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  • 301.
    Tonda, R.
    et al.
    University of Muhammadiyah Malang, Indonesia.
    Zalizar, L.
    University of Muhammadiyah Malang, Indonesia.
    Widodo, W.
    Setyobudi, R. H.
    University of Muhammadiyah Malang, Indonesia.
    Hermawan, D.
    University of Muhammadiyah Malang, Indonesia.
    Damat, D.
    University of Muhammadiyah Malang, Indonesia.
    Purbajanti, E. D.
    University of Diponegoro, Semarang, Indonesia.
    Prasetyo, H.
    University of Brawijaya, Malang, East Java, Indonesia .
    Ekawati, I.
    University of Wiraraja, Sumenep, East Java, Indonesia.
    Jani, Yahya
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Burlakovs, J.
    Institute of the Polish Academy of Sciences, Kraków, Poland.
    Wahono, S. K.
    Research Center for Food Technology and Processing - National Research and Innovation Agency Republic of Indonesia, Special Region of Yogyakarta, Indonesia.
    Anam, C.
    Universitas Islam Darul Ulum, Lamongan, Indonesia.
    Pakarti, T. A.
    Mayantara School, Malang, East Java, Indonesia.
    Susanti, M. S.
    Aura Statistics Consultant, Malang, East Java, Indonesia.
    Mahnunin, R.
    PT. Zakiyah Jaya Mandiri, Lumajang, East Java, Indonesia.
    Sutanto, A.
    University of Muhammadiyah Malang, Malang, East Java, Indonesia.
    Sari, D. K.
    PT. Zakiyah Jaya Mandiri, Lumajang, East Java, Indonesia.
    Hilda, H.
    CV. Harapan Jaya Abadi, Malang, East Java, Indonesia.
    Fauzi, A.
    University of Muhammadiyah Malang, Malang, East Java, Indonesia.
    Wirawan, W.
    University of Tribhuwana Tunggadewi, Malang, East Java, Indonesia.
    Sebayang, N. S.
    University of Muhammadiyah Palembang, Palembang, South Sumatera, Indonesia.
    Hadinoto, H.
    University of Lancang Kuning, Pekanbaru, Riau, Indonesia.
    Suhesti, E.
    University of Lancang Kuning, Pekanbaru, Riau 28266, Indonesia.
    Amri, U.
    University of Muhammadiyah Makassar, Makassar, South Sulawesi, Indonesia.
    Busa, Y.
    University of Muhammadiyah Enrekang, Enrekang, South Sulawesi Indonesia.
    Potential Utilization of Dried Rice Leftover of Household Organic Waste for Poultry Functional Feed2022In: Jordan Journal of Biological Sciences, ISSN 1995-6673, Vol. 15, no 5, p. 879-886Article in journal (Refereed)
    Abstract [en]

    Indonesia produced 30 × 106 t of waste in 2021; 40 % was organic and 276 × 103 t leftover rice. Meanwhile, broiler chicken farmers have been struggling with high feed costs to continue their production. Processing leftover rice into "aking-rice" is environmentally friendly, and it also provides alternative feed for chickens. "Aking-rice" is a type of resistant starch because it has undergone a gelatinization process that works as a synthesis of short-chain fatty acids that positively improve the function of the digestive tract because it increases the villi in the small intestine. This study analyzed the potential of “akingrice” in broiler chicken productivity. The experimental method was a completely randomized design with three treatments, five replications and 12 chickens in each unit. The treatments are T0 (100 % basal feed), T1 (80 % basal feed + 20 % “akingrice” spread on top of the basal feed), and T2 (80 % basal feed + 20 % "aking-rice" mix). Statistical analysis used ANOVA, and continued with LSD with observed variables, i.e. Feed Intake (FI), Average Daily Gain (ADG), Feed Conversion Ratio (FCR), and Performance Index (PI). The results showed that the highest FI values were T0 (99.02), T1 (97.45), and T2 (96.58). The highest ADG was T1 (40.40) then T0 (37.07) and the lowest was T2 (36.40). T1 has the lowest FCR (2.42) compared to T0 (2.68), T2 (2.66). The lowest FCR is T1 (2.42), then T2 (2.66) and the highest is T0 (2.68). The third variable was not significantly different, but the PI results showed a significant difference with the highest PI value T1 (433.84), while T0 (374.81) and T2 (372.67) were not different. Economic analysis also shows that the highest cost T0 (118 475) is significantly different from T1 (110 541) and T2 (109 558). The highest profit is shown by T1 (2 102) then T2 (1 063) and T0 (507). In conclusion, the use of "aking-rice" can increase the performance index with a higher ADG value and a lower FCR so that the costs are smaller and the profit is greater.

  • 302.
    Toorajipour, Reza
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Chirumalla, Koteshwar
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Johansson, Glenn
    Lund University, Sweden.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Implementing circular business models for electric vehicle battery second life: Challenges and enablers from an ecosystem perspective2023Manuscript (preprint) (Other academic)
  • 303.
    Toorajipour, Reza
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Chirumalla, Koteshwar
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Parida, V.
    Lulea University of Technology, Sweden.
    Johansson, G.
    Lund University, Sweden.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Preconditions of Circular Business Model Innovation for the Electric Vehicle Battery Second Life: An Ecosystem Perspective2022In: Advances in Transdisciplinary Engineering, IOS Press BV , 2022, p. 279-291Conference paper (Refereed)
    Abstract [en]

    There is a strong interconnection between transportation and sustainability. Therefore, electric vehicles (EVs) have received a great deal of attention, and their sales and market share have been growing rapidly. Soon, a huge amount of EV batteries will reach their end of life that need to be handled appropriately. The second life applications are suggested as a potential solution. However, to implement such applications, there is a need to shift towards new business models, which have a central focus on circularity. Therefore, this paper studies preconditions of circular business model innovation (CBMI) for the electric vehicle battery second life from the ecosystem perspective. It also identifies current (as is) and upcoming (to be) business models. Data has been collected from fourteen companies representing the electric vehicle battery second life (EVBSL) ecosystem. Results show three types of current and three types of upcoming business models in the EVBSL ecosystem. Further, four preconditions for CBMI were found, namely, 2nd life value proposition, 2nd life value network development, 2nd life-based revenue model, and digital technologies. 

