| 1. |
- Camarasa, Clara, 1986, et al.
(författare)
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Diffusion of energy efficiency technologies in European residential buildings: A bibliometric analysis
- 2019
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 202
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Forskningsöversikt (refereegranskat)abstract
- Many studies have investigated different aspects in the decarbonisation of the European housing stock. However, a comprehensive quantitative analysis of the literature on the diffusion of energy efficiency technologies is still missing. We conducted a bibliometric analysis to better understand the knowledge base in the field energy efficiency technology diffusion in the European residential building stock. After the scanning and screening process, we identified 954 scientific articles pertinent to this topic. Through a co-citation network analysis, we generated a visual knowledge structure of the field and by the further investigation of the bibliography we were able to synthesize the state-of-the-art and answer to our initial research questions. Results of the co-citation network show a scattered and fragmented field in many domains. The descriptive analysis highlights this fragmentation, especially on a cross-country level among EU country members. Findings from this study contribute to map the scientific knowledge base in relation to technology diffusion in European residential building projects, identify relevant topic areas, visualize the links between the topics, as well as to recognize research gaps and opportunities. The methodology utilized in this paper proved to be viable approach to map and characterize the knowledge base within a field and can, therefore, be replicated in upcoming studies with analogous ambitions.
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| 2. |
- Camarasa, Clara, 1986, et al.
(författare)
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Specific Barriers to Massive Scale Energetic Refurbishment for Sample Markets in Europe
- 2015
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Ingår i: IFoU - 8th Conference of the International Forum on Urbanism.
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Konferensbidrag (refereegranskat)abstract
- International bodies such as the Intergovernmental Panel on Climate Change or the United Nations agree in seeing the built environment as one of the key sectors to mitigate emissions. Cost abatement curves as generated by McKinsey list a number of technologies in the building sector, which are already cost effective and are together potentially allowing for carbon mitigations of 2,0-3,0 Gtons of CO2eq per annum. Despite being economically attractive as well as desirable from a climate change mitigation viewpoint, almost none of these technologies are massively upscaling. The European Union requires the individual member countries to implement measures to speed up energy efficiency in the building sector. Each country however is free on the exact way how to do so as long as its specific approach is in line with the general EU road-map. This paper assesses the effect of the implemented frameworks for France and Germany and draws conclusions regarding immediate and future phenomenon. Findings are that both countries have implemented holistic frameworks that include legal standards, financial incentives and market education. While the German setup focuses on systemic solutions though, France promotes a component based subsidy scheme. In both countries the refurbishment rate on a component level is substantially higher than for deep renovation with window exchange and roof refurbishment being the most commonly implemented ones. Component based measures are higher in France than in Germany, in some cases even meeting the aimed for 3% needed for a refurbishment of the complete building stock by 2050 on an EU level. In general however both countries fail to achieve refurbishment and renovation rates that enable them to stand up to the EU 2050 targets yet, indicating that the market barrier and mechanisms have to be monitored and understood better to implement massive up-scaling of energy efficient technologies.
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| 3. |
- Fennell, P., et al.
(författare)
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Challenges and Lessons Learned in Applying Sensitivity Analysis to Building Stock Energy Models
- 2022
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Ingår i: Building Simulation Conference Proceedings. - : KU Leuven. - 2522-2708. ; , s. 2203-2210
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Konferensbidrag (refereegranskat)abstract
- Uncertainty Analysis (UA) and Sensitivity Analysis (SA) offer essential tools to determine the limits of inference of a model and explore the factors which have the most effect on the model outputs. However, despite a well-established body of work applying UA and SA to models of individual buildings, a review of the literature relating to energy models for larger groups of buildings undertaken by Fennell et al. (2019) highlighted very limited application at larger scales. This contribution describes the efforts undertaken by a group of research teams in the context of IEA-EBC Annex 70 working with a diverse set of Building Stock Models (BSMs) to apply global sensitivity analysis methods and compare their results. Since BSMs are a class of model defined by their output and coverage rather than their structure and inputs, they represent a diverse set of modelling approaches. Key challenges for the application of SA are identified and explored, including the influence of model form, input data types and model outputs. This study combines results from 7 different modelling teams, each using different models across a range of urban areas to explore these challenges and begin the process of developing standardised workflows for SA of BSMs.
