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  • 1.
    Andersen, Martin
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology. Dept. of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg.
    Bales, Chris
    Dalarna University, School of Information and Engineering, Energy Technology.
    Dalenbäck, J. -O
    Economic Analysis of Heat Distribution Concepts for a Small Solar District Heating System2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 13, article id 4737Article in journal (Refereed)
    Abstract [en]

    One challenge in today’s district heating systems is the relatively high distribution heat loss. Lowering distribution temperatures is one way to reduce operational costs resulting from high heat losses, while changing the distribution system from steel pipes to plastic pipes and changing the heat distribution concept can reduce investment costs. The result is that the overall life cycle cost of the district heating system is reduced, leading to the improved cost competitiveness of district heating versus individual heating options. The main aim of this study was to determine the most cost-efficient distribution system for a theoretical solar district heating system, by comparing the marginal life cycle cost of two different distribution systems. A secondary aim was to determine the influence of the employed pipe type and insulation level on the marginal life cycle cost by comparing detailed economic calculations, including differences in pipe installation costs and construction costs, among others. A small solar-assisted district heating system has been modeled in TRNSYS based on a real system, and this “hybrid” model is used as a basis for a second model where a novel distribution system is employed and the heating network operating temperature is changed. Results indicate that a novel distribution concept with lower network temperatures and central domestic hot water preparation is most efficient both from an energy and cost perspective. The total life cycle costs vary less than 2% for a given distribution concept when using different pipe types and insulation classes, indicating that the investment costs are more significant than operational costs in reducing life cycle costs. The largest difference in life cycle cost is observed by changing the distribution concept, the novel concept having approximately 24% lower marginal life cycle cost than the “hybrid” system. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

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  • 2.
    Andersen, Martin
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology. Chalmers University of Technology, Gothenburg.
    Bales, Chris
    Dalarna University, School of Information and Engineering, Energy Technology.
    Dalenbäck, Jan-Olof
    Chalmers University of Technology, Gothenburg.
    Heat distribution concepts for small solar district heating systems – Techno-economic study for low line heat densities2022In: Energy Conversion and Management: X, ISSN 2590-1745, Vol. 15, article id 100243Article in journal (Refereed)
    Abstract [en]

    The high operating temperatures in today’s district heating networks combined with the low energy demand of new buildings lead to high relative network heat losses. New networks featuring lower operating temperatures have reduced relative heat losses while enabling an increase in the use of solar heat. The primary aim of this study was to determine if a particular district heating system can be made more effective with respect to heat losses and useful solar energy, by considering different distribution concepts and load densities. A small solar assisted district heating system with a novel hybrid distribution system has been modelled based on a real case study. This model serves as a basis for two other models where the distribution system and heating network operating temperature is changed. A secondary aim of the study was to determine the economic implications of making these changes, by using costs estimates to calculate the contribution of essential system components to total system cost. Results indicate that a novel distribution concept with lower network temperatures and central domestic hot water preparation is most energy efficient in a sparse network with a heat density of 0.2 MWh/m∙a and a performance ratio of 66%, while a conventional district heating system performs worst and has a performance ratio of less than 58% at the same heat density. In an extremely sparse network with heat density of 0.05 MWh/m∙a, the performance ratio is 41% and 30% for these systems, respectively. A simple economic analysis indicates that the novel distribution concept is also best from an economic point of view, reducing the initial investment cost by 1/3 compared to the conventional concept, which is the most costly. However, more detailed calculations are needed to conclude on this.

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  • 3.
    Andersson, Mikael
    et al.
    Dalarna University, School of Information and Engineering, Construction.
    Barrioz, Gabriel
    Borlänge kommun.
    Nordström, Louise
    Borlänge kommun.
    Ranhagen, Ulf
    Dalarna University, School of Information and Engineering, Construction.
    Svensson, Tony
    Dalarna University, School of Information and Engineering, Construction.
    Rönnelid, Mats
    Dalarna University, School of Information and Engineering, Energy Technology.
    Energiinnovation Jakobsdalen: Workshopserie hösten 20212022Report (Other academic)
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  • 4. Arya, N.
    et al.
    Chandran, Y.
    Luhar, B.
    Kajal, P.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Institute of Technology, Mandi, Himachal Pradesh, India.
    Balakrishnan, V.
    Porosity-Engineered CNT-MoS2 Hybrid Nanostructures for Bipolar Supercapacitor Applications2023In: ACS Applied Materials and Interfaces, ISSN 1944-8244, E-ISSN 1944-8252, Vol. 15, no 29, p. 34818-34828Article in journal (Refereed)
    Abstract [en]

    Bipolar supercapacitors that can store many fold higher capacitance in negative voltage compared to positive voltage are of great importance if they can be engineered for practical applications. The electrode material encompassing high surface area, better electrochemical stability, high conductivity, moderate distribution of pore size, and their interaction with suitable electrolytes is imperative to enable bipolar supercapacitor performance. Apropos of the aforementioned aspects, the intent of this work is to ascertain the effect of ionic properties of different electrolytes on the electrochemical properties and performance of a porous CNT-MoS2 hybrid microstructure toward bipolar supercapacitor applications. The electrochemical assessment reveals that the CNT-MoS2 hybrid electrode exhibited a two- to threefold higher areal capacitance value of 122.3 mF cm-2 at 100 μA cm-2 in 1 M aqueous Na2SO4 and 42.13 mF cm-2 at 0.30 mA cm-2 in PVA-Na2SO4 gel electrolyte in the negative potential window in comparison to the positive potential window. The CNT-MoS2 hybrid demonstrates a splendid Coulombic efficiency of ∼102.5% and outstanding stability with capacitance retention showing a change from 100% to ∼180% over 7000 repeated charging-discharging cycles. © 2023 American Chemical Society.

  • 5. Attri, Shubham Dutt
    et al.
    Singh, Shweta
    Dhar, Atul
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Institute of Technology Mandi, Himachal Pradesh, India.
    Multi-attribute sustainability assessment of wastewater treatment technologies using combined fuzzy multi-criteria decision-making techniques2022In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 357, article id 131849Article in journal (Refereed)
    Abstract [en]

    Water, which is predicted to be one of the most critical resources for the near future, also plays a vital role in society's sustainable development. Wastewater treatment is a critical part of the circular water management system and offers various technological alternatives. Taking appropriate decision for the technology selection is, therefore, essential for a long-term perspective. A complex yet imperative process is the sustainable selection of the wastewater treatment process. This paper presents the use of multi-criteria decision-making (MCDM) in the sustainability assessment of wastewater treatment technologies that may be very relevant to the growing sector with many emerging options. A comparison of six wastewater treatment technologies based on four sustainability parameters using three MCDM techniques, namely FSWARA, FMOORA and FTOPSIS is presented in detail. FSWARA is used for weighting criteria and the other two for technology ranking. The detailed step-by-step comparison study is presented and the results were somewhat predictable for the study, and this confirms the reliability of the methodology. This paper's primary objective is to propose a well-defined increscent practice for making sustainable wastewater treatment decisions among state-of-the-art technologies.

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  • 6. Barthwal, M.
    et al.
    Dhar, A.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. School of Engineering, Indian Institute of Technology, India.
    Effect of Nanomaterial Inclusion in Phase Change Materials for Improving the Thermal Performance of Heat Storage: A Review2021In: ACS Applied Energy Materials, E-ISSN 2574-0962, Vol. 4, no 8, p. 7462-7480Article in journal (Refereed)
    Abstract [en]

    Dispersion of nanoparticles is one of the potential solutions to improve the thermophysical properties of phase change (or transition) materials (PCMs) and enhance the performance of latent thermal energy storage (LTES) systems. The PCM ought to have a high latent heat of fusion, and zero or negligible coefficient of thermal expansion. A good PCM should have melting and solidification compatibility with negligible or zero subcooling, and it should not react with the common chemical reagents. The present known PCMs possess low thermal conductivity that results into a longer solidification and melting time of PCMs. In the past two decades, researchers have reported improved thermal conductivity and heat-storing capacity of PCMs employing graphite nanoparticles/fibers, carbon nanotubes/fibers, metal, and metal oxide nanoparticles. This work reviews the reported experimental and numerical studies describing the consequences of nanoparticle inclusions of various shapes and sizes on the thermal properties of the PCMs. This review attempts to make a consolidated database of the studies related to nanoadditive inclusion into PCMs for various applications. Graphene dispersed into PCM has resulted into 14 times thermal conductivity enhancement. As far as metal oxide nanoparticles are concerned, TiO2 and Al2O3 nanoparticles outperformed others. The compatibility between the nanoadditive and PCM is necessary to tailor favorable thermal properties. This work reviews numerous studies of different nanoparticle-PCM duos. © 2021 American Chemical Society.