  • 304.
    Tsirikoglou, P.
    et al.
    Limmat Scientific AG, Zurich, Switzerland.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kalfas, A. I.
    Aristotle University, Department of Mechanical Engineering, Thessaloniki, Greece.
    Contino, F.
    Université Catholique de Louvain, Thermodynamics and Fluid Mechanics Group, Louvain, Belgium.
    Optimization in probabilistic domains: an engineering approach2020In: Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications, Elsevier , 2020, p. 391-414Chapter in book (Other academic)
    Abstract [en]

    The uncertain nature of engineering variables and parameters dictates the transition of engineering design from global exploration and deterministic optimization to the uncertainty quantification and probabilistic optimization. Therefore, such optimization processes and algorithmic frameworks emerge as key aspects of engineering design, aiming to derive new solutions to all sorts of products and processes. Nature-inspired computing is one of the main drivers, coupled to the continuously evolving engineering models. In this chapter, several aspects of probabilistic optimization are analyzed from an engineering application perspective to highlight the advances and shortcomings as moving towards the efficient global optimization in probabilistic domains. Moreover, the definition of engineering optimization cases, uncertainty quantification techniques, surrogate modeling, and other common case-related challenges are discussed. Finally, this conceptual analysis focuses mainly on engineering models from the aircraft design field, which can provide different types of engineering cases.

  • 305.
    Tu, R.
    et al.
    Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Jiao, Y.
    Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Qiu, Rui
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Liao, Q.
    Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Xu, N.
    Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Du, J.
    Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Liang, Y.
    Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Energy saving and consumption reduction in the transportation of petroleum products: A pipeline pricing optimization perspective2023In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 342, article id 121135Article in journal (Refereed)
    Abstract [en]

    Pipeline transportation is a low-energy and economical mode of transporting petroleum products in the downstream supply chain, however, there is almost no theoretical research on its pricing strategies. The unreasonable pricing strategy has resulted in low utilization of multi-product pipeline capacity as well as high energy consumption of petroleum products transportation. Therefore, this paper aims to improve pipeline turnover and promote the low-carbon transportation market from the perspective of pipeline pricing optimization. We propose an integrated framework for multi-product pipelines that couples pricing strategy and logistics optimization model. This framework simulates the pricing behavior of the pipeline carrier and the corresponding logistics planning behavior of the oil shipper. We apply the framwork to 10 pipeline pricing schemes for two regions in China with different logistics structures, and analyze the economic and environmental benefits of the new strategy. The results show that the well-performing scheme can increase pipeline carriers' revenue by 11.41 million CNY per month, significantly improve the competitive advantage of long-distance pipelines, and reduce energy consumption by 272 tce. Based on these findings, we provide recommendations for policymakers at four levels. In conclusion, the new pricing strategy will help reverse the disadvantageous situation of the pipeline in the competitive market and promote energy conservation in the petroleum products logistics industry. 

  • 306.
    Vadiee, Amir
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    A non-linear gray-box model of buildings connected to district heating systems2022In: Energy Proceedings, 2022Conference paper (Refereed)
    Abstract [en]

    Traditional building automation controllers are having low performance in dealing with non-linear phenomena. In recent years, model predictive control (MPC) has become a notable control algorithm for building automation system capable of handling non-linear processes. Performance of model-based controllers, such as MPC, is depending on reasonably accurate process models. For a building using baseboard radiator heater, a non-linear model is a more reliable representation of heat distribution system. Therefore, this study aims to present a non-linear gray-box model for a residential building connected to the local district heating network that is equipped with radiator heat emitters. The model is supposed to forecast the indoor air temperature as well as the radiator secondary return temperature. The model is validated using measurements collected from a building in Västerås, Sweden. In addition to a better accuracy, another motivation behind using a non-linear heating circuit model is to enhance its generalization performance. With the added benefits of accuracy and generalization, this model is expected to extend practical MPC implementation for such buildings.

  • 307.
    Vadiee, Amir
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Chapter 7 - Solar heating and cooling applications in agriculture and food processing systems2022In: Solar Energy Advancements in Agriculture and Food Production Systems, Elsevier, 2022, p. 237-270Chapter in book (Other academic)
    Abstract [en]

    The agricultural and food processing industries are considered key sectors aligned with sustainable development goals, as they play an important role in sustainable rural development. About 30% of global energy is used in these sectors, particularly thermal energy in both heating and cooling applications. Research considers solar energy technologies to be promising ways to increase system flexibility and lead to climate mitigation impacts. Different types of solar heating and cooling systems can supply a wide range of desired operating temperatures for various applications in agricultural and food processing systems. The main applications of solar thermal energy systems in the agricultural and food processing industries are solar air heaters for drying and dehydration processes, solar water heaters for both heat and food processing systems, solar cooking systems, solar heating and cooling systems for maintaining greenhouse climate, and solar-powered cooling systems for both food processing and space cooling. Furthermore, some innovative active and passive integrated solar systems such as the solar-blind concept remain underdeveloped. Further advances in solar energy integration systems in the agricultural and food processing industries will lead to considerable climate mitigation impacts as well as more resilient energy management in this sector.