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| 4. |
- Gontia, Paul, 1984, et al.
(författare)
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Material-intensity database of residential buildings: A case-study of Sweden in the international context
- 2018
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Ingår i: Resources, Conservation and Recycling. - : Elsevier BV. - 0921-3449 .- 1879-0658. ; 130, s. 228-239
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Tidskriftsartikel (refereegranskat)abstract
- © 2017 Elsevier B.V. Material intensity coefficient (MIC) databases are crucial for bottom-up material stock studies. However, MIC databases are site specific and not available in many countries. For this reason, a MIC database of residential buildings in Sweden was created in this study. As these had not previously been explored, considerable attention was paid to MIC database results, variables and limitations. Next, to contextualize the results, the database was compared and discussed with other studies in other geographical scales and regions. The MIC database is based on (1) specialized architectural-data and (2) densities of construction materials. The study looked at 46 typical residential buildings in Sweden, 12 single-family (SF) and 34 multi-family (MF) structures, built within the time period 1880ö2010. The results show specific trends for material intensity and composition, but also for the mass distribution of different building elements. Additionally, it was shown that the number of floors and the footprint size of a building have a considerable impact on the MICs, especially for buildings with a low number of floors, such as SF structures. Furthermore, when compared to MIC databases from other countries, the study database, which relates to Sweden, shows a higher intensity for wood and steel. Finally, contradictory MIC results for similar geographical regions were highlighted and discussed. This showed that to achieve consistent standardized MIC databases, further analysis of MIC databases for different geographical scales and regions are needed, and this is therefore recommended.
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| 5. |
- Jakob, Martin, et al.
(författare)
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CREATE: A toolbox to develop, implement and monitor advanced energy and climate goals and strategies
- 2019
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Ingår i: Eceee Summer Study Proceedings. - 2001-7960 .- 1653-7025. ; 2019-June, s. 785-792
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Konferensbidrag (refereegranskat)abstract
- Various environmental and regulatory changes, such as climate change mitigation strategies and market regulation, have increased the complexity of the challenges which cities, utilities, and real estate owners face. Thus, cities and their utilities are confronted with various problems: How, and at which costs can ambitious climate change mitigation goals be reached? How can urban planning be developed while simultaneously tackling climate change? How can the long-term economic and environmental performance of the building stock be optimized? How to plan electricity, gas, and thermal networks to suit future energy demand and the existing urban topology? These problems are usually addressed individually and independently from each other using instruments that lack an interdisciplinary approach. Data collections are often done “ad hoc” and not from a systemic point of view, resulting in datasets that are often incomplete, incoherent, and with different structures that make them difficult to merge. The paper describes the Carbon Resource Energy and Adaption Toolbox Europe (CREATE), a comprehensive modelling and data toolbox that can overcome these shortcomings. This toolbox has been developed to include elements that are specially conceived for various use cases of different decision makers (and their service providers): urban planners, energy utilities, network operators, building portfolio owners, building code designers, construction authorities, energy and climate policy makers. CREATE has three main elements: • Expert BSM: GIS-based scenario analysis tool for urban and utility energy planners, providing evaluation and management of energy demand, emissions, renewable energy resources, and other parameters. • Basic Web BSM: Simplified web-based spatial data information, monitoring and visualization tool for smaller municipalities and utilities. • Portfolio BSM: A portfolio assessment tool for real estate portfolio owners and manager to analyse the status quo of their portfolio and the possibility to develop short- and long-term strategies in terms of economic, energy and carbon performance. As such CREATE enables engagement between the various decision-making levels and bodies of cities and municipalities as well as (energy) utilities and building portfolio owners or real estate site developers.