  • 7. Bonthu, D.
    et al.
    Mahesh, V.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Institute of Technology Mandi, Himachal Pradesh, Mandi, India.
    Doddamani, M.
    3D printed functionally graded foams response under transverse load2023In: Results in Materials, ISSN 2590-048X, Vol. 19, article id 100410Article in journal (Refereed)
    Abstract [en]

    The applications of 3D printing are rapidly increasing in aerospace and naval applications. Nonetheless, 3D printing (3DP) of graded foams exhibiting property variation along the thickness direction is yet to be explored. In the current work, the different volume fractions of hollow glass micro balloon (GMB) reinforced high-density polyethylene (HDPE) composite based graded foams are 3D printed using the fused deposition modelling (FDM) technique. The bonding between successive layers and porosity distribution of these graded configurations are studied using micro-CT scan. Further, the 3D Printed functionally graded foams (FGFs) are tested for flexural response, and results are compared with numerical values. The micro-CT results showed delamination absence between the layers. In neat HDPE layers, porosity is not evident, while minor porosity creeps in the layers having the highest GMB content. Experimental results of the flexural test showed that the graded sandwiches exhibited better strength than the graded core alone. Compared to neat HDPE, the modulus of FGF-2 (H20–H40–H60) increased by 33.83%, implying better mechanical stiffness. Among all the FGFs, FGF-2 exhibited a better specific modulus. A comparative study of experimental and numerical results showed a slight deviation due to neglecting the induced porosity. © 2023 The Authors

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  • 8. Chang, Li
    et al.
    Chong, Wen Tong
    Wang, Xinru
    Pei, Fei
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Wang, Tongzhao
    Wang, Chunqing
    Pan, Song
    Recent progress in research on PM2.5 in subways.2021In: Environmental Science: Processes & Impacts, ISSN 2050-7887, E-ISSN 2050-7895, Vol. 23, no 5, p. 642-663Article in journal (Refereed)
    Abstract [en]

    Nowadays, PM2.5 concentrations greatly influence indoor air quality in subways and threaten passenger and staff health because PM2.5 not only contains heavy metal elements, but can also carry toxic and harmful substances due to its small size and large specific surface area. Exploring the physicochemical and distribution characteristics of PM2.5 in subways is necessary to limit its concentration and remove it. At present, there are numerous studies on PM2.5 in subways around the world, yet, there is no comprehensive and well-organized review available on this topic. This paper reviews the nearly twenty years of research and over 130 published studies on PM2.5 in subway stations, including aspects such as concentration levels and their influencing factors, physicochemical properties, sources, impacts on health, and mitigation measures. Although many determinants of station PM2.5 concentration have been reported in current studies, e.g., the season, outdoor environment, and station depth, their relative influence is uncertain. The sources of subway PM2.5 include those from the exterior (e.g., road traffic and fuel oil) and the interior (e.g., steel wheels and rails and metallic brake pads), but the proportion of these sources is also unknown. Control strategies of PM mainly include adequate ventilation and filtration, but these measures are often inefficient in removing PM2.5. The impacts of PM2.5 from subways on human health are still poorly understood. Further research should focus on long-term data collection, influencing factors, the mechanism of health impacts, and PM2.5 standards or regulations.

  • 9. Copertaro, Benedetta
    et al.
    Shen, Jingchun
    Dalarna University, School of Information and Engineering, Construction.
    Sangelantoni, Lorenzo
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Building Renovation Adapting to Future Climate: A Potential Solution of Phase-Change Material to Building Envelope2022In: Handbook of Climate Change Mitigation and Adaptation / [ed] Maximilian Lackner, Baharak Sajjadi, Wei-Yin Chen, Springer Nature, 2022Chapter in book (Refereed)
  • 10. Dong, Bing
    et al.
    Liu, Yapan
    Fontenot, Hannah
    Ouf, Mohamed
    Osman, Mohamed
    Chong, Adrian
    Qin, Shuxu
    Han, Mengjie
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Carlucci, Salvatore
    Occupant behavior modeling methods for resilient building design,operation and policy at urban scale: a review2021In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 293, article id 116856Article in journal (Refereed)
  • 11. Duryodhana, D.
    et al.
    Waddar, S.
    Bonthu, D.
    Pitchaimani, J.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. School of Mechanical and Materials Engineering, Indian Institute of Technology Mandi, Himachal Pradesh, Mandi, India.
    Doddamani, M.
    Buckling and free vibrations behaviour through differential quadrature method for foamed composites2023In: Results in Engineering (RINENG), ISSN 2590-1230, Vol. 17, article id 100894Article in journal (Refereed)
    Abstract [en]

    The current work focuses on predicting the buckling and free vibration frequencies (fn) of cenosphere reinforced epoxy based syntactic foam beam under varying loads. Critical buckling loads (Ncr) and fn are predicted using the differential quadrature method (DQM). Ncr and fn have been calculated for beams of varying cenosphere volume fractions subjected to axial load under clamped-clamped (CC), clamped-simply (CS), simply-simply (SS), and clamped-free (CF) boundary conditions (BC′s). Upon increasing the cenosphere volume fraction, Ncr and fn of syntactic foam composites increases. These numerical outcomes are compared with the theoretical values evaluated through the Euler-Bernoulli hypothesis and further compared with experimental outcomes. Results are observed to be in precise agreement. The results of the DQM numerical analysis are given out for the different BC′s, aspect ratios, cenosphere volume fractions, and varying loads. It is perceived that depending on the BC′s, the type of axial varying loads and aspect ratios has a substantial effect on the Ncr and fn behaviour of the syntactic foam beams. A comparative study of the obtained results showed that the beam subjected to parabolic load under CC boundary conditions exhibited a higher buckling load. © 2023 The Authors

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  • 12.
    Fiedler, Frank
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Matas, Joaquin C.
    Techno-Economic Analysis of Grid-Connected PV Battery Solutions for Holiday Homes in Sweden2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 8Article in journal (Refereed)
    Abstract [en]

    Grid-connected PV battery systems for private homes are becoming increasingly popular in many countries, including Sweden. This study aimed to evaluate the techno-economic feasibility of such distributed, grid-connected PV battery systems for single homes at a Swedish holiday location. It was especially of interest to investigate the impact of demand charges, as they are frequently introduced by utilities in Sweden and are also common in popular winter sport regions. Grid-connected PV battery systems were sized and optimized based on their net present cost. Load patterns, incentives, demand tariff structures and electricity price variation were used to study the sensitivity of the obtained results. Grid-connected residential PV battery systems were found to be equally profitable compared to grid-connected PV systems without batteries when demand charges were applied. When the load profiles had peak loads throughout the whole year and the batteries were large enough sized to shave many peaks, grid-connected PV battery systems had slightly higher profitability than grid-connected PV systems without batteries. The total savings also depended on the actual rate of demand charge. The good profitability we found greatly depends on the current state incentives for these systems in the form of tax credits for surplus electricity and investment costs. Removing the tax credit for surplus electricity would reduce the savings generated by a grid-connected PV system without batteries significantly more than for grid-connected PV systems with batteries.