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  • 308.
    Vincevica-Gaile, Zane
    et al.
    Department of Environmental Science, University of Latvia, LV-1004 Riga, Latvia.
    Sachpazidou, Varvara
    Department of Biology and Environmental Science, Linnaeus University, 391 82 Kalmar, Sweden.
    Bisters, Valdis
    Department of Environmental Science, University of Latvia, LV-1004 Riga, Latvia.
    Klavins, Maris
    Department of Environmental Science, University of Latvia, LV-1004 Riga, Latvia.
    Anne, Olga
    Department of Engineering, Klaipeda University, LT-91225 Klaipeda, Lithuania.
    Grinfelde, Inga
    Laboratory of Forest and Water Resources, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia.
    Hanc, Emil
    Mineral and Energy Economy Research Institute, Polish Academy of Sciences, 31-261 Krakow, Poland.
    Hogland, William
    Department of Biology and Environmental Science, Linnaeus University, 391 82 Kalmar, Sweden.
    Ibrahim, Muhammad Asim
    Department of Biology and Environmental Science, Linnaeus University, 391 82 Kalmar, Sweden.
    Jani, Yahya
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kriipsalu, Mait
    Chair of Rural Building and Water Management, Estonian University of Life Sciences, 51014 Tartu, Estonia.
    Pal, Divya
    Department of Biology and Environmental Science, Linnaeus University, 391 82 Kalmar, Sweden.
    Pehme, Kaur-Mikk
    Chair of Rural Building and Water Management, Estonian University of Life Sciences, 51014 Tartu, Estonia.
    Shanskiy, Merrit
    Chair of Soil Science, Estonian University of Life Sciences, 51014 Tartu, Estonia.
    Saaremäe, Egle
    Chair of Rural Building and Water Management, Estonian University of Life Sciences, 51014 Tartu, Estonia.
    Pilecka-Ulcugaceva, Jovita
    Laboratory of Forest and Water Resources, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia.
    Celms, Armands
    Department of Land Management and Geodesy, Latvia University of Life Sciences and Technologies, LV-3001 Jelgava, Latvia.
    Rudovica, Vita
    Department of Analytical Chemistry, University of Latvia, LV-1004 Riga, Latvia.
    Hendroko Setyobudi, Roy
    Waste Laboratory, University of Muhammadiyah Malang, Malang 65114, Indonesia.
    Wdowin, Magdalena
    Mineral and Energy Economy Research Institute, Polish Academy of Sciences, 31-261 Krakow, Poland.
    Zahoor, Muhammad
    Department of Biochemistry, University of Malakand, Chakdara Dir Lowever 18800, Khyber Pakhtunkhwa, Pakistan.
    Aouissi, Hani Amir
    Scientific and Technical Research Centre on Arid Regions (CRSTRA), Biskra 07000, Algeria.
    Krauklis, Andrey E.
    Institute for Mechanics of Materials, University of Latvia, LV-1004 Riga, Latvia.
    Zekker, Ivar
    Institute of Chemistry, University of Tartu, 50411 Tartu, Estonia.
    Burlakovs, Juris
    Mineral and Energy Economy Research Institute, Polish Academy of Sciences, 31-261 Krakow, Poland.
    Applying Macroalgal Biomass as an Energy Source: Utility of the Baltic Sea Beach Wrack for Thermochemical Conversion2022In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 21, article id 13712Article in journal (Refereed)
    Abstract [en]

    Global resource limits and increasing demand for non-fossil energy sources have expanded the research on alternative fuels. Among them, algal biomass is designated as a third-generation feedstock with promising opportunities and the capability to be utilized for energy production in the long term. The paper presents the potential for converting beach wrack containing macroalgal biomass into gaseous fuel as a sustainable option for energy production, simultaneously improving the organic waste management that the coastline is facing. Beach wrack collected in the northern Baltic Sea region was converted by gasification technology applicable for carbon-based feedstock thermal recovery, resulting in syngas production as the main product and by-product biochar. Proximate and ultimate analysis, trace and major element quantification, detection of calorific values for macroalgal biomass, and derived biochar and syngas analysis were carried out. A higher heating value for beach wrack was estimated to be relatively low, 5.38 MJ/kg as received (or 14.70 MJ/kg on dry basis), but produced syngas that contained enough high content of CH4 (42%). Due to macroalgal biomass specifics (e.g., high moisture content and sand admixture), an adjusted gasification process, i.e., the combination of thermochemical procedures, such as mild combustion and pyrolytic biomass conversion, might be a better choice for the greater economic value of biowaste valorization

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  • 309.
    Vouros, Stavros
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Diamantidou, Dimitra-Eirini
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Teaching optimization of thermal and fluid machinery in the post-pandemic era2023In: Proceeding of the ASME Turbo Expo 2023, AMER SOC MECHANICAL ENGINEERS , 2023, Vol. 6, article id v006t07a003Conference paper (Refereed)
    Abstract [en]

    Higher education has been crucially impacted by the pandemic during the past years. Despite the associated challenges, a wide portfolio of digital literacies has been developed for the delegates. This work evaluates the introduction of digital tools into in-person education. The “Process Optimization” course at Mälardalen University is reformed to operate in a digitally enhanced classroom mode. The course covers a variety of optimization methods applied on thermal and fluid machinery such as systems of compressors, pumps and heat exchangers, heat and power plants, aircraft trajectories and propulsion systems. The constructive alignment is presented to illustrate links between learning objectives, learning activities, and assessment tasks. A series of digital tools is introduced to elevate learning experience prior, during, and after class time. Those comprise digital quizzes, a video channel, polls, a digital whiteboard, and a digital forum. The course is systematically instrumented, yielding a vast set of statistics for evaluating the effectiveness of digital tools as well as engagement levels for learners. The contribution of digitalization into standardizing the formative and summative assessment is discussed. It is observed that digital tools complement the participation into pre- and post-classroom activities. An interactive and digitalized course evaluation activity is also designed. This allowed learners and educators to productively exchange feedback in an inclusive manner. The accrued data provides insight into the impact of digitalization on the delivery of an applied engineering course. Lessons learnt comprise quantitative and qualitative outcomes arising from the perspectives of both learners and teachers. Guidelines and recommended practices are provided for the penetration of digital tools into synchronous and asynchronous learning activities. This paper identifies opportunities as well as space for improvement arising from the penetration of digital tools into the new era for education.