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| 6. |
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| 7. |
- Kharseh, Mohamad, 1980, et al.
(författare)
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Feasibility of solar energy in south sweden: artificial neural network modeling
- 2016
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Ingår i: International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM. - 1314-2704. ; 3:BOOK 4, s. 273-280
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Konferensbidrag (refereegranskat)abstract
- Observations provide evidence that atmospheric greenhouse gases concentration has increased rapidly over last century. This leads to extreme climate changes such as heat waves, rising sea-levels, changes in precipitation resulting in flooding and droughts, intense hurricanes, and degraded air quality, affect directly and indirectly the physical, social, and psychological health of humans. For that reasons, and in helping achieving the EU targets for 2020 and 2050, utilizing the available local renewable energy resources is needed. Although the current efficiency of PV system (PVs) is still relatively low and the capital cost is still high, the abundance of solar energy that strikes the Earth continuously makes the photovoltaic systems viable alternative. The current work, therefore, investigate the potential of utilizing solar energy for electricity generation in Europe. For this aim, a residential building in Landskrona, Sweden, was chosen as a case study. Solar World SW325 XL, which is a monocrystalline module, was selected as PV panel. A computer model was built to simulate grid-connected rooftop PV system in which the module elements are attached to the roof of the building. Sensitive analysis was carried out to test the robustness of the simulation results. Performed calculations show that there is a big potential to use PVs with 193 kWh/y electricity can be generated per square meter of PV. The payback time of the systems is 6 years with levelized cost of electricity is 10.3 C/kWh. Finally, artificial neural network (ANN)-base model was built to generate user-friendly formula that states the relationship between the NPV (net present value) of PVs and specific factors of interest. These factors, including electricity price, real interest rate, module price and inverter price, were chosen based on sensitivity analysis results. The study leaded to create a simple formula that can easily be used to estimate the NPV of PVs without use of complicated software.
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| 8. |
- Kharseh, Mohamad, 1980, et al.
(författare)
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Humid Wall: Review on Causes and Solutions
- 2017
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Ingår i: Proceedings of the The World Sustainable Built Environment Conference 2017 (WSBE17). - 9789887794301 ; , s. 675-681
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Konferensbidrag (refereegranskat)
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| 9. |
- Kharseh, Mohamad, 1980, et al.
(författare)
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Identify Optimal Renovation Packages for Residential Buildings: A State-of-the-Art Computational Model
- 2019
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Ingår i: IOP Conference Series: Earth and Environmental Science. - : IOP Publishing. - 1755-1307 .- 1755-1315. ; 297:1
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Konferensbidrag (refereegranskat)abstract
- Renovating the existing building stock has a significant potential to achieve the goal of reducing greenhouse gas (GHG) emissions in the European Union. However, a common European renovation project focuses primarily on improving the thermal performance of the building shell by adding insulation to the opaque surfaces and improve the thermal performance of the windows. The potentially positive contribution of renewable energies (RE) in balance with energy efficiency measures is often underestimated. Consequently, a more holistic approach can contribute to a reduction in total net energy demand up to 40-45% for the entire buildings sector. Thus, in order to achieve the goal of GHG emission reduction in an economic most responsible way, the share of RE in a renovation project needs to be increased. However, building renovation projects are becoming - apparently - more complicated if more factors are considered in the planning of a renovation project. Thus, a computational tool for evaluating hundreds of different renovation options, including the implementations of renewable energy resources, to obtain an optimal or nearly optimal set of renovation options is essential. Therefore, a novel planning tool has been developed within the framework of DREEAM project, a project funded by the European Union within the Horizon 2020 research framework. The DREEAM-Tool has been designed in the way that it helps designers and other stakeholders to plan a renovation project of a single building or even on a multi-building scale. The tool was built in the way to optimize the renovation project taking into consideration the most critical factors in planning and decision-making processes, such as the economic or environmental performance. In other words, the tool combines an energy calculation model for a building or multiple building with an economic and environmental assessment to identify and optimize the most beneficial refurbishment solutions. The current study presents the concept of the DREEAM-Tool and shows examples of how the optimal renovation packages of a considered building will be determined and how this will support designers or buildings owners in decision-making processes.