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  • 13. Gambardella, Andrea
    et al.
    Saini, Puneet
    Dalarna University, School of Information and Engineering, Energy Technology.
    A novel method for assessing the techno-economicalcompatibility of solar thermal integrations2022Conference paper (Refereed)
    Abstract [en]

    In this work we present a method to evaluate the compatibility of a solar thermal integration in an industrial process. We introduce two indicators to quantify in a comprehensive way all the financial and technicalboundaries influence on the design choices and on the costs of a solar thermal integration.Both the indicators are measures of the divergence of an integration from a fictive (yet technically possible)ideal case and from a “do-nothing” case. In this way, the incompatibilities of the integration are associated tothe consequences that the non-ideal factors have on both costs and performances. Moreover, the value of the indicators is normalized between a minimum and a maximum being the “do-nothing” and the ideal cases respectively.We then used these indicators on a real case scenario to compare the pros and cons of two different solarthermal integration approaches (hot water vs steam) to a beer brewery in southern Europe.The results show that retrofitting part of the existing appliance to be fed with hot water rather than steamenhances the compatibility of solar thermal with the brewery. Nevertheless, we measured no relevant improvement to the compatibility of solar thermal when designing a brewery from scratch with the same characteristics but were the solar thermal system could have been integrated “ad-hoc” rather than retrofitted

  • 14. Gao, D. -C
    et al.
    Sun, Y.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Zhang, Yelin
    A GA-based NZEB-cluster planning and design optimization method for mitigating grid overvoltage risk2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 243, article id 123051Article in journal (Refereed)
    Abstract [en]

    Net-zero energy buildings (NZEBs) are considered as a promising method to mitigating the energy problems. Due to the intermittent characteristics of renewable energy (e.g., solar energy), NZEBs need to frequently exchange energy with the grid, which imposes severe negative impacts on the grid especially the overvoltage risk. Both planning and design are essential for reducing NZEB connected grid overvoltage, but most existing studies isolated the efforts from planning to design, thereby failing to achieve the best cumulative result. More importantly, existing studies oversimplified overvoltage quantification by using aggregated power interactions to represent overvoltage risk, which cannot consider the complex voltage influences among grid nodes. Due to the isolated efforts and the quantification oversimplification, existing studies can hardly achieve overvoltage risk minimization. Therefore, this study proposes a novel GA (genetic algorithm)-based method in which the key planning and design parameters are optimized sequentially for mitigating the overvoltage risk. Meanwhile, distribution network model has been adopted to precisely quantify the grid overvoltage. The study results show that the proposed method is highly effective in reducing NZEB cluster connected grid overvoltage risk. The proposed method can be used in practice for improving NZEB cluster planning and system design as grid interaction is considered. © 2021 Elsevier Ltd

  • 15.
    Garman, Ian
    et al.
    Dalarna University, School of Information and Engineering, Construction. Univ Gävle.
    Mattsson, Magnus
    Univ Gävle.
    Myhren, Jonn Are
    Dalarna University, School of Information and Engineering, Construction.
    Persson, Tomas
    Dalarna University, School of Information and Engineering, Energy Technology.
    Demand control and constant flow ventilation compared in an exhaust ventilated bedroom in a cold-climate single-family house2023In: Intelligent Buildings International, ISSN 1750-8975, E-ISSN 1756-6932Article in journal (Refereed)
    Abstract [en]

    A convertible, zoned ventilation system was field-tested in a modern, airtight Swedish home when occupied either by an experimental team or by a family. Indoor air quality in the master bedroom was monitored under four ventilation strategies. Relative to constant air volume strategies (CAV), demand-controlled ventilation (DCV) that was responding to CO2 concentration extracted more air when people were present, but less in total over 24 h. This elevated the indoor air humidity, beneficial in climates with dry winter air. Multiple monitors within the bedroom indicated that vertical CO2 stratification occurred routinely, presumably due to low mixing of supply air from a wall-mounted diffuse vent, spreading the air radially over the wall. This seemingly improved air quality in the breathing zone under local (ceiling) extract ventilation but worsened it during more typical, centralised extract ventilation, where air escapes the room via an inner doorway. The local extract arrangement thus seemed to yield both improved ventilation efficiency and reduced contaminant spread to other rooms. The noted air quality variations within the room highlight the importance of sensor placement in demand-control ventilated spaces, even in small rooms such as bedrooms.

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  • 16.
    Garman, Ian
    et al.
    Dalarna University, School of Information and Engineering, Construction.
    Mattsson, Magnus
    Persson, Tomas
    Dalarna University, School of Information and Engineering, Energy Technology.
    Ventilation alone fails to prevent overheating in a Nordic home field study2022In: 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022, Kuopio, 12 June 2022 through 16 June 2022, International Society of Indoor Air Quality and Climate , 2022Conference paper (Refereed)
    Abstract [en]

    A field study conducted in a modern Nordic single-family house with high airtightness and insulation levels, attempted to control summer indoor overheating using night-time cooling strategies. Exhaust air flow rates were manually scheduled by the researchers (based on weather forecasts), analogous to what an engaged occupant - or a predictive system - might do. Air temperatures at a nearby meteorological station peaked at 30 °C during 6 days in June that saw only 44 hours below 18 °C. Temperatures recorded indoors at the test house reached 32 °C, due also to very large solar gains, and never fell below 26 °C over 8 continuous days. It appears that under extended heat conditions that are exceptional now, but foreseen to become more frequent, some modern Nordic homes cannot be temperature controlled by ambient ventilation alone. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

  • 17.
    Ghasemi, Mohammad
    Dalarna University, School of Information and Engineering, Energy Technology.
    Comparative techno-economic analysis of high temperature heat pump and parabolic trough collector system for industrial steam generation: Analysis for Europe2022Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Industrial heat production is responsible for around 20 % of total greenhouse gas emissions in Europe. To achieve the climate change goals defined in Paris Climate Agreement, reducing greenhouse gas emissions from industry are urgently needed. Therefore, providing sustainable heat production for industrial applications would be considered as an essential solution. The ongoing conflict between Russia and Ukraine has further exposed EU for their dependency of natural gas in Russia. The EU commission has shifted their focus on sustainable means to generate heating in both residential and industrial applications. For fulfilling this target, focus and develop in novel technologies using renewable sources which could help to minimize CO2 emissions in their life cycle is inevitable.

     

    Among few existing technologies, this report, focuses on two technologies which hold strong potential for heating decarbonization. High-temperature heat pumps (HTHP) which is a technology currently under development and already reached to cover up to 160 °C applications. It is projected that heat pumps would play bigger role with their higher rate of performance in future for industrial heat problem as they have potential to be totally carbon free technology, when they are hybridized with electricity from renewable sources. Solar thermal (ST) technology and specifically parabolic trough collector (PTC) which has a longer history of implementation in industrial energy systems and have obtained significant attention in ST heating systems for industrial applications. Solar thermal system can produce heat economically and at minimal carbon footprint compare to other technologies in the market.

     

    The main aim of this thesis is based on implementing of mentioned technologies and evaluate their levelized cost of heat (LCOH) individually and consequently their capabilities in providing industrial heat loads. To be more precise, this thesis aims are to fulfil a comparative techno-economic analysis using PTC and HTHP. Boundary conditions for geographical constrains in Europe have been applied for setting up cases for further analysis. Then a sensitivity analysis by manipulating different parameters is made.  It is important to mention that simulations for HTHP are performed using Excel spread sheet, while for ST part TRNSED and OCTAVE are used. 

     

    Results shows the cost of heat generation for both HTHP and PTC collectors with changing boundary conditions. A  maximum solar fraction (SF) limit of PTC collector is defined to indicate when the LCOH for these two technologies coincides. The results can support decision-makers/designers to have a rough estimation of which SF would be viable under different boundaries such as: Direct Normal Irradiation (DNI) level, Capital expenses (CAPEX) of HTHP, load profile, and electricity price.

     

    The results from the work can be used as a stepping stone to bring collaboration between two technologies thus working as hybrid system to provide nearly renewable heating systems for industries.