  • 310.
    Vouros, Stavros
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Hiebl, David
    Mälardalen University.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Impact of boundary layer ingestion on the performance of propeller systems for hybrid electric aircraft2022In: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2022, Vol. 1, article id V001T01A025Conference paper (Refereed)
    Abstract [en]

    Boundary layer ingestion (BLI) has demonstrated potential for reduced thrust requirements, fuel consumption and environmental impact. An integrated approach is developed for evaluating the performance of propeller systems including BLI propulsors. A rotor model based on lifting-line theory is coupled with a high-order panel method and an integral boundary layer formulation. The impact of BLI on single propeller performance maps is quantified, with efficiencies up to 15% higher compared to uniform freestream conditions. A design space exploration framework is developed for the analysis of BLI effects at propeller system level, including the impact of weight differentiation, installation technology factors, thrust split between rotors and electrical transmission losses. A reference 19-passenger aircraft featuring two wing-mounter propellers is compared with a series of conceptual designs featuring an aftfuselage BLI propeller and two wing-mounted propellers. A system-wide power saving coefficient is derived for the quantification of performance deltas between the conceptual and the reference system, including all propulsors. For systems with BLI aerodynamic benefits entirely negated by weight penalties, and electrical transmission losses of 10%, power savings of 1.5% are accrued. In a technologically advanced system with 2% reduced thrust requirements due to BLI and 3% transmission losses, power savings rise to 6.5%. This work reveals the anticipated performance potential and limitations of BLI propeller systems for the electrified future fleet.

  • 311.
    Vouros, Stavros
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kavvalos, Mavroudis
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Sahoo, Smruti
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Enabling the potential of hybrid electric propulsion through lean-burn-combustion turbofans2021In: Journal of the Global Power and Propulsion Society, ISSN 2515-3080, Vol. 5, p. 164-176Article in journal (Refereed)
    Abstract [en]

    Hybrid-electric propulsion has emerged as a promising technology to mitigate the adverse environmental impact of civil aviation. Boosting conventional gas turbines with electric power improves mission performance and operability. In this work the impact of electrification on pollutant emissions and direct operating cost of geared turbofan configurations is evaluated for an 150-passenger aircraft. A baseline two-and-a-half-shaft geared turbofan, representative of year 2035 entry-into-service technology, is employed. Parallel hybridization is implemented through coupling a battery-powered electric motor to the engine low-speed shaft. A multidisciplinary design space exploration framework is employed comprising modelling methods for multi-point engine design, aircraft sizing, performance and pollutant emissions, mission and economic analysis. A probabilistic approach is developed considering uncertainties in the evaluation of direct operating cost. Sensitivities to electrical power system technology levels, as well as fuel price and emissions taxation are quantified at different time-frames. The benefits of lean direct injection are explored along short-, medium-, and long-range missions, demonstrating 32% NOx savings compared to traditional rich-burn, quick-mix, lean-burn technologies in short-range operations. The impact of electrification on the enhancement of lean direct injection benefits is investigated. For hybrid-electric powerplants, the take-off-to-cruise turbine entry temperature ratio is 2.5% lower than the baseline, extending the corresponding NOx reductions to the level of 46% in short-range missions. This work sheds light on the environmental and economic potential and limitations of a hybrid-electric propulsion concept towards a greener and sustainable civil aviation. 

  • 312.
    Vörösmarty, C. J.
    et al.
    Advanced Science Research Center, City University of New York, New York, NY, United States.
    Campana, Pietro Elia
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Jewitt, G.
    IHE Delft Institute for Water Education Delft, Delft, Netherlands; Water Resources Research, University of KwaZulu-Natal Durban, Durban, South Africa.
    Lawford, R.
    Department of Computer, Mathematical & Natural Sciences (Retired), Morgan State University, Baltimore, MD, United States.
    Wuebbles, D.
    Department of Atmospheric Science, University of Illinois at Urbana-Champaign, Champaign, IL, United States.
    Editorial: Food-energy-water systems: achieving climate resilience and sustainable development in the 21st century2023In: Frontiers in Environmental Science, E-ISSN 2296-665X, Vol. 11, article id 1334892Article in journal (Refereed)
  • 313.
    Wang, C.
    et al.
    Department of Information and Communication Engineering, Tongji University, Shanghai, China.
    Li, X.
    Department of Information and Communication Engineering, Tongji University, Shanghai, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    nRole of input features in developing data-driven models for building thermal demand forecast2022In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 277, article id 112593Article in journal (Refereed)
    Abstract [en]

    The energy consumption of buildings accounts for a major share in the modern society. Accurate forecast of building thermal demand is of great significance to both building management systems and heat distribution networks. Machine learning models driven by abundant load data have demonstrated their great capability in predicting real-world consumption patterns and trends. A large number of input features have been considered in the literature for developing data-driven models. However, a thorough analysis regarding their importance is currently lacking. This work first presents a review on the commonly considered features in building thermal demand prediction models, and focuses particularly on their influences. To further facilitate investigating the impacts of various input features, based on a four-year dataset collected from a district heating system with 13 input features, a deep learning model, the long short-term memory (LSTM) network, is employed for a real-world case study. Our results suggest that the past load, outdoor temperature, and hour index have the greatest influence, and should be primarily considered in building thermal demand forecast models. For the studied case, they lead to an RMSE of 12.231 MW and a CV-RMSE of 5.814 %. Additionally involving wind speed and day index is also useful, which improves the RMSE to 11.971 MW and CV-RMSE to 5.691 %. On the contrary, including all available features does not achieve a bettery accuracy, in which RMSE and CV-RMSE are 12.349 MW and 5.871 %. 