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| 10. |
- Langevin, Jared, et al.
(författare)
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Developing a common approach for classifying building stock energy models
- 2020
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Ingår i: Renewable and Sustainable Energy Reviews. - : Elsevier BV. - 1879-0690 .- 1364-0321. ; 133
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Tidskriftsartikel (refereegranskat)abstract
- Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.
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| 11. |
- Nägeli, Claudio, 1987, et al.
(författare)
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A building specific economic building stock model to evaluate energy efficiency and renewable energy
- 2015
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Ingår i: Proceedings of CISBAT 2015, September 9-11.
-
Konferensbidrag (refereegranskat)abstract
- In developed countries, the residential and commercial building stock account for a considerable share of final energy demand and greenhouse gas emissions. Building stock modeling is an established tool to assess different development paths of buildings on city, region or country level. Current building stock models (BSM) as well as previous works of the authors, however, lack a holistic approach that take technological, economic and ecological factors into account on an individual building scale. There are, therefore, limitations in the conclusions that can be drawn. In order to increase their significance, current research shows trends towards spatial differentiation, representation of individual building and owners as well as economic decision modeling. However, no model combines all three aspects in a more holistic approach. This paper describes a novel approach which combines spatial differentiation with building specific heat demand modeling and an economic decision simulation. The model developed combines a building specific engineering model with a micro-economic discrete choice approach. Using spatial building data, the engineering model calculates space heat and hot water energy demand on a building level. The alteration of the building refurbishment state is modeled using a discrete choice approach to simulate the decision process of building owners of building envelope refurbish and/or to substitute the heating system. Due to the building specific approach, the decision model is able to take into account building specific information such as size, geometry, room temperature, investment, maintenance and energy costs and achievable energy savings as well as other factors such as local potentials and restrictions on the use of renewable energy. In a case study of the city of Zürich we demonstrate the feasibility and strengths of the new model approach. The results demonstrate that modeling space heating demand on an individual building scale yields specific heat demand distribution across building clusters (and not simply in average values as in other models). The building level approach enables the model to deliver differentiated results of the heat demand development for the whole building stock, building types building periods or spatially distributed as shown in the results.
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| 12. |
- Nägeli, Claudio, 1987, et al.
(författare)
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A Multidimensional Optimization Approach to Refurbishment Design on a Multi-Building Scale
- 2017
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Ingår i: Proceedings of World Sustainable Built Environment Conference 2017.
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Konferensbidrag (refereegranskat)abstract
- European countries face a large challenge in retrofitting their aging building stock, which they need to embark on, in order to reach European Union (EU) energy and emission reduction targets. Despite significant policy interventions, refurbishment rates remain low and the refurbishments that are carried out often do not meet the energy savings targeted by the EU, for example nearly Zero-Energy Building standards (nZEB). One of the key reasons for the lower than expected energy savings is that current refurbishment approaches tend to focus predominantly on energy efficiency improvements for individual buildings. The integrated energy systems perspective that can be leveraged at a multi-building scale – and is related to possible interactions between building sizes, scales, and the different systems – is not taken into consideration in most refurbishment concepts. The result are suboptimal renovation solutions which do not reach the full energy demand reduction potential of the refurbished building(s).This paper introduces a methodology for a tool that aims to develop economically and environmentally optimal nZEB refurbishment concepts for multi-building scale refurbishment actions. Increasing the scale of a refurbishment from a single building to a multiple building, or even a building portfolio, will allow to generate economies of scale (both for solution and workforce cost) and facilitate the integration of renewable energy generation. The tool applies the Lifecycle Assessment (LCA) and Lifecycle Cost Assessment (LCC) methods, which makes it possible to optimize refurbishment concepts, both with respect to economic and environmental criteria. Thanks to a multidimensional optimization approach, based on an evolutionary algorithm that can automatically find the Pareto-boarder for a given design space, Pareto-optimal refurbishment concepts are generated. Refurbishment options presented this way can help housing companies prioritize refurbishment needs and actions in their building portfolios, as well as evaluate and select between different refurbishment approaches in line with overarching targets.