  • 18. Gorjian, Shiva
    et al.
    Calise, Francesco
    Kant, Karunesh
    Ahamed, Md Shamim
    Copertaro, Benedetta
    Dalarna University, School of Information and Engineering, Energy Technology.
    Najafi, Gholamhassan
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Aghaei, Mohammadreza
    Shamshiri, Redmond R.
    A review on opportunities for implementation of solar energy technologies in agricultural greenhouses2021In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 285, article id 124807Article in journal (Refereed)
  • 19.
    Han, Mengjie
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Canli, Ilkim
    Department of Architecture, Middle East Technical University, Ankara 06800, Türkiye;Center for Solar Energy Research and Applications (ODTÜ-GÜNAM), Middle East Technical University, Ankara 06800, Türkiye.
    Shah, Juveria
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Dino, Ipek Gursel
    Department of Architecture, Middle East Technical University, Ankara 06800, Türkiye;METU Robotics and AI Technologies Application and Research Center (METU-ROMER), Middle East Technical University (METU), Ankara 06800, Türkiye.
    Kalkan, Sinan
    METU Robotics and AI Technologies Application and Research Center (METU-ROMER), Middle East Technical University (METU), Ankara 06800, Türkiye;Department of Computer Engineering, Middle East Technical University, Ankara 06800, Türkiye.
    Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts2024In: Buildings, E-ISSN 2075-5309, Vol. 14, no 2, article id 371Article in journal (Refereed)
    Abstract [en]

    The concept of a Positive Energy District (PED) has become a vital component of the efforts to accelerate the transition to zero carbon emissions and climate-neutral living environments. Research is shifting its focus from energy-efficient single buildings to districts, where the aim is to achieve a positive energy balance across a given time period. Various innovation projects, programs, and activities have produced abundant insights into how to implement and operate PEDs. However, there is still no agreed way of determining what constitutes a PED for the purpose of identifying and evaluating its various elements. This paper thus sets out to create a process for characterizing PEDs. First, nineteen different elements of a PED were identified. Then, two AI techniques, machine learning (ML) and natural language processing (NLP), were introduced and examined to determine their potential for modeling, extracting, and mapping the elements of a PED. Lastly, state-of-the-art research papers were reviewed to identify any contribution they can make to the determination of the effectiveness of the ML and NLP models. The results suggest that both ML and NLP possess significant potential for modeling most of the identified elements in various areas, such as optimization, control, design, and stakeholder mapping. This potential is realized through the utilization of vast amounts of data, enabling these models to generate accurate and useful insights for PED planning and implementation. Several practical strategies have been identified to enhance the characterization of PEDs. These include a clear definition and quantification of the elements, the utilization of urban-scale energy modeling techniques, and the development of user-friendly interfaces capable of presenting model insights in an accessible manner. Thus, developing a holistic approach that integrates existing and novel techniques for PED characterization is essential to achieve sustainable and resilient urban environments.

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  • 20.
    Han, Mengjie
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Johari, Fatemeh
    Uppsala University.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Generating hourly electricity demand data for large-scale single-family buildings by a decomposition-recombination method2022In: Energy and Built Environment, ISSN 2666-1233Article in journal (Refereed)
    Abstract [en]

    Household electricity demand has substantial impacts on local grid operation, energy storage and the energy performance of buildings. Hourly demand data at district or urban level helps stakeholders understand the demand patterns from a granular time scale and provides robust evidence in energy management. However, such type of data is often expensive and time-consuming to collect, process and integrate. Decisions built upon smart meter data have to deal with challenges of privacy and security in the whole process. Incomplete data due to confidentiality concerns or system failure can further increase the difficulty of modeling and optimization. In addition, methods using historical data to make predictions can largely vary depending on data quality, local building environment, and dynamic factors. Considering these challenges, this paper proposes a statistical method to generate hourly electricity demand data for large-scale single-family buildings by decomposing time series data and recombining them into synthetics. The proposed method used public data to capture seasonality and the distribution of residuals that fulfill statistical characteristics. A reference building was used to provide empirical parameter settings and validations for the studied buildings. An illustrative case in a city of Sweden using only annual total demand was presented for deploying the proposed method. The results showed that the proposed method can mimic reality well and represent a high level of similarity to the real data. The average monthly error for the best month reached 15.9% and the best one was below 10% among 11 tested months. Less than 0.6% improper synthetic values were found in the studied region.

  • 21.
    Han, Mengjie
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    May, Ross
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Reinforcement Learning Methodologies for Controlling Occupant Comfort in Buildings2021In: Data-driven Analytics for Sustainable Buildings and Cities, Switzerland: Springer, 2021, p. 179-205Chapter in book (Other academic)
  • 22.
    Han, Mengjie
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Shah, Juveria
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Review of natural language processing techniques for characterizing positive energy districts2023In: journal of Physics; Conference series, Institute of Physics Publishing (IOPP), 2023, Vol. 2600, no 8, article id 082024Conference paper (Refereed)
    Abstract [en]

    The concept of Positive Energy Districts (PEDs) has emerged as a crucial aspect of endeavours aimed at accelerating the transition to zero carbon emissions and climate-neutral living spaces. The focus of research has shifted from energy-efficient individual buildings to entire districts, where the objective is to achieve a positive energy balance over a specific timeframe. The consensus on the conceptualization of a PED has been evolving and a standardized checklist for identifying and evaluating its constituent elements needs to be addressed. This study aims to develop a methodology for characterizing PEDs by leveraging natural language processing (NLP) techniques to model, extract, and map these elements. Furthermore, a review of state-of-the-art research papers is conducted to ascertain their contribution to assessing the effectiveness of NLP models. The findings indicate that NLP holds significant potential in modelling the majority of the identified elements across various domains. To establish a systematic framework for AI modelling, it is crucial to adopt approaches that integrate established and innovative techniques for PED characterization. Such an approach would enable a comprehensive and effective implementation of NLP within the context of PEDs, facilitating the creation of sustainable and resilient urban environments. © 2023 Institute of Physics Publishing. All rights reserved.

  • 23.
    Han, Mengjie
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Wang, Zhenwu
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    An Approach to Data Acquisition for Urban Building Energy Modeling Using a Gaussian Mixture Model and Expectation-Maximization Algorithm2021In: Buildings, E-ISSN 2075-5309, Vol. 11, no 1Article in journal (Refereed)
    Abstract [en]

    In recent years, a building’s energy performance is becoming uncertain because of factors such as climate change, the Covid-19 pandemic, stochastic occupant behavior and inefficient building control systems. Sufficient measurement data is essential to predict and manage a building’s performance levels. Assessing energy performance of buildings at an urban scale requires even larger data samples in order to perform an accurate analysis at an aggregated level. However, data are not only expensive, but it can also be a real challenge for communities to acquire large amounts of real energy data. This is despite the fact that inadequate knowledge of a full population will lead to biased learning and the failure to establish a data pipeline. Thus, this paper proposes a Gaussian mixture model (GMM) with an Expectation-Maximization (EM) algorithm that will produce synthetic building energy data. This method is tested on real datasets. The results show that the parameter estimates from the model are stable and close to the true values. The bivariate model gives better performance in classification accuracy. Synthetic data points generated by the models show a consistent representation of the real data. The approach developed here can be useful for building simulations and optimizations with spatio-temporal mapping.

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  • 24.
    Han, Mengjie
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhao, Jing
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Shen, Jingchun
    Dalarna University, School of Information and Engineering, Construction.
    Li, Yu
    The reinforcement learning method for occupant behavior in building control: A review2021In: Energy and Built Environment, ISSN 2666-1233, Vol. 2, no 2, p. 137-148Article in journal (Refereed)
    Abstract [en]

    Occupant behavior in buildings has been considered the major source of uncertainty for assessing energy consumption and building performance. Modeling frameworks are usually built to accomplish a certain task, but the stochasticity of the occupant makes it difficult to apply that experience to a similar but distinct environment. For complex and dynamic environments, the development of smart devices and computing power makes intelligent control methods for occupant behaviors more viable. It is expected that they will make a substantial contribution to reducing global energy consumption. Among these control techniques, the reinforcement learning (RL) method seems distinctive and applicable. The success of the reinforcement learning method in many artificial intelligence applications has given an explicit indication of how this method might be used to model and adjust occupant behavior in building control. Fruitful algorithms complement each other and guarantee the quality of the optimization. However, the examination of occupant behavior based on reinforcement learning methodologies is not well established. The way that occupant interacts with the RL agent is still unclear. This study briefly reviews the empirical applications using reinforcement learning, how they have contributed to shaping the modeling paradigms and how they might suggest a future research direction.