  • 314.
    Wang, F.
    et al.
    Faculty of Maritime and Transportation, Ningbo University, Ningbo, 315211, China.
    Nian, V.
    Centre for Strategic Energy and Resources, Singapore.
    Campana, Pietro Elia
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Jurasz, Jakob
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Wrocław University of Science and Technology, Wrocław, Poland.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Chen, L.
    Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi'an Jiaotong University, Shaanxi, Xi'an, 710049, China.
    Tao, W. -Q
    Key Laboratory of Thermo-Fluid Science and Engineering of MOE, School of Energy and Power Engineering, Xi'an Jiaotong University, Shaanxi, Xi'an, 710049, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Do ‘green’ data centres really have zero CO2 emissions?2022In: Sustainable Energy Technologies and Assessments, ISSN 2213-1388, E-ISSN 2213-1396, Vol. 53, article id 102769Article in journal (Refereed)
    Abstract [en]

    The claim of a green data centre is generally made based on a net-zero CO2 emission through a ‘balance-sheet’ approach, which considers renewable electricity through on-site installation or purchase agreement as abatement measures against the use of fossil electricity from the electric grid on an annual basis. However, when the hourly dynamic fuel mix is accounted for in the assessment, the annual net-zero energy approach does not lead to a true carbon neutral data centre. In response, two approaches based on net-zero energy and net-zero CO2 emission respectively are proposed and investigated regarding the goal of net-zero CO2 emission. A data centre in Singapore with typical load profiles is used as a case study, different scenarios considering climate change and projected future energy are defined to examine the impacts of dynamic energy mix on the net CO2 emission of the data centre. The net-zero energy approach is found to result in significant amount of annual CO2 emissions. In comparison, the net-zero CO2 emission approach can assure a true net-zero CO2 emission, but this approach will require an increase of PV capacity by 20% and 60% as compared to the net-zero energy approach based on assessment for the year 2030 and 2050, respectively.

  • 315.
    Wang, Fengjuan
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Business School, Sichuan University, Chengdu, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Xu, J.
    Business School, Sichuan University, Chengdu, China.
    Resilience evaluation framework towards urban power system2021In: Energy Proceedings, Scanditale AB , 2021, Vol. 16Conference paper (Refereed)
    Abstract [en]

    As the increased frequency, intensity and duration of extreme weather events have significantly challenged power systems, greater attention has been focused on the development of resilient power systems. Taking a physical-cyber-human system perspective, this paper establishes a multi-criteria resilience evaluation framework for urban power systems, in which two principal elements responsible for power system function degradation are described, and fifteen (eleven objective and four subjective) power system resilience evaluation indicators are identified. Fuzzy hesitant judgement and a TOPSIS aggregation method are applied for the evaluation to minimize expert divergence and maximize group consensus. The evaluation method is then applied to four Chinese municipalities: Shanghai, Beijing and Chongqing, and Tianjin. It was found that Beijing’s resilience was the best of the four but overall the urban power system resiliencies were not enough in the face of extreme event challenges.

  • 316.
    Wang, Fengjuan
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Business School Sichuan University, Chengdu, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Xu, Jiuping
    Business School Sichuan University, Chengdu, China.
    Yan, Zhouxingyu
    South Kent School, South Kent, Connecticut, USA.
    Chen, Dan
    Electricity Reliability Management Center, China Electricity Council, Beijing, China.
    Physical–cyber–human framework‐based resilience evaluation toward urban power system: Case study from ChinaIn: Risk Analysis, ISSN 0272-4332, E-ISSN 1539-6924Article in journal (Refereed)
    Abstract [en]

    Because the increased frequency, intensity, and duration of extreme weather events have significantly challenged power systems, there has been an increased interest in resilient power systems. This article establishes a multicriteria resilience evaluation framework for urban power systems from a physical-cyber-human system perspective, in which the two principal elements responsible for power system function degradation are described, the three major domains comprising urban power systems are explained, four core capacities that positively contribute to power system resilience are proposed, and 15 (11 objective and four subjective) power system resilience evaluation indicators are identified. Fuzzy hesitant judgment and a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) aggregation method are employed to minimize the expert divergence and maximize the group consensus. A validation method is designed and a comparison with commonly applied performance-based and attributes-based evaluation methods is conducted. The applicability of the evaluation framework is verified using data from four Chinese municipalities: Shanghai, Beijing, Chongqing, and Tianjin. It was found that Shanghai's resilience was the best, and Chongqing's physical resistance disadvantages would result in the greatest difficulties in coping with extreme event disturbances. Physical, cyber, and human domain resilience enhancement strategies are given for different cities separately. This study provides a practical tool to evaluate, compare, and enhance power system resilience for governments and public utilities. 

  • 317.
    Wang, L.
    et al.
    College of Chemical Engineering, Qingdao University of Science and Technology, Qingdao, 266042, China.
    Huang, X.
    Institute of Building Environment and Sustainability Technology, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
    Babaei, M.
    Department of Chemical Engineering, School of Engineering, The University of Manchester, Manchester, M13 9PL, United Kingdom.
    Liu, Z.
    Department of Power and Electrical Engineering, Northwest A&F University, Yangling, 712100, China.
    Yang, X.
    Institute of Building Environment and Sustainability Technology, School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, 710049, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Renewable Energy Research Group (RERG), Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
    Full-scale utilization of geothermal energy: A high-efficiency CO2 hybrid cogeneration system with low-temperature waste heat2023In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 403, article id 136866Article in journal (Refereed)
    Abstract [en]

    The utilization of geothermal energy is becoming increasingly important in the current transition towards sustainable energy sources. Among the various methods of utilizing geothermal energy, the use of hybrid geothermal power plants that exploit CO2 fluid for preheating in electricity generation has been identified as an attractive approach. Additionally, the shallow ground source heat pump (SGSHP) has been proven to be superior in previous experimental studies. However, the full-scale utilization of geothermal energy, through generating electricity from geothermal power plants and applying waste heat with SGSHPs for auxiliary heating, needs further exploration. This study proposes a novel CO2 hybrid geothermal system that incorporates a GSHP heating system. The hybrid geothermal system uses CO2 as the underground working fluid, and the electricity and waste heat are used to assist the GSHP for heating, ventilation, and air conditioning. The proposed system can produce 11.41 MW of electricity, 80 °C of hot water, and 34.76 MW of cold energy by driving 50 MW of the geothermal heat. Through a comprehensive analysis of the economy, energy, exergy, and environment, the results demonstrate that the maximum exergy damage of the refrigeration power cycle is 37999.33 kW, which has the highest exergy losses. The exergy loss of the steam turbine heat power conversion in the geothermal power generation process is the highest, but this loss can be effectively reduced through heat integration. The optimal cooling temperature of the coupled system should be set at 8 °C, and it has a good investment prospect. In summary, the CO2 hybrid geothermal system can realize effective cogeneration and fully utilize geothermal energy. Therefore, it has great potential to contribute to the transition towards a sustainable energy future. 

