| 1. |
- Bozaghian Bäckman, Marjan, et al.
(författare)
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Bed material performance of quartz, natural K-feldspar, and olivine in bubbling fluidized bed combustion of barley straw
- 2024
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Ingår i: Fuel. - : Elsevier. - 0016-2361 .- 1873-7153. ; 364
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Tidskriftsartikel (refereegranskat)abstract
- The present study investigates how three different silicate-based bed materials behave in bubbling fluidized bed combustion of a model agricultural residue with respect to ash composition, namely barley straw. Quartz, natural K-feldspar, and olivine were all used in combustion at 700 °C, and the resulting layer formation and bed agglomeration characteristics were determined. Based on this, a general reaction model for bed ash from agricultural residues was proposed, taking into account the reactivity of the different silicates investigated towards the main ash-forming elements K, Ca, and Si. The proposed reaction model links bed material interaction with K-rich bed ash to the degree of polymerization of the silicate bed material, where addition reactions occur in systems with high polymerization, predominately in quartz, and substitution reactions dominate for depolymerized silicates such as K-feldspar and olivine.
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| 2. |
- Liu, Bokai, et al.
(författare)
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Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits : A case study in northern Sweden
- 2023
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Ingår i: Technology in society. - : Elsevier. - 0160-791X .- 1879-3274. ; 75
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an open digital ecosystem based on a web-framework with a functional back-end server for user-centric energy retrofits. This data-driven web framework is proposed for building energy renovation benchmarking as part of an energy advisory service development for the Västerbotten region, Sweden. A 4-tier architecture is developed and programmed to achieve users’ interactive design and visualization via a web browser. Six data-driven methods are integrated into this framework as backend server functions. Based on these functions, users can be supported by this decision-making system when they want to know if a renovation is needed or not. Meanwhile, influential factors (input values) from the database that affect energy usage in buildings are to be analyzed via quantitative analysis, i.e., sensitivity analysis. The contributions to this open ecosystem platform in energy renovation are: 1) A systematic framework that can be applied to energy efficiency with data-driven approaches, 2) A user-friendly web-based platform that is easy and flexible to use, and 3) integrated quantitative analysis into the framework to obtain the importance among all the relevant factors. This computational framework is designed for stakeholders who would like to get preliminary information in energy advisory. The improved energy advisor service enabled by the developed platform can significantly reduce the cost of decision-making, enabling decision-makers to participate in such professional knowledge-required decisions in a deliberate and efficient manner. This work is funded by the AURORAL project, which integrates an open and interoperable digital platform, demonstrated through regional large-scale pilots in different countries of Europe by interdisciplinary applications.
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| 3. |
- Penaka, Santhan Reddy, et al.
(författare)
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A data-driven framework for building energy benchmarking and renovation decision-making support in Sweden
- 2023
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Ingår i: SBE23-Thessaloniki. - : Institute of Physics (IOP).
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Konferensbidrag (refereegranskat)abstract
- In Europe, the buildings sector is responsible for 40% of energy use and more than 30% of buildings are older than 50 years. Due to ageing, a large number of houses require energy-efficient renovation to meet building energy performance standards and the national energy efficiency target. Although Swedish house owners are willing to improve energy efficiency, there is a need for a dedicated platform providing decision-making knowledge for house owners to benchmark their buildings. This paper proposes a data-driven framework for building energy renovation benchmarking as part of an energy advisory service development for the Vasterbotten region, Sweden. This benchmark model facilitates regional homeowners to benchmark their building energy performance relative to the national target and similar neighbourhood buildings. Specifically, based on user input data such as energy use, location, construction year, floor area, etc., this model benchmarks the user's building performance using two benchmark references i.e., 1) Sweden's target to reduce buildings by 50% energy use intensity (EUI) by 50% by 2050 compared to the average EUI in 1995, 2) comparing user building with the most relevant peer group of buildings, using energy performance certificates (EPC) big data. Several building groups will be classified based on influential factors that affect building energy use. Hence, this benchmark provides decision-making supportive knowledge to homeowners e.g., whether they need to perform an energy-efficient renovation. In the future, this methodology will be extended and implemented in the digital platform to provide helpful insights to decide on suitable EEMs. This work is an integral part of project AURORAL aims to deliver an interoperable, open, and integrated digital platform, demonstrated by cross-domain applications through large-scale pilots in 8 regions in Europe, including Vasterbotten.
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| 4. |
- Penaka, Santhan Reddy, et al.