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| 13. |
- Nägeli, Claudio, 1987, et al.
(författare)
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A service-life cycle approach to maintenance and energy retrofit planning for building portfolios
- 2019
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Ingår i: Building and Environment. - : Elsevier BV. - 0360-1323. ; 160
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Tidskriftsartikel (refereegranskat)abstract
- © 2019 The Authors Residential buildings account for almost a quarter of the total energy use in Sweden and building owners are, therefore, under pressure from policy makers to improve the energy performance of their buildings. Building portfolio owners (BPOs) generally face multiple barriers in energy efficiency investments such as financial constraints and lack of knowledge of the current state when planning energy efficiency measures. This paper presents a method for cost-optimal scheduling of maintenance and retrofit measures on a portfolio level by drawing on research on building stock modeling and maintenance retrofit planning. The method uses a building stock modeling approach to model costs, energy and greenhouse gas emissions (GHG)of a building portfolio and combines this with a method for optimal maintenance and retrofit scheduling in order to forecast and optimize the timing of measures on a building portfolio level. This enables the integrated long-term planning on retrofit investments and reduction of energy demand and GHG emissions for a portfolio of existing buildings. The application to the building portfolio of the municipal housing company of Gothenburg showed that by optimizing the maintenance and retrofit plans, ambitious retrofit measures can be introduced in the majority of the buildings with a positive effect on the service-life cycle costs. Moreover, the method is easily transferable to other building portfolios in Sweden as it builds up on nationally available data sets but is ideally complemented and verified using inspection data and existing maintenance plans of the BPOs in future applications.
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| 14. |
- Nägeli, Claudio, 1987, et al.
(författare)
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Best practice reporting guideline for building stock energy models
- 2022
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 260
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Tidskriftsartikel (refereegranskat)abstract
- Buildings are responsible for 38% of global greenhouse gas (GHG) emissions and, therefore, pathways to reduce their impact are crucial to achieve climate targets. Building stock energy models (BSEMs) have long been used as a tool to assess the current and future energy demand and environmental impact of building stocks. BSEMs have become more and more complex and are often tailored to case-specific datasets, which results in a high degree of heterogeneity among models. This heterogeneity, together with a lack of consistency in the reporting hinders the understanding of these models and, thereby, an accurate interpretation and comparison of results. In this paper we present a reporting guideline in order to improve reporting practices of BSEMs. The guideline was developed by experts as part of the IEA's Annex 70 and builds upon reporting guidelines from other fields. It consists of five topics (Overview, Model Components, Input and Output, Quality Assurance and Additional Information), which are further subdivided into subtopics. We explain which model aspects should be described in each subtopic, and provide illustrative examples on how to apply the guideline. The reporting guideline is consistent with the model classification framework and online model registry also developed in the Annex.