  • 318.
    Wang, L.
    et al.
    School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, China.
    Shao, Y.
    School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, China.
    Wang, C.
    School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, China.
    Tang, C.
    Mechanical Engineering College, Xi’an Shiyou University, Xi’an, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Sundén, B.
    Department of Energy Sciences, Lund University, Lund, Sweden.
    Che, D.
    School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, China.
    Design on CO2 capture based on adsorption-absorption integration and energy storage for energy supply buildings with fixed carbon emissionIn: International Journal of Green Energy, ISSN 1543-5075, E-ISSN 1543-5083Article in journal (Refereed)
    Abstract [en]

    A novel design for the energy storage by adsorption-absorption for the partial CO2 capture of the energy supply buildings with fixed CO2 emission is proposed. The new design successfully utilizes the attainment of the low energy consumption and implements energy storage through adsorption part, overcoming the deficiencies of poor selectivity through absorption part. Numerical approaches have been developed for modeling the adsorption-absorption procedure, while attaining satisfactory agreement with experimental data. The adsorption process is modeled based on the finite volume method, and the absorption process is simulated based on the double-film theory and the rate-based model. The issue of operating parameters upon system assessments has received considerable critical attention by numerical implementations. The results show that the mass fraction of CO2 in the flue gas has been increased to 39.0%. The comprehensive enhancement effects are instrumental at a height of 20 m in the absorption tower. As the CO2 concentration of the flue gas increases from 5.0% to 20.0%, the absorbent flow, absorber diameter, and reboiler specific load decrease by 13.0%, 42.1%, and 16.6%, in respective. The present analysis and design will provide guidance and gain fresh prominence with advantages in the CO2 capture and purification. 

  • 319.
    Wang, S.
    et al.
    Institute for Advanced Technology, Shandong University, Jinan, 250061, China.
    Dong, Beibei
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Gustafsson, K.
    Department of Sustainable Development, Environmental Science and Engineering (SEED), Royal Institute of Technology (KTH), Stockholm, Sweden.
    Ma, C.
    Institute for Advanced Technology, Shandong University, Jinan, 250061, China.
    Sun, Q.
    Institute for Advanced Technology, Shandong University, Jinan, 250061, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Assessing the CO2 capture potential for waste-fired CHP plants2023In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 428, article id 139379Article in journal (Refereed)
    Abstract [en]

    The integration of CO2 capture with biomass-fired power plants has attracted much attention due to its ability to achieve negative emissions. Waste-fired combined heat and power (CHP) plants with CO2 capture, on the other hand, has received little attention, and their potential remains unclear. This study aims to identify the possible range of the amount of captured CO2 and investigate the impact of CO2 capture on the performance of waste-fired CHP plants. Since heat is the primary product of CHP plants, it is important to maintain heat production unchanged when CO2 capture is integrated. Based on this prerequisite, two operating strategies (OS) were investigated, which correspond to the upper and lower boundaries of CO2 capture: OS1 was to maximize the amount of captured CO2 while keeping the heat supplied to the district heating (DH) network unchanged; and OS2 was to maximize CO2 capture while keeping both supplied heat and generated electricity unchanged. To obtain more accurate results regarding the CO2 capture, a dynamic model developed in Aspen Hysys™ was utilized to simulate monoethanolamine (MEA) based chemical absorption for CO2 capture. By using real dynamic data from a waste-fired CHP plant, dynamic simulation results showed that the highest amount of captured CO2, which was achieved in OS1, was 401 kton/year, corresponding to a CO2 capture ratio of 82%; while the lowest amount of captured CO2, which was achieved in OS2, was 99 kton/year, corresponding to a CO2 capture ratio of 20%. For OS1, the electricity generation was substantially decreased by 61%. When determining the negative emission, the emission resulted from the share of fossil fuel in the waste needs to be excluded. For the studied CHP plant, the fossil share was around 45%. As a result, only OS1 can achieve the negative emission, which was 181 kton/year; while OS2 still led to positive emissions. Compared to the plant without CO2 capture, the carbon intensity of heat was reduced from 0.405 ton/MWh to 0.091 ton/MWh in OS1 and 0.351 ton/MWh in OS2, while the carbon intensity of electricity was reduced from 0.409 ton/MWh to 0.072 ton/MWh in OS1 and 0.343 ton/MWh in OS2. 

  • 320.
    Wang, S.
    et al.
    Institute for Advanced Technology, Shandong University, Jinan, China.
    Hu, C.
    Tianjin University of Commerce, Tianjin, China.
    Sun, Q.
    Institute for Advanced Technology, Shandong University, Jinan, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Institute for Advanced Technology, Shandong University, Jinan, China.
    Wennersten, R.
    Institute for Advanced Technology, Shandong University, Jinan, China.
    A Method to Assess the CO2 Capture Potential from a Biomass-fired CHP2021In: Energy Proceedings, Scanditale AB , 2021, Vol. 16Conference paper (Refereed)
    Abstract [en]

    The bioenergy with CO2 capture and storage (BECCS) is an important solution to reduce CO2 emissions. This paper proposed a new method that can accurately access CO2 capture potential from a biomass-fired combined heat and power (BCHP). Chemical absorption is used as CO2 capture technology. By carefully considering the temperatures of the heat required by district heating and CO2 capture, the allocation of the available heat from flue gas condensation and extracted steam condensation for different purposes has been optimized. By using a real BCHP with a thermal capacity of 200MW as a case study, results show that the captured CO2 was 23.42t/day without any change in heat and power supply, which was 1.77% of the total released CO2.