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  • 25. Han, Y.
    et al.
    Wu, P.
    Geng, Z.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Editorial: Energy efficiency analysis and intelligent optimization of process industry2023In: Frontiers in Energy Research, E-ISSN 2296-598X, Vol. 11, article id 1283021Article in journal (Other academic)
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  • 26. Hedman, Åsa
    et al.
    Rehman, Hassam U.
    Gabaldón, Andrea
    Bisello, Adriano
    Albert-Seifried, Vicky
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Guarino, Francesco
    Grynning, Steinar
    Eicker, Ursula
    Reda, Francesco
    IEA EBC Annex83 Positive Energy Districts2021In: Buildings, E-ISSN 2075-5309, Vol. 11, no 3Article in journal (Refereed)
    Abstract [en]

    At a global level, the need for energy efficiency and an increased share of renewable energy sources is evident, as is the crucial role of cities due to the rapid urbanization rate. As a consequence of this, the research work related to Positive Energy Districts (PED) has accelerated in recent years. A common shared definition, as well as technological approaches or methodological issues related to PEDs are still unclear in this development and a global scientific discussion is needed. The International Energy Agency’s Energy in Buildings and Communities Programme (IEA EBC) Annex 83 is the main platform for this international scientific debate and research. This paper describes the challenges of PEDs and the issues that are open for discussions and how the Annex 83 is planned and organized to facilitate this and to actively steer the development of PEDs major leaps forward. The main topics of discussion in the PED context are the role and importance of definitions of PEDs, virtual and geographical boundaries in PEDs, the role of different stakeholders, evaluation approaches, and the learnings of realized PED projects.

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  • 27.
    Hernandez Velasco, Marco
    Dalarna University, School of Information and Engineering, Energy Technology.
    Enabling Year-Round Cultivation in the Nordics-Agrivoltaics and Adaptive LED Lighting Control of Daily Light Integral2021In: Agriculture, E-ISSN 2077-0472, Vol. 11, no 12, p. 1255-1255Article in journal (Refereed)
    Abstract [en]

    High efficacy LED lamps combined with adaptive lighting control and greenhouse integrated photovoltaics (PV) could enable the concept of year-round cultivation. This concept can be especially useful for increasing the production in the Nordic countries of crops like herbaceous perennials, forest seedlings, and other potted plants not native of the region, which are grown more than one season in this harsh climate. Meteorological satellite data of this region was analyzed in a parametric study to evaluate the potential of these technologies. The generated maps showed monthly average temperatures fluctuating from −20 °C to 20 °C throughout the year. The natural photoperiod and light intensity also changed drastically, resulting in monthly average daily light integral (DLI) levels ranging from 45–50 mol·m−2·d−1 in summer and contrasting with 0–5 mol·m−2·d−1 during winter. To compensate, growth room cultivation that is independent of outdoor conditions could be used in winter. Depending on the efficacy of the lamps, the electricity required for sole-source lighting at an intensity of 300 µmol·m−2·s−1 for 16 h would be between 1.4 and 2.4 kWh·m−2·d−1. Greenhouses with supplementary lighting could help start the cultivation earlier in spring and extend it further into autumn. The energy required for lighting highly depends on several factors such as the natural light transmittance, the light threshold settings, and the lighting control protocol, resulting in electric demands between 0.6 and 2.4 kWh·m−2·d−1. Integrating PV on the roof or wall structures of the greenhouse could offset some of this electricity, with specific energy yields ranging from 400 to 1120 kWh·kW−1·yr−1 depending on the region and system design.

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  • 28.
    Huang, Pei
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Han, Mengjie
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Hussain, Sayed Asad
    The University of British Columbia, Canada.
    Jayprakash Bhagat, Rohit
    Hogarehalli Kumar, Deepu
    Characterization and optimization of energy sharing performances in energy-sharing communities in Sweden, Canada and Germany2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 326, article id 120044Article in journal (Refereed)
    Abstract [en]

    Peer-to-peer (P2P) renewable power sharing within a building community is a promising solution to enhance the community's self-sufficiency and relieve the grid stress posed by the increased deployment of distributed renewable power. Existing studies have pointed out that the energy sharing potentials of a building community are affected by various factors including location, community scale, renewable energy system (RES) capacity, energy system type, storage integration, etc. However, the impacts of these factors on the energy sharing potentials in a building community are not fully studied. Being unaware of those factors’ impacts could lead to reduced energy sharing potentials and thus limit the associated improvement in energy and economic performances. Thus, this study conducts a comprehensive analysis of various factors’ impacts on the energy sharing performances in building communities. Two performance indicators are first proposed to quantify the energy sharing performances: total amount of energy sharing and energy sharing ratio (ESR). Then, parametric studies are conducted based on real electricity demand data in three countries to reveal how these factors affect the proposed indictors and improvements in self-sufficiency, electricity costs, and energy exchanges with the power grid. Next, a genetic algorithm based design method is developed to optimize the influential parameters to maximize the energy sharing potentials in a community. The study results show that the main influential factors are RES capacity ratio, PV capacity ratio, and energy storage system capacity. A large energy storage capacity can enhance the ESR. To achieve the maximized ESR, the optimal RES capacity ratio should be around 0.4 ∼ 1.1. The maximum energy sharing ratio is usually smaller in high latitude districts such as Sweden. This study characterizes the energy sharing performances and provides a novel perspective to optimize the design of energy systems in energy sharing communities. It can pave the way for the large integration of distributed renewable power in the future. © 2022 The Author(s)

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  • 29.
    Huang, Pei
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Lovati, M.
    Shen, Jingchun
    Dalarna University, School of Information and Engineering, Construction.
    Chai, J.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Investigation of the Peer-to-Peer energy trading performances in a local community under the future climate change scenario in Sweden2022In: Energy Reports, E-ISSN 2352-4847, Vol. 8, p. 989-1001Article in journal (Refereed)
    Abstract [en]

    Peer-to-peer (P2P) energy sharing among neighboring households is a promising solution to mitigating the difficulties of renewable power (such as solar Photovoltaics (PV)) penetration on the power grid. Until now, there is still a lack of study on the impacts of future climate change on the P2P energy trading performances. The future climate change will cause variances in the renewable energy production and further lead to changes in the economic performances of households with various energy uses and affect the decision making in PV ownership and pricing strategies. Being unaware of these impacts could potentially hinder the P2P energy sharing application in practice. To bridge such knowledge gap, this paper conducts a systematic investigation of the climate change impacts on the energy sharing performance in solar PV power shared communities. The future weather data is generated using the Morphine method, and an agent-based modeling method is used for simulating the energy trading behaviors of households. Four comparative scenarios of different PV ownerships and pricing strategies are designed. The detailed energy trading performances (including the PV power self-sufficiency, cost saving, revenues, and compound annual growth rate) for the four comparative scenarios are analyzed under both the present and future climates and compared. The study results of a building community located in Sweden show that the future climate change is more beneficial to large energy use households while less beneficial to small households. High price of energy trading can improve the fairness of the economic performances in the community, especially when some of the households do not have any PV ownership. This study can help understand the future climate impacts on the energy sharing performances of building communities, which can in turn guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications. © 2021 The Author(s)

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  • 30.
    Huang, Pei
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Munkhammar, J.
    Fachrizal, R.
    Lovati, M.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Sun, Y.
    Comparative studies of EV fleet smart charging approaches for demand response in solar-powered building communities2022In: Sustainable cities and society, ISSN 2210-6707, Vol. 85, article id 104094Article in journal (Refereed)
    Abstract [en]

    The use of electric vehicles (EVs) has been on the rise during the past decade, and the number is expected to rapidly increase in the future. At aggregated level, the large EV charging loads, if not well regulated, will cause great stress on the existing grid infrastructures. On the other hand, considered as a resource-efficient and cost-effective demand response resource, EV fleet smart charging control methods have been developed and applied to mitigate power issues of the grid while avoiding expensive upgrade of power grid infrastructure. Until now, there is no systematic study on how different coordination mechanisms affecting the EV fleet's charging demand response performance. Thus, it is still unclear which one may perform better in the increasingly common solar-powered building communities, especially as demand response is increasingly concerned. Aiming to fill in such knowledge gaps, this study conducted systematic comparative studies of three representative control methods selected from the non-coordinated, bottom-up coordinated, and top-down coordinated control categories. Their power regulation performances have been comparatively investigated in two perspectives: minimizing peak power exchanges with the grid and maximizing PV self-utilization, based on a real building community in Sweden. Meanwhile, their computational performances have also been investigated. The study results show that due to the ability to schedule and coordinate all the EVs simultaneously, the top-down coordinated control is superior to the other two control methods in the considered demand response performances. Note that its better performance is realized with a higher computational load, leading to possible convergence difficulties in practice. The study results will help improve understanding of how coordination affect the EV smart charging control performances. It will pave the way for developments of more sophisticated control methods for EV smart charging in more complex scenarios. © 2022 Elsevier Ltd