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| 15. |
- Nägeli, Claudio, 1987
(författare)
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Bottom-Up Modeling of Building Stock Dynamics - Investigating the Effect of Policy and Decisions on the Distribution of Energy and Climate Impacts in Building Stocks over Time
- 2019
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In Europe, residential and commercial buildings are directly and indirectly responsible for approximately 30–40% of the overall energy demand and emitted greenhouse gas (GHG) emissions. A large share of these buildings was erected before minimum energy-efficiency standards were implemented and are therefore not energy- or carbon-efficient. Consequently, buildings offer significant potential in terms of energy efficiency and the reduction of GHG emissions compared to the status quo. To make use of this potential at scale, targeted policy measures and strategies are needed that should be based on a quantitative assessment of the feasibility and impact of these measures. Building stock models (BSMs) have long been used to assess the current and future energy demand and GHG emissions of building stocks. Most common BSMs characterize the building stock through the use of archetype buildings, which are taken to be representative of large segments of the stock. The increasing availability of disaggregated datasets—such as building registries, 3D city models, and energy performance certificates—has given rise to building-specific BSMs focusing on describing the status quo as an input to energy planning, primarily on the urban scale. Owing to the availability of building-level data, BSMs can be extended beyond policy advice and urban planning, to the assessment of large building portfolios. Thus far, the advances made in building-specific BSMs on the urban scale have not been transferred to the national scale, where such datasets are often not available. Moreover, the focus on an increasingly detailed description of the existing stock has left approaches for modeling stock dynamics without much development. Stock dynamics, therefore, are still primarily modeled through exogenously defined retrofit, demolition, and new construction rates. This limits the applicability and reliability of model results, as the influence of economic, environmental, or policy factors on stock development is not considered. This thesis addresses these shortcomings and advances modeling practices in BSMs. The thesis with appended papers provides a methodology for how the modeling of national building stock can be further developed in terms of building stock characterization through synthetic building stocks as well as stock dynamics through the use of agent-based modeling. Furthermore, the thesis extends BSM applications to inform the strategic planning of large building portfolios through the integration of a maintenance and renovation scheduling method to project the future development of building portfolios.
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| 16. |
- Nägeli, Claudio, 1987, et al.
(författare)
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Building Stock Modelling - A novel instrument for urban energy planning in the context of climate change
- 2016
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Ingår i: Proceedings of IEECB 2016.
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Konferensbidrag (refereegranskat)abstract
- Cities and their building stock represent one of the largest energy consumer groups and emitters of greenhouse gases (GHG). The urban building stock, including commercial buildings, offers a large and mostly untapped potential for energy efficiency improvement and GHG mitigation. Urban development, building stock alterations, and building technology measures therefore play a major role in setting the framework to exploit these potentials. A way to describe possible building stock development pathways is through building stock modelling. Although there have been many different bottom-up approaches that model energy demand and GHG emissions as well as other aspects of urban development, they have not been fully integrated and are not giving community energy planners, urban planners and decision makers enough information to influence the development in specific areas and technological fields. The building stock model presented in this paper gives the possibility to model energy supply and demand of both the residential and non-residential building stock at the scale of individual buildings, taking into account both heating and cooling demand (and other energy services) of buildings of various types and age classes. The model allows for tapping into spatially differentiated potentials and to balance demand and supply and renewable energy source (RES) potentials at a local scale (typically small-scale neighbourhoods and hectares) to guide the planning and development of sustainable cities. It is shown that commercial buildings in particular play a key role in initiating thermal energy network approaches (e.g. local low-temperature networks). Furthermore, the possibility to connect with other models e.g. through the Smart Urban Adapt (SUA) modelling platform, makes it possible to run a fully integrated, bottom-up simulation of different urban development scenarios and their impact on energy demand and GHG emissions taking into account all aspects of urban development. The SUA modelling platform provides a highly integrated model, taking into account energy, land use and urban design, in order to investigate the socio-economic drivers of energy consumption. The results of a concrete case study revealed the benefit of integrating energy efficient commercial buildings with district energy systems that allow for tapping local potentials of renewable energy sources, for both heating and cooling.
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| 17. |
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| 18. |
- Nägeli, Claudio, 1987, et al.
(författare)
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Methodologies for Synthetic Spatial Building Stock Modelling: Data-Availability-Adapted Approaches for the Spatial Analysis of Building Stock Energy Demand
- 2022
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Ingår i: Energies. - : MDPI AG. - 1996-1073 .- 1996-1073. ; 15:18
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Tidskriftsartikel (refereegranskat)abstract
- Buildings are responsible for around 30 to 40% of the energy demand and greenhouse gas (GHG) emissions in European countries. Building stock energy models (BSEMs) are an established method to assess the energy demand and environmental impact of building stocks. Spatial analysis of building stock energy demand has so far been limited to cases where detailed, building specific data is available. This paper introduces two approaches of using synthetic building stock energy modelling (SBSEM) to model spatially distributed synthetic building stocks based on aggregate data. The two approaches build on different types of data that are implemented and validated for two separate case studies in Ireland and Austria. The results demonstrate the feasibility of both approaches to accurately reproduce the spatial distribution of the building stocks of the two cases. Furthermore, the results demonstrate that by using a SBSEM approach, a spatial analysis for building stock energy demand can be carried out for cases where no building level data is available and how these results may be used in energy planning.