  • 321.
    Wang, Xiaolin
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Market Oriented Transmission Expansion Planning2021In: Energy Proceedings, Scanditale AB , 2021, Vol. 16Conference paper (Refereed)
    Abstract [en]

    The reform of electricity market in China has made the market participants more active, which has posed a series of challenges for the power system planning with high penetration of renewable energy. This paper proposed a price-driven bi-level model for transmission expansion planning. At the upper level, the investment cost and operation cost of the transmission system is comprehensively considered. While at the lower level, the market clearing model is established, i.e., energy market and reserve market. The local marginal prices are obtained to guide the expansion planning of the upper level. By integrating the market clearing model of the lower level using Karush-Kuhn-Tucker condition, a mixed-integer nonlinear programming problem is formulated, which is further solved by a Heuristic method. In the case study, a modified Garver-6 bus system is utilized to verify the validity of the proposed method.

  • 322.
    Wang, Xiaolin
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zhang, Shengmin
    Swedish University of Agricultural Sciences,Sweden.
    Li, Haichao
    Swedish University of Agricultural Sciences,Sweden.
    Odlare, Monica
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Skvaril, Jan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Elevated CO2 effects on Zn and Fe nutrition in vegetables: A meta-analysis2024Conference paper (Refereed)
    Abstract [en]

    The atmospheric carbon dioxide (CO2) concentration has been progressively increasing since the onset of the Industrial Revolution and has already reached at around 420 μmol mol⁻¹ nowadays. It is well recognized that elevated CO2 concentration stimulates the yield for C3 crops, but it also simultaneously changes the essential nutrients. However, compared with the main crops, far less attention has been devoted to the effects of elevated CO2 concentration on vegetable growth and quality. Vegetables are highly recommended in daily diets due to their diverse range of beneficial compounds, such as vitamins, antioxidants, minerals, and dietary fiber.  In controlled greenhouse vegetable cultivation, elevated CO2 has been widely adopted as an agricultural practice for enhancing plant growth. Thus, understanding both vegetable growth and nutrient status is crucial to assess the potential impacts of elevated CO2 on future food security in both natural and controlled environments. However, much more attention has been paid to biomass enhancement, and elevated CO2 effects on nutrient quality are less recognized. Among the nutrients, Zinc (Zn) and Iron (Fe) are essential elements in humans. Previous studies have demonstrated a decreasing trend of Zn and Fe in main crops such as wheat and rice with increased CO2, while less is known about whether this alleviation effect on Zn and Fe can apply to vegetables. Therefore, a meta-analysis was conducted in this study to evaluate the influence of elevated CO2 concentration in the atmosphere on vegetable Fe and Zn status, and quantify the potential impact of future climate on nutrition security.

  • 323.
    Wang, Y.
    et al.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Yin, X.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Li, X.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Liu, S.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Zhu, X.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Ma, X.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Minimum Air Cooling Requirements for Different Lithium-Ion Battery Operating Statuses2024In: ASME Journal of Heat and Mass Transfer, ISSN 2832-8450, Vol. 146, no 10, article id 101501Article in journal (Refereed)
    Abstract [en]

    Battery energy storage systems (BESSs) play an important role in increasing the use of renewable energy sources. Owing to the temperature sensitivity of lithium-ion batteries (LIBs), battery thermal management systems (BTMSs) are crucial to ensuring the safe and efficient operation of BESSs. Previous works mainly focused on evaluating the performance of BTMS; however, little attention has been paid to the minimum cooling requirements of BESSs, which are important for optimizing the design and operation of BTMSs. To bridge the knowledge gap, this work investigated the performance of air cooling for a battery cabin under different charge/discharge (C) rates by using a computational fluid dynamics (CFD) model, which is coupled with a battery model. Simulation results show that the inlet airflow rate has the strongest influence. For the studied cases, when the battery operates at C-rates lower than 3, the inlet temperature should be controlled below 35 °C, and the gap between the batteries should be greater than 3 mm to meet the minimum heat dissipation requirement. At a C-rate of 0.5C, natural convection is sufficient to meet the cooling need, whereas at 1C or higher C-rates, forced convection has to be used. Increasing the number of batteries, for example, from 6 to 8, has negligible impact on the inlet flow required to assure the heat dissipation.

  • 324.
    Wang, Yuan
    et al.
    Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa 277-8563, Japan.
    Shi, Xiaodan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa 277-8563, Japan.
    Oguchi, Takashi
    Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa 277-8563, Japan;Center for Spatial Information Science, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa 277-8568, Japan.
    Archaeological Predictive Modeling Using Machine Learning and Statistical Methods for Japan and China2023In: ISPRS International Journal of Geo-Information, E-ISSN 2220-9964, Vol. 12, no 6, p. 238-238Article in journal (Refereed)
    Abstract [en]

    Archaeological predictive modeling (APM) is an essential method for quantitatively assessing the probability of archaeological sites present in a region. It is a necessary tool for archaeological research and cultural heritage management. In particular, the predictive modeling process could help us understand the relationship between past human civilizations and the natural environment; moreover, a better understanding of the mechanisms of the human-land relationship can provide new ideas for sustainable development. This study aims to investigate the impact of topographic and hydrological factors on archaeological sites in the Japanese archipelago and Shaanxi Province, China and proposes a hybrid integration approach for APM. This approach employed a conditional attention mechanism (AM) using deep learning and a frequency ratio (FR) model, in addition to a separate FR model and the widely-used machine learning MaxEnt method. The models' outcomes were cross-checked using the four-fold cross-validation method, and the models' performances were compared using the area under the receiver operating characteristic curve (AUC) and Kvamme's Gain. The results showed that in both study areas, the AM_FR model exhibited the most satisfactory performances.