  • 31.
    Huang, Pei
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Sun, Yongjun
    Lovati, Marco
    Dalarna University, School of Information and Engineering, Energy Technology.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Solar-photovoltaic-power-sharing-based design optimization of distributed energy storage systems for performance improvements2021In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 222, article id 119931Article in journal (Refereed)
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  • 32.
    Huang, Pei
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Tu, Ran
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Han, Mengjie
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Sun, Yongjun
    Hussain, Syed Asad
    Zhang, Linfeng
    Investigation of electric vehicle smart charging characteristics on the power regulation performance in solar powered building communities and battery degradation in Sweden2022In: Journal of Energy Storage, ISSN 2352-152X, E-ISSN 2352-1538, Vol. 56, p. 105907-105907, article id 105907Article in journal (Refereed)
  • 33.
    Huang, Pei
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    A systematic comparison of various electric vehicle charging approaches2022In: E3S Web of Conferences, EDP Sciences , 2022, Vol. 362, article id 06006Conference paper (Refereed)
    Abstract [en]

    The use of electric vehicles (EVs) has been on the rise. Most of the existing EV smart charging controls can be categorized into three approaches according to their optimization principles: individual, bottom-up and top-down. Until now, systematic comparison and analysis of the different approaches are still lacking. It is still unknown whether a control approach performs better than others and, if yes, why is it so. This study aims to fill in such knowledge gaps by conducting a systematic comparison of these three different control approaches and analyzing their performances in depth. A representative control algorithm will be selected from each control approach, then the selected algorithms will be applied for optimizing EV charging loads in a building community in Sweden. Their power regulation performances will be comparatively investigated. This study will help pave the way for the developments of more sophisticated control algorithms for EV smart charging. © 2022 The Authors, published by EDP Sciences.

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  • 34. Hussain, Syed Asad
    et al.
    Wang, Lan
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Sadiq, Rehan
    Hewage, Kasun
    Dissimilarity-driven ensemble model-based real-time optimization for control of building HVAC systems2022In: Journal of Building Engineering, E-ISSN 2352-7102, Vol. 52, article id 104376Article in journal (Refereed)
    Abstract [en]

    Model-based real-time optimization (MRTO) is proven as an effective tool that can capture the complex dynamics of heating, ventilation, and air conditioning (HVAC) systems and improve its energy performance. Despite the energy benefits offered by MRTO, these approaches are rarely implemented in actual buildings. This is due to the reason that these approaches are very difficult to implement because they require the synthesis of a reliable and accurate performance model of the system. The reliability of decision-making with MRTO is directly related to the accuracy of these performance models. In addition, the model has to be computationally efficient for practical implementation. The development of such a model requires the most effort and is a major challenge in the implementation of MRTO. Several HVAC performance models are already available in the literature, and these can be classified as semiphysical models and data-driven models. The semiphysical models are generalized models with simplification assumptions that can provide consistent performance, however, with reduced accuracy. Contrastingly, the data-driven models can offer better accuracy; however, they lack robustness in terms of operational ranges. These factors affect the energy performance of MRTO, and an improper parametrized model could result in performance that is even worse than the conventional fixed setpoint or rule-based approaches. A dissimilarity-driven ensemble model-based real-time optimization (DEMRTO) approach is presented in this study that incorporates a dissimilarity-driven ensemble model in the framework of real-time optimization. The dissimilarity-driven ensemble model combines semiphysical models and data-driven models in a systematic manner to use one's strengths to address others' weaknesses, rather than developing a new form of a model. The performance of the proposed integrated approach was examined using case studies over three weather seasons in Hong Kong. The results showed as compared to the fixed setpoint approach the DEMRTO approach can provide significant energy savings up to 11.085% setpoint, and around 2.785% reduction in energy use as compared with the conventional MRTO approach. It was demonstrated that the proposed approach can capture diversity in load conditions and provide consistency in model prediction to improve reliability in decision-making with real-time optimization.

  • 35. Jin, Yuan
    et al.
    Yan, Da
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    An, Jingjing
    Han, Mengjie
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    A data-driven model predictive control for lighting system based on historical occupancy in an office building: Methodology development2021In: Building Simulation, ISSN 1996-3599, E-ISSN 1996-8744, Vol. 14, p. 219-235Article in journal (Refereed)
  • 36.
    Kajal, Priyanka
    et al.
    Indian Inst Technol Mandi, Sch Engn, Mandi 175005, Himachal Prades, India..
    Verma, Bhupesh
    Ctr Study Sci Technol & Policy, Bangalore 560094, Karnataka, India..
    Vadaga, Satya Gangadhara Rao
    Ananyavijaya Consultancy LLP, Bangalore 562107, Karnataka, India..
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Inst Technol Mandi, Sch Engn, Mandi 175005, Himachal Prades, India.
    Costing Analysis of Scalable Carbon-Based Perovskite Modules Using Bottom Up Technique2022In: Global Challenges, E-ISSN 2056-6646, Vol. 6, no 2, article id 2100070Article in journal (Refereed)
    Abstract [en]

    In recent years, perovskite solar cells (PSCs) have achieved a remarkable power conversion efficiency of 25.5%, indicating that they are a promising alternative to dominant Si photovoltaic (PV) technology. This technology is expected to solve the world's energy demand with minimal investment and very low CO2 emissions. The market has shown a lot of interest in PSCs technology. A technoeconomic analysis is a useful tool for tracking manufacturing costs and forecasting whether technology will eventually achieve market-driven prices. A technoeconomic analysis of a 100 MW carbon-based perovskite solar module (CPSM) factory located in India is presented in this paper. Two CPSMs architectures-high-temperature processed CPSMs (Module A) and low-temperature processed CPSM's (Module B)-are expected to offer minimum sustainable prices (MSPs) of $ 0.21 W-1 and $ 0.15 W-1. On the basis of MSP, the levelized cost of energy (LCOE) is calculated to be 3.40 (sic) kWh(-1) for module A and 3.02 (sic) kWh(-1) for module B, with a 10-year module lifetime assumption. The same modules with a 25-year lifespan have LCOEs of 1.66 and 1.47 (sic) kWh(-1), respectively. These estimates are comparable to market dominant crystalline silicon solar modules, and they are also favorable for utilizing perovskite solar cell technology.

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  • 37. Kaundal, Ankur
    et al.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Institute of Technology Mandi, Mandi, Himachal Pradesh, India.
    Dhar, Atul
    Numerical investigation of the effect of air supply on cook stove performance.2021In: Inhalation Toxicology, ISSN 0895-8378, E-ISSN 1091-7691, Vol. 33, no 5, p. 193-203Article in journal (Refereed)
    Abstract [en]

    Objectives: In a domestic biomass cook stove, the air supply plays a significant role in improving the overall combustion characteristics. The present research aims to numerically investigate the effect of air supply, division of air intake into primary and secondary air, and its optimization. > In a domestic biomass cook stove, the air supply plays a significant role in improving the overall combustion characteristics. The present research aims to numerically investigate the effect of air supply, division of air intake into primary and secondary air, and its optimization. Methods: The geometries of cook stove combustion chamber were prepared and simulated using species transport model with eddy-dissipation turbulent mixing. The stoichiometric amount of air was split into different ratios varying from 50:50 to 10:90 and simulations were carried out for each case. The computational model was validated and the concentration of CO2, H2O, O2, wood volatile and resultant temperature were compared and analyzed. Results: Species transport in the form of conservation of mass along with momentum conservation and energy conservation gave the spatial distribution of resultant species and spatial temperature distribution. The computational domain with feedstock inlet corresponding to the pyrolysis regime has yielded good results compared to that in the front. In this domain, the primary to secondary air ratio of 50:50 showed the best results due to the dominance of primary air utilization and, thus, less secondary air use even at higher elevations. With the maximum temperature near 1300 K, maximum relative CO2 production, and maximum feedstock utilization, the primary to secondary air ratio of 50:50 observed to be optimum. Conclusions: Due to the adequate intermixing of reactant species and uniform diffusion of product species along the combustion chamber's height, the computational domain with feedstock inlet corresponding to the pyrolysis regime has shown realistic conditions. The temperature profile and mole fraction of various species, thus obtained, can be used to design an efficient cook stove as the cross-section and dimensions of the combustion chamber and chimney relates to approach the desired division of air.