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| 19. |
- Nägeli, Claudio, 1987, et al.
(författare)
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Policies to decarbonize the Swiss residential building stock: An agent-based building stock modeling assessment
- 2020
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Ingår i: Energy Policy. - : Elsevier BV. - 0301-4215. ; 146
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Tidskriftsartikel (refereegranskat)abstract
- In light of the Swiss government's reduction targets for greenhouse gas (GHG) emissions under the Paris Agreement, this article investigates how and with which policy measures these reduction targets can be met for the Swiss residential building sector. The paper applies an agent-based building stock model to simulate the development of the Swiss residential building stock under three different policy scenarios. The scenario results until 2050 are compared against the reduction targets set by the Swiss government and with each other. The results indicate that while the current state of Swiss climate policy is effective in reducing energy demand and GHG emissions, it will not be enough to reach the ambitious emission-reduction targets. These targets can be reached only through an almost complete phase-out of fossil-fuel heating systems by 2050, which can be achieved through the introduction of further financial and/or regulatory measures. The results indicate that while financial measures such as an increase in the CO2 tax as well as subsidies are effective in speeding up the transition in the beginning, a complete phase-out of oil and gas by 2050 is reached only through additional regulatory measures such as a CO2 limit for new and existing buildings.
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| 20. |
- Nägeli, Claudio, 1987, et al.
(författare)
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Synthetic building stocks as a way to assess the energy demand and greenhouse gas emissions of national building stocks
- 2018
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 173, s. 443-460
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Tidskriftsartikel (refereegranskat)abstract
- In Europe, the final energy demand and greenhouse gas (GHG) emissions of residential and commercial building stocks account for approximately 40% of energy and emissions. A building stock model (BSM) is a method of assessing the energy demand and GHG emissions of building stocks and developing pathways for energy and GHG emission reduction. The most common approach to building stock modeling is to construct archetypes that are taken to representing large segments of the stock. This paper introduces a new method of building stock modeling based on the generation of synthetic building stocks. By drawing on relevant research, the developed methodology uses aggregate national data and combines it with various data sources to generate a disaggregated synthetic building stock. The methodology is implemented and validated for the residential building stock of Switzerland. The results demonstrate that the energy demand and GHG emissions can vary greatly across the stock. These and other indicators vary significantly within common building stock segments that consider only few attributes such as building type and construction period. Furthermore, the results indicate a separation of the stock in terms of GHG emissions between old fossil fuel-heated buildings and new and refurbished buildings that are heated by renewable energy. Generating a disaggregated synthetic building stock allows for a discrete representation of various building states. This enables a more realistic representation of past building stock alterations, such as refurbishment, compared with commonly used archetypes, and not relying on more extensive data sources and being able to accommodate a wide variation of data types. The developed methodology can be extended in numerous manners and lays groundwork for future studies.
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| 21. |
- Nägeli, Claudio, 1987, et al.
