of improved thermal comfort, necessitates effective energy conservation measures. This study established urban building energy models for 32,145 residential buildings in Changsha City, China, and conducted a comprehensive retrofit analysis of seven energy conservation measures (ECMs). Additionally, the study assessed the impact of residents’ conscious energy-saving behaviors concerning air conditioner (AC) control. The research commenced by creating six baseline models representative of the diverse building stock. Identifying seven commonly used ECMs, the study examined the potential of each measure for enhancing energy efficiency. To facilitate the analysis, a dedicated toolkit, AutoBPS-Retrofit, was developed to efficiently modify the baseline model for each ECM. Furthermore, the investigation delved into the investment cost of implementing the ECMs and evaluated their simple payback year (PBP) and net present value (NPV). The results demonstrate that tailored retrofit plans are essential when addressing envelope improvements, varying according to building types and ages. Retrofits targeting lighting systems offer both promising energy savings and favorable economic viability, albeit subject to residents’ preferences. Alternatively, upgrading the AC systems emerges as the most energy-efficient approach, yet the economic assessment raises concerns. The study’s findings offer practical insights for governments seeking to establish effective carbon reduction goals and policies. Moreover, the research can assist energy-saving institutions, real-estate companies, and stakeholders involved in renovation projects by offering guidance in making informed decisions to enhance energy efficiency in city-scale residential buildings.

Multipath retrofit planning approach for coal-fired power plants in low-carbon power system transitions: Shanxi Province case in China

Multipath retrofit planning approach for coal-fired power plants in low-carbon power system transitions: Shanxi Province case in China

Improving the Energy Performance and Economic Benefits of Aged Residential Buildings by Retrofitting in Hot–Humid Regions of China

The existing building stock faces the challenge of low energy efficiency and requires renovation and upgrading to meet society′s goals of carbon reduction and sustainable development. This study presents an optimization framework utilizing genetic algorithms to develop robust retrofit plans that balance the need for improved energy efficiency, cost-effectiveness considerations for householders, and uncertainties regarding climate conditions. A case study of an aged residential building in a hot and humid region of China is used to demonstrate the proposed method. The optimization results show a potential energy demand reduction of 81.5%. However, due to the relatively long time required to realize economic benefits from high investments, short-term optimization tends to favor solutions with high energy demand and low primary costs. To effectively reduce carbon emissions, it is recommended to consider the long-term economic benefits of retrofits and prioritize solutions with high energy efficiency. However, it is important to acknowledge that the expensive nature of retrofit investments may pose barriers to residents. Society should provide adequate support and guidance to facilitate residential renovation efforts.

Comparison of Numerical Strategies for Historic Elevated Water Tanks: Modal Analysis of a 50-Year-Old Structure in Italy

The seismic vulnerability assessment of existing structures is a well-known challenging task, due to a combination of several aspects. The use of analytical or finite element (FE) numerical models can offer robust support in this analysis but necessitates the accurate calibration of geometrical and mechanical input, with related uncertainties. In this paper, attention is focused on the identification of dynamic parameters, based on modal numerical analysis, of a 50-year-old, reinforced concrete, elevated water tank (EWT) characterised by a reservoir with a truncated cone shape. The structure is located in a high seismic region of northern Italy and presently necessitates retrofit plans to preserve its functionality. Based on the limited available experimental evidence and technical drawings, major efforts are spent for the numerical prediction of fundamental vibration modes and frequencies of the structure, which represent a first key step for seismic analyses, under various water-filling levels. To this aim, four different FE numerical strategies able to include both structural features and possible fluid–structure interaction (FSI) effects are developed. By progressively increasing the computational cost (and expected the accuracy of the solutions), FE models based on added-mass (M0 model), spring-mass (M1-DM or M1-DS models), or acoustic (M2 model) strategies are taken into account and combined with increasing detailing in geometrical description of the structure. Results from parametric modal analyses are discussed for the case-study EWT, in terms of computational cost, possible numerical limitations, accuracy of predicted frequencies/modal shapes, sensitivity to water-filling levels and operational configurations, with the support of several pieces of experimental evidence and consolidated analytical formulations for fundamental frequency estimations.