  • 38. Koke, Johannes
    et al.
    Schippmann, André
    Shen, Jingchun
    Dalarna University, School of Information and Engineering, Construction.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Kaufmann, Peter
    Krause, Stefan
    Strategies of Design Concepts and Energy Systems for NearlyZero‐Energy Container Buildings (NZECBs) inDifferent Climates2021In: Buildings, E-ISSN 2075-5309, Vol. 11, no 8, article id 364Article in journal (Refereed)
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  • 39. Koubar, M.
    et al.
    Lindberg, O.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Munkhammar, J.
    Economic estimations of a PV park combined with stationary battery storage operation on day-ahead and frequency regulation markets2023In: IET Conference Proceedings, Institution of Engineering and Technology , 2023, no 20, p. 683-690Conference paper (Refereed)
    Abstract [en]

    As interest in deploying Battery Storage systems (BSSs) grows, a significant challenge is to determine the specific services that the BSS should provide to maximize profits. This study aims to determine the most profitable strategy and size of integrated grid-connected BSS with and without PV park for participating in Day-Ahead Market (DAM) and Frequency Regulation Market (FRM). The Frequency control services activate in response to changes in the electricity grid frequency, with BSS supporting during frequency fluctuations. The focus of this study is on the primary regulation within FRM. In this study, a BSS operation algorithm is evaluated in economic terms. The algorithm imports inputs like market prices, fees, tariffs, PV production, and chosen BSS service. Economic metrics include Net Present Value (NPV) and Internal Rate of Return (IRR). Real-world data from a Swedish PV park was used for case studies across three categories: BSS stand-alone, PV park alone, and PV-BSS combination. Results highlight that stand-alone BSS scenarios are superior to PV-BSS combination cases, showing a 73% Internal Rate of Return (IRR) for a 1000 kWh/400 kW BSS configuration. PV park alone participation in FRM and DAM shows marginal benefits compared to only acting on the spot market. The sensitivity analysis examining changes in prices for both DAM and FRM relative to 2022 reveals a significant negative change in revenue in 2020, which is explained by the higher and more fluctuating electricity prices. Lastly, the sensitivity analysis explores changes in the acceptance rate of bids in the future relative to 2022, as FCR products will be procured at a marginal price. These analyses indicate potential negative changes that may occur as the acceptance rate may decrease. © Energynautics GmbH.

  • 40.
    Kroner, Marie-Désirée
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Lundgren, Urban
    Wireless Communication, RISE Research Institutes of Sweden Borås, Sweden.
    Module Type Impacting Electromagnetic Emissions from Photovoltaic Systems2023In: The European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC), 2023, p. 020416-001-020416-019Conference paper (Refereed)
    Abstract [en]

    Radiated electromagnetic emissions of photovoltaic systems causing interference with radiocommunication can pose a major barrier to further increase photovoltaic penetration. This is particularly critical close to sensitive infrastructures such as hospitals, airports and, military-, public- and commercial-communication facilities. To understand the electromagnetic emission impact of each component and installation detail, we performed systematic electromagnetic emission measurements on comparable commercial photovoltaic systems in the frequency range 150 kHz to 30 MHz. Our measurements indicate that photovoltaic systems with module optimizers are the main cause of increased electromagnetic emissions. The results indicate that the choice of a specific module type can increase electromagnetic emission from systems with module optimizers, while changes in cable management and earthing do not substantially affect electromagnetic emissions. For the module optimizer measurements, emissions were significantly increased when replacing aluminum framed half-cut modules with frameless bifacial glass-glass modules. The results are relevant for photovoltaic-system designers and installers, enabling them to build photovoltaic systems with acceptable electromagnetic emission level.

  • 41.
    Kroner, Marie-Désirée
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology. Electrical Power Engineering, Luleå University of Technology, Skellefteå, Sweden.
    Urban, Lundgren
    Wireless Communication, RISE Research Institutes of Sweden, Borås, Sweden.
    Radiated Electromagnetic Emissions from Photovoltaic Systems – Measurement Results from Inverter and Modules2023In: 2023 International Symposium on Electromagnetic Compatibility – EMC Europe, 2023, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Radiated electromagnetic emissions of photovoltaic systems causing interference with radiocommunication can pose a major barrier to further photovoltaic penetration. This is particularly critical close to sensitive infrastructures such as hospitals, airports, and communication facilities. To understand the impact of each component and installation detail, we performed systematic emission measurements on comparable commercial photovoltaic systems in the range 150 kHz to 30 MHz. Our measurements indicate that systems with module optimizers are the main cause of increased emissions. The choice of a specific module type can increase emissions from inverter systems with module optimizers, while changes in cable management and earthing do not substantially affect emissions. For the module optimizer measurements, emissions were significantly increased when replacing aluminum framed half-cut modules with frameless bifacial glass-glass modules.

  • 42. Kumar, S.
    et al.
    Ramesh, M. R.
    Jeyaraj, P.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Institute of Technology Mandi, Himachal Pradesh, Mandi, India.
    Doddamani, M.
    Buckling behavior of non-uniformly heated 3D printed plain and functionally graded nanocomposites2023In: Polymer Composites, ISSN 0272-8397, E-ISSN 1548-0569, Vol. 44, p. 5450-5463Article in journal (Refereed)
    Abstract [en]

    The functionalized multi-walled carbon nanotubes (MWCNTs) (0.5–5 wt.%) are compounded with high density polyethylene (HDPE), and, subsequently, used for extruding nanocomposite filaments to fabricate nanocomposites (NCs) and functionally graded nanocomposites (FGNCs) through 3D printing. The 3D printed NCs are investigated for coefficient of thermal expansion (CTE), and buckling under different non-uniform temperature distributions (case-1: left edge heating, case-2: centre heating, and case-3: left and right edge heating). A significant reduction in CTE is observed with MWCNT addition and gradation. The highest reduction in CTE is observed for H5 (5 wt.% of MWCNT in HDPE) NC and H1 ⟶ H3 ⟶ H5 (FGNC-2) among the NCs and the FGNCs. It is noted that Tcr (critical buckling temperature) is highest for case-3 and lowest for case-2. The highest deflection is noticed in case-2, while no significant difference is observed in case-1 and case-3 heating conditions. It is also observed that Tcr increases with gradation and MWCNTs addition. The H5 NC and FGNC-2 exhibited the highest Tcr among the NCs and FGNCs, respectively. The maximum deflection is noticed for HDPE, whereas the minimum deflection is noticed for FGNC-2 and H-5 NC among the tested samples. The results also revealed that Tcr is very sensitive to type of heating. © 2023 Society of Plastics Engineers.