(författare)
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Towards agent-based building stock modeling: Bottom-up modeling of long-term stock dynamics affecting the energy and climate impact of building stocks
- 2020
-
Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 211
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Tidskriftsartikel (refereegranskat)abstract
- Buildings are responsible for a large share of the energy demand and greenhouse gas (GHG) emissions in Europe and Switzerland. Bottom-up building stock models (BSMs) can be used to assess policy measures and strategies based on a quantitative assessment of energy demand and GHG emissions in the building stock over time. Recent developments in BSM-related research have focused on modeling the status quo of the stock and comparatively little focus has been given to improving the modeling methods in terms of stock dynamics. This paper presents a BSM based on an agent-based modeling approach (ABBSM) that models stock development in terms of new construction, retrofit and replacement by modeling individual decisions on the building level. The model was implemented for the residential building stock of Switzerland and results show that it can effectively reproduce the past development of the stock from 2000 to 2017 based on the changes in policy, energy prices, and costs. ABBSM improves on current modeling practice by accounting for heterogeneity in the building stock and its effect on uptake of retrofit and renewable heating systems and by incorporating both regulatory or financial policy measures as well as other driving and restricting factors (costs, energy prices).
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| 22. |
- Ostermeyer, York, 1976, et al.
(författare)
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Building Inventory and Refurbishment Scenario Database Development for Switzerland
- 2018
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Ingår i: Journal of Industrial Ecology. - : Wiley. - 1530-9290 .- 1088-1980. ; 22:4, s. 629-642
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Tidskriftsartikel (refereegranskat)abstract
- Material usage and the related embodied environmental impact have grown in significance in the built environment. Therefore, cities and governments need to develop strategies to reduce both the consumption of resources during usage phase as well as the embodied impact of the current building stock. This article proposes a new component-based building inventory database as a basis to develop such strategies using building stock modeling. The developed database clusters the building stock according to building typology (single- family houses, multifamily houses, and office buildings), age, and the main construction systems of the different building components. Based on the component makeup, it lists the necessary material input and waste output for different refurbishment options for each building component. The advantages of the proposed database structure are shown based on two applications for the developed database for Switzerland. The component- based database allows optimization of refurbishment strategies not only from an energetic perspective, but also with respect to materials, both on the input (sourcing of materials) and the output (waste streams) level. The database structure makes it possible to continuously extend the data set by adding new refurbishment options or add data such as component- specific lifetimes, costs, or labor intensities of the refurbishment options. In combination with an aligned economic model, this would give an even more holistic view, impact, and feasibility of different refurbishment scenarios both in environmental and economic terms. Introduction
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| 23. |
- Österbring, Magnus, 1986, et al.
(författare)
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Prioritizing deep renovation for housing portfolios
- 2019
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Ingår i: Energy and Buildings. - : Elsevier BV. - 0378-7788. ; 202
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Tidskriftsartikel (refereegranskat)abstract
- Cost-effectiveness of deep renovation has been assessed thoroughly on a building level. Such studies pro- vide limited guidance when prioritizing renovation measures for a building portfolio. On a stock level, building-stock modelling is commonly used to assess impact of renovation on a national and city level, targeting stakeholders operating at a planning or policy level. However, due to methodological choices and data availability, assessment of property owner portfolios is lacking. The aim of this paper is to cal- culate and spatially differentiate cost-effectiveness of deep renovation using equivalent annual cost and increase in assessed building value for a portfolio owner as a first step in prioritizing deep renovation within a building portfolio. A bottom-up engineering-based model is applied utilizing building-specific information for a municipal housing company portfolio in the City of Gothenburg, Sweden, consisting of 1803 multi-family buildings. Energy demand for space heating and hot-water is calibrated using mea- sured energy use from energy performance certificates. Deep renovation is assessed by applying a pack- age of measures across all buildings. Results show average energy use reduction across the portfolio of 51% to an average cost of 597 EUR/m 2 living area. While average energy cost savings account for 21% of equivalent annual cost, there are seven buildings where more than half the annual equivalent cost of renovation is covered by energy cost savings. Similarly, the distribution of change in assessed build- ing value is large for individual buildings, ranging from 0–23%. Aggregating results to larger areas tend to average out results while differences between individual buildings within areas persists. As such, the cost-effectiveness of deep renovation should be assessed on a building-by-building basis rather than for an area or neighbourhood. The results are intended as a first step in prioritizing deep renovation within a building portfolio and further detailed assessment is needed.
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