A Multi-Stage Decision Framework for Optimal Energy Efficiency Measures of Educational Buildings: A Case Study of Chongqing

Buildings consume large amounts of energy resources and emit considerable amounts of greenhouse gases, especially existing buildings that do not meet energy standards. Building retrofitting is considered one of the most promising and significant solutions to reduce energy consumption and greenhouse gas emissions. However, finding suitable energy efficiency measures for existing buildings is extremely difficult due to the existence of thousands of retrofit measures and the need to meet various objectives. In this paper, a multi-stage decision framework, including a multi-objective optimization model, and a ranking method are proposed to help decision-makers select the optimal energy efficiency measures. The multi-objective optimization model considers the economic and environmental objectives, expressed as the retrofit cost and energy consumption, respectively. The entropy weight ideal point ranking method, an evaluation and ranking method that combines the entropy weight method and ideal point method, is adopted to sort the Pareto front and make a final decision. Then, the proposed decision framework was implemented for the retrofit planning of an educational building in Chongqing, China. The results show that decision-makers can quickly identify near-optimal energy efficiency measures through multi-objective optimization and can select suitable energy efficiency measures using the ranking method. Moreover, energy consumption can be reduced by building retrofitting. The energy consumption of the case building was 64.20 kWh/m2 before retrofitting, and the value can be reduced by 6.79% through retrofitting. Furthermore, the reduction in building energy consumption was significantly improved by applying the decision framework. The highest value of energy consumption was 59.84 kWh/m2, while the lowest value was 27.11 kWh/m2 when implementing the multi-stage decision framework. Thus, this paper provides a useful decision framework for decision-makers to formulate suitable energy efficiency measures.

Effects of latitude and building orientation in indoor-illuminance levels towards energy efficiency

As a matter of concern in sustainable buildings, daylight is studied to improve the balance between visual comfort for the occupants and energy consumption. This study analyzed the effects of latitude and orientation on the sunlight illuminance level within a northwest/southeast-oriented hypothetical house, with a wide-glassed façade, by integrating the BIM and BEM methodologies. The house was located in five different locations showing different latitudes: Búzios, Brazil; Capri, Italy; Punta Cana, Dominican Republic; Dubai, United Arab Emirates; and Sydney, Australia. Five different studies were carried out for each one of them by using the Autodesk REVIT energy-analysis tool named Lighting; they included sun-path analysis, calculation of daylight factor and daylight autonomy, and evaluation of daylight illuminance levels. It was found that a high amount of sunlight enters the house on its rear side, where are located the most occupied rooms, predominantly in the summer season, in the afternoon hours; however, 67% of the total house is below the 2% of daylight factor threshold. Withal, the rear-side rooms are the ones that satisfy most of the time with illumination levels above 300 lux, with maximum levels varying according to the season. This research contributes to associating BIM and BEM methodologies as an option to improve the design of energy-efficient buildings, being possible to consider further improvements to enhance the illuminance in the rooms, both for the early design stages and for future retrofit plans.

국공립 어린이집 그린리모델링 사업의 리트로핏 대안별 에너지 성능 및 경제성 비교 분석 : 단일 사례의 시뮬레이션 기반 분석 중심으로

Purpose: The purpose of this study was to present an optimized green remodeling retrofit plan through energy performance and economic analysis of the public daycare center for which green remodeling has been completed. Method: By collecting data on public building green remodeling project management in 2020 from the Korea Authority of Land & Infrastructure Safety, target daycare centers that are single-use and can collect monthly building energy consumption data through a public data open system were extracted. The building outline and operating conditions were investigated, and energy performance was analyzed using Design Builder, a dynamic building energy analysis program. After calibration, an alternative model analysis for each technical element was performed, including the basic base model. Then, economic analysis was performed using the net present value method. Result: The results of this study were as follows. After comprehensively analyzing energy performance and economic feasibility, ALT-4(heat recovery ventilation system), ALT-9 (heat recovery ventilation system+high-efficiency air conditioning+LED lighting replacement), ALT-6(LED lighting replacement) models were determined by the final priority. ALT-4(heat recovery ventilation system) as a single element model and ALT-9(heat recovery ventilation system+high-efficiency air conditioner+LED lighting replacement) as a combined element model were the best alternative when comprehensively considering energy performance and economic feasibility in green remodeling.

Improved locust swarm optimization algorithm applied for building retrofitting based on the green policy of buildings

Regarding the high costs associated with retrofitting buildings, finding an optimal retrofit plan considering existing buildings' environmental effects is critical. Each building following the green policy of buildings should gain a particular rate of EPC. In this paper, the most appropriate defined retrofit options are selected by the decision-makers for the building retrofits based on an optimization model. To assist decision-makers in have sensible decisions, the model incorporates economic analysis. A new algorithm called Improved Locust Swarm Optimization is used to retrofit an existing office building as a studied case. By incorporating the envelope components and indoor facilities into the model, optimal retrofit plans are systematically determined for an entire building. Electricity produced from fossil fuels decreased by utilizing a solar PV system on the roof. As a result, the concept of a zero-energy building with the lowest environmental concerns is achievable by reducing the use of nonrenewable energy in buildings. The model breaks down a long-term investment into yearly short-term investments to make investments further appealing to investors. Investments have an extended payback time that is offset by a government tax incentive program. The results indicate that 761.6 MWh of energy can be saved with a 70-month payback period and a rating form of EPC, demonstrating the model's effectiveness. Environmental concerns, such as excessive fossil fuel use and CO2 emissions, have significantly decreased.