  • 43.
    Lovati, Marco
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology. Aalto University, Espoo, Finland.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Olsmats, Carl
    Dalarna University, School of Information and Engineering, Industrial Engineering and Management.
    Yan, Da
    Tsinghua University, Beijing, China.
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Agent Based Modelling of a Local Energy Market: A Study of the Economic Interactions between Autonomous PV Owners within a Micro-Grid2021In: Buildings, E-ISSN 2075-5309, Vol. 11, no 4, article id 160Article in journal (Refereed)
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  • 44.
    May, Ross
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Carling, Kenneth
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Does a smart agent overcome the tragedy of the commons in residential prosumer communities?2023Article in journal (Refereed)
  • 45.
    May, Ross
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    A multi-agent reinforcement learning approach for investigating and optimising peer-to-peer prosumer energy markets2023In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 334, article id 120705Article in journal (Refereed)
    Abstract [en]

    Current power grid infrastructure was not designed with climate change in mind, and, therefore, its stability, especially at peak demand periods, has been compromised. Furthermore, in light of the current UN’s Intergovernmental Panel on Climate Change reports concerning global warming and the goal of the 2015 Paris climate agreement to constrain global temperature increase to within 1.5–2 °C above pre-industrial levels, urgent sociotechnical measures need to be taken. Together, Smart Microgrid and renewable energy technology have been proposed as a possible solution to help mitigate global warming and grid instability. Within this context, well-managed demand-side flexibility is crucial for efficiently utilising on-site solar energy. To this end, a well-designed dynamic pricing mechanism can organise the actors within such a system to enable the efficient trade of on-site energy, therefore contributing to the decarbonisation and grid security goals alluded to above. However, designing such a mechanism in an economic setting as complex and dynamic as the one above often leads to computationally intractable solutions. To overcome this problem, in this work, we use multi-agent reinforcement learning (MARL) alongside Foundation – an open-source economic simulation framework built by Salesforce Research – to design a dynamic price policy. By incorporating a peer-to-peer (P2P) community of prosumers with heterogeneous demand/supply profiles and battery storage into Foundation, our results from data-driven simulations show that MARL, when compared with a baseline fixed price signal, can learn a dynamic price signal that achieves both a lower community electricity cost, and a higher community self-sufficiency. Furthermore, emergent social–economic behaviours, such as price elasticity, and community coordination leading to high grid feed-in during periods of overall excess photovoltaic (PV) supply and, conversely, high community trading during overall low PV supply, have also been identified. Our proposed approach can be used by practitioners to aid them in designing P2P energy trading markets.

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  • 46. Meng, Qinglong
    et al.
    Xi, Xuan
    Zhang, Xingxing
    Dalarna University, School of Information and Engineering, Energy Technology.
    Mourshed, Monjur
    Hui, Yue
    Evaluating multiple parameters dependency of base temperature for heating degree-days in building energy prediction2021In: Building Simulation, ISSN 1996-3599, E-ISSN 1996-8744, Vol. 14, p. 969-985Article in journal (Refereed)
  • 47.
    Momoh, Ozaveshe
    Dalarna University, School of Information and Engineering, Energy Technology.
    Impact of power quality on PV performance of grid connected systems2022Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The problem with the implementation of the PV generators is that majority of the UNDP offices are in developing and underdeveloped countries. Majority of these countries experience various problems with the power quality from the national electrical grid. There is also a second problem with the installed PV system, the problem is that the installed PV sources show a significant decrease in the expected annual yield ranging from 10 % – 60 % in some cases. The main aim of this thesis is to analyze the power quality in three countries (Nepal, Sao Tome and Namibia) and find the correlation between power quality and PV generation. This aim is done in five steps. The first step is the collection of measured data from the grid for a specific period of one year from July 2020 to August 2021. The collected data includes the current, voltage, power factor, frequency, reactive and active power. To achieve this, the Acuvim II power quality analyzer was sent to these three countries. In the second step, a literature review is done to research about power quality problems, identifying the power quality problems and analyzing the problems created by these identified power quality problems. In the three countries, undervoltage, overvoltage, swells, and sags where the main power quality problems which were recorded. The third step is a system case study process in which an in-depth analysis is done on the three PV systems and a simulation is done to understand the solar parameters which includes the specific yield, and performance ratio. The fourth step involves comparing the collected data from the PQ analyzer with the simulation results and determine the effects the power quality problems and system design have on the low annual yield. Also, the yearly amount of overvoltage and undervoltage in the three countries within the analysis period was analyzed. The voltage and fluctuation analysis also includes other power quality parameters which were measured. The collected parameters were analyzed and the correlation between the electrical grid requirements in the three countries were made with the recorded data. The final step involves recommending improvements and optimization techniques for the three systems to improve life cycle cost and long-term vision. Thus, analyzed results and simulated results are compared to evaluate the performance. The PV system in Namibia had the best grid conditions with all the grid parameters operating within the defined grid limits, there was a 30 % reduction in annual energy production in the Nepal system due to poor power quality conditions which included overvoltage, undervoltage, and frequency deviations. There was also a 50 % energy loss in the annual production of the PV systeminstalled in Sao Tome. Sao Tome also had the highest number of recorded outages with an average of 6 – 7 hours of outages recorded daily. Power quality problems recorded in Sao Tome included voltage fluctuation problems and frequency deviations.

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  • 48. Neelam, R.
    et al.
    Kulkarni, S. A.
    Bharath, H. S.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Institute of Technology Mandi, Himachal Pradesh, Mandi, India.
    Doddamani, M.
    Mechanical response of additively manufactured foam: A machine learning approach2022In: Results in Engineering (RINENG), ISSN 2590-1230, Vol. 16, article id 100801Article in journal (Refereed)
    Abstract [en]

    This paper uses ensemble and automated machine learning algorithms to predict the mechanical properties (tensile and flexural strength) of a three-dimensionally printed (3DP) foamed structure. The closed cell foams were made from the most commonly used thermoplastic, High-Density Polyethylene (HDPE). The hollow glass microspheres are infused in HDPE at varying volume %. The available data on these foams' mechanical properties are used by the chosen machine learning (ML) algorithms to propose the best suited algorithm for such a three-phased microstructure as these closed cell foams exhibit. Finally, the strength predictions from the models were validated using experimental data. The models were trained with nozzle temperature, bed temperature, and force values as input parameters. The output parameters predicted were the tensile and flexural strength. LightGBM outperforms all other models in terms of performance among ensemble-based models, while H2OAutoML outperforms all other models. All the ML algorithms produced models with greater than 95% accuracy. Finally, memory and time consumption for each model are presented. © 2022 The Authors

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  • 49.
    Nevell, Carl
    et al.
    Dalarna University, School of Information and Engineering, Energy Technology.
    Almquist, Lucas
    Dalarna University, School of Information and Engineering, Energy Technology.
    Mot en Grönare Industri: Potential för värmeåtervinning från industriella glödgningsugnar2023Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The current global situation has intensified the interest in energy-efficient solutions within the industry, aiming to reduce costs, increase self-sufficiency, and be more environmentally friendly. In this study, the waste heat from three industrial annealing furnaces was analyzed to assess its potential for heat recovery. A quantitative analysis and calculations were conducted, which demonstrated that the waste heat has a potential energy of approximately 633 MWh per year. Most of this energy, around 431 MWh, can be utilized in the facility's radiators. However, other applications for the waste heat should be explored, as the industry in question typically utilizes heat recovery from large refrigeration compressors to meet a substantial portion of the heating demand in the radiator circuit. These refrigeration compressors were not in operation during the time this study was conducted.

  • 50. Pakere, I.
    et al.
    Kacare, M.
    Murauskaite, L.
    Huang, Pei
    Dalarna University, School of Information and Engineering, Energy Technology.
    Comparison of Suitable Business Models for the 5thGeneration District Heating System Implementation through Game Theory Approach2023In: Environmental and Climate Technologies, ISSN 2255-8837, Vol. 27, no 1, p. 1-15Article in journal (Refereed)
    Abstract [en]

    District Heating and Cooling (DHC) technology is widely recognised as a promising solution for reducing primary energy consumption and emissions. The 5th Generation District Heating and Cooling (5GDHC) network is the latest DHC concept characterised by low-temperature supply, bi-directional heating network operation, decentralised energy flows, and surplus heat sharing. Unlike the 4th Generation District Heating (4GDH) technology, the 5GDHC technology switched to a consumer/prosumer-oriented perspective. The introduction of 5GDHC solutions requires high investments, an important barrier to further developing DHC systems. Therefore, a novel pricing and business model could include introducing co-owners or energy managers into the system. Three different local market business models for 5GDHC at the community level have been tested. The reverse technical and economic simulation has been used for a feasibility study to determine the resources, business models, and combinations closest to the break-even point with lower costs and higher gains for all involved stakeholders. © 2023 Ieva Pakere et al., published by Sciendo.

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