(författare)
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Improved energy retrofit decision making through enhanced bottom-up building stock modelling
- 2024
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Ingår i: Energy and Buildings. - : Elsevier. - 0378-7788 .- 1872-6178. ; 318
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Tidskriftsartikel (refereegranskat)abstract
- Modelling the performance of building stocks is crucial in facilitating the renovation at the building stock level. Bottom-up building stock modelling begins by detailing individual buildings and then aggregates them into stock level. Its primary advantage lies in capturing the inherent heterogeneity among distinct buildings, which enables tailored retrofitting. Naturally, this approach requires a comprehensive dataset with detailed building information such as geometry and envelope thermal properties. However, a common challenge is the incompleteness of available data in individual datasets. To address this, previous bottom-up studies have filled the missing data with representative or statistical data. Such practice could lead to homogeneous modelling of distinct buildings within the same statistical group. This limits the utilization of key ability of bottom-up building stock modelling in capturing heterogeneity, such as tailored retrofitting to explore potential retrofitting areas and strategies. To address this challenge of homogeneous modelling, we utilize data fusion framework for bottom-up building stock modelling, employing probabilistic record linkage and inverse modelling techniques to integrate multiple incomplete building performance datasets. This framework fills the missing data in one dataset with information from another, thus capturing inherent heterogeneity in the building stock. An empirical study was conducted in Umeå, Sweden, to investigate the framework's effectiveness by modelling building stock with various retrofitting strategies. This study contribution lies in enhancing bottom-up building stock modelling by capturing inherent heterogeneity, to provide tailored retrofitting solutions.
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| 5. |
- Rebbling, Anders, 1980-, et al.
(författare)
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Demonstrating Fuel Design To Reduce Particulate Emissions and Control Slagging in Industrial-Scale Grate Combustion of Woody Biomass
- 2020
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Ingår i: Energy & Fuels. - : AMER CHEMICAL SOC. - 0887-0624 .- 1520-5029. ; 34:2, s. 2574-2583
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Tidskriftsartikel (refereegranskat)abstract
- The demand for increased overall efficiency, improved fuel flexibility, and more stringent environmental legislations promotes the development of new fuel- and technology-related concepts for the bioenergy sector. Previous research has shown that careful consideration of the fuel ash composition and the adjustment of the same via various routes, i.e., fuel design, have the potential to alter the ash transformation reactions, leading to, e.g., a reduction of the formation of slag or entrained inorganic ash particles. The objective of the present work was, therefore, to demonstrate the use of fuel design as a primary measure to reduce the emission of PM1 during combustion of woody biomass in medium-scale grate-fired boilers while keeping the slag formation at a manageable level. This was achieved by designing fuel blends of woody biomass with carefully selected Scandinavian peats rich in Si, Ca, and S. The work includes results from three experimental campaigns, performed in three separate grate-fired boilers of different sizes, specifically 0.2 MWth, 2 MWth, and 4 MWth. In one of the campaigns, softwood-based stemwood pellets were copelletized with different additions of peat (5 and 15 wt %) before combustion. In the other campaigns, peat was added in a separate fuel feed to Salix chips (15 wt % peat) and softwood-based stemwood pellets (10 and 20 wt % peat). Particulate matter and bottom ashes were characterized by scanning electron microscopy-energy-dispersive X-ray spectroscopy for morphology and elemental composition as well as by powder X-ray diffraction for crystalline phase composition. The results show that the fuel design approach provided PM1 reduction for all fuel blends between 30 and 50%. The PM1 reduction could be achieved without causing operational problems due to slagging for any of the three commercial boilers used, although an expected increased slagging tendency was observed. Overall, this paper illustrates that fuel design can be implemented on an industrial scale by achieving the desired ash transformation reactions, in this case, leading to a reduction of fine particulate emissions by up to 50% without any operational disturbances due to slag formation on the grate.
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| 6. |
- Rebbling, Anders, 1980-, et al.
(författare)
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Prediction of slag related problems during fixed bed combustion of biomass by application of a multivariate statistical approach on fuel properties and burner technology
- 2020
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Ingår i: Biomass and Bioenergy. - : Elsevier. - 0961-9534 .- 1873-2909. ; 137
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Tidskriftsartikel (refereegranskat)abstract
- Slag is related to the melting properties of ash and is affected by both the chemical composition of the fuel ash and the combustion parameters. Chemical analysis of slag from fixed bed combustion of phosphorus-poor biomass show that the main constituents are Si, Ca, K, O (and some Mg, Al, and Na), which indicates that the slag consists of different silicates. Earlier research also points out viscosity and fraction of the ash that melts, as crucial parameters for slag formation. To the authors’ knowledge, very few of the papers published to this day discuss slagging problems of different pelletized fuels combusted in multiple combustion appliances. Furthermore, no comprehensive classification of both burner technology and fuel ash parameters has been presented in the literature so far. The objective of the present paper was therefore to give a first description of a qualitative model where ash content, concentrations of main ash forming elements in the fuel and type of combustion appliance are related to slagging behaviour and potential operational problems of a biomass fuel in different small- and medium scale fixed bed appliances.Based on the results from the combustion of a wide range of pelletized biomass fuels in nine different burners, a model is presented for amount of slag formed and expected severity of operational problems. The model was validated by data collected from extensive combustion experiments and it can be concluded that the model predicts qualitative results.
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