  • 325.
    Warneryd, Martin
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Disruptive power: How distributed energy resources shape organizations and value logics in the future of electricity systems2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The electricity sector faces its largest transformation since its beginning about a century ago. Combinations of ageing electricity networks, removal of fossil supply sources and electrification of industry and transport sectors require vast efforts at all levels of society. Increasing renewable supply and demand sources means the growth of distributed energy resources. This thesis explores what this transformation means for society; how it affects the traditional actors and “new” active users in the energy system. Traditional actors include electrical utilities and distribution system operators; the “new” actors include different types of prosumers such as property companies and communities. In addition, the thesis investigates the nature of the energy transition towards an increasingly decentralized organization with the ultimate goal of increasing understanding of the potential values, organizational demands, institutional setup, and role changes required for this transformation. To investigate this, the thesis departs from theories of sustainable transition and applies analytical frameworks to different local energy systems cases, specifically small-scale solar PV plants and microgrids. The chosen empirical areas are motivated both by the recent growth in these technologies and that their features enable a complete decentralized energy system configuration, which is interesting as an extreme case in energy transition. Findings are presented in four different articles. One conclusion is that values from distributed energy resources go beyond what the current centralized system is able to provide.  Both traditional as well as “new” actors can benefit from these values, although it requires an understanding and endorsement of alternative “value logics” stemming from prosumer-oriented configurations. Further, the findings show the relation between values, engagement, and evolvement of roles and responsibilities for local energy systems.  These can be utilized by policymakers who desire to expand the renewable energy sector and, at the same time, increase incentives for users to actively engage in the energy system. However, the findings also show deep lock-ins in current centralized structures, both organizationally and institutionally, which need to be managed to realize the full potential of distributed energy resources. The thesis does, however, contribute with examples of proactive cases which can be utilized to learn from and create abilities among actors to transform along the decentralized energy transition pathway.

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  • 326.
    Warneryd, Martin
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Dalarna University, Falun, SE-791 88, Sweden.
    Karltorp, Kersti
    Jönköping international business school, Box 1026, Jönköping, SE-551 11, Sweden.
    Microgrid communities: disclosing the path to future system-active communities2022In: Sustainable Futures, E-ISSN 2666-1888, Vol. 4, article id 100079Article in journal (Refereed)
    Abstract [en]

    To increase sustainability in future energy systems, both technical and social measures must be taken. Microgrid communities offer local balancing of supply and demand, while also integrating the community as an active part of the energy system. This study investigates two cases of microgrid communities; how they were realized and what wider effects they offered its communities and other stakeholders. The study shows that the microgrid collaboration between community and utility offers a new organizational division that can overcome the traditional locked-in position of the utility. This brings forward communities as system-active participants and a sustainably beneficial energy system for the future.

  • 327.
    Waskitho, N. T.
    et al.
    Department of Forest, University of Muhammadiyah Malang, Indonesia .
    Amelida, R. D.
    Department of Forest, University of Muhammadiyah Malang, Indonesia .
    Wibowo, F. A. C.
    Department of Forest, University of Muhammadiyah Malang, Indonesia .
    Jani, Yahya
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Forest, University of Muhammadiyah Malang, Indonesia .
    Aryanti, N. A.
    Department of Forest, University of Muhammadiyah Malang, Indonesia .
    The Characteristic of Teak Growing in Three Areas (Mine, Non-Mining, and Ex-Mining) Forest Management Unit Parengan Bojonegoro, Indonesia2024In: BIO. Web. Conf., EDP Sciences , 2024, Vol. 104Conference paper (Refereed)
    Abstract [en]

    Bojonegoro Regency has an oil mining location where it is estimated that Indonesia's crude oil reserves are 25 % of national needs. The location is in Forest Management Unit (Kesatuan Pengelolaan Hutan - KPH) Parengan which has a teak forest (Tectona grandis L.) with a very close oil mining radius. The aim of the research is to determine the differences in the characteristics of teak growing places and to determine the types of petroleum fractions in active oil mines, former oil mines and those without oil mines. The research method uses a circle plot (17.8 m) with a Sampling Intensity (IS) of 20 % with data analysis results using a one sample test and a Least Significant Difference (LSD) alpha test of 5 %. The characteristics of the teak growing area at each location have different values for height, P content, C content, number of oil fractions and temperature. The types of petroleum fractions in active oil mines are naphtha, kerosene, fuel oil and wax. Ex-oil mines contain gasoline (premium), kerosene, aviation fuel, light gas, fuel oil, lubricating oil, wax and asphalt. In locations without oil mines there is kerosene, aviation fuel, gasoline (premium) and light gas.

  • 328.
    Wei, X.
    et al.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas.
    Liang, Y.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas.
    Qiu, R.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas.
    Liao, Q.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas.
    zhang, B.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas.
    Jiao, Y.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas.
    Zhang, Haoran
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan.
    Assessing benefits in the flexibility of refined oil logistics from pipeline network integration reform: A case from South China2022In: Chemical Engineering Science, ISSN 0009-2509, E-ISSN 1873-4405, Vol. 253, article id 117605Article in journal (Refereed)
    Abstract [en]

    The pipeline network integration reform enables unified management of pipelines from different entities. For refined oil logistics, this paper proposes a framework based on the MILP optimization model to quantify its flexibility. Considering the uncertainty, three disturbances occur in the logistics concurrently, and 10,000 simulations are performed to obtain the turnover cost. The ratio of pipeline transportation cost to the calculated average turnover cost is defined as the flexibility indicator. Taking China's largest refined oil pipeline network as an example, the results show that the flexibility rises 8.9% after the reform. The paper also quantifies the impact of the reform on logistics flexibility in South China, which is embodied in achieving lower freights and GHG emissions, lower impact by fluctuations, higher pipeline utilization, more efficient oil product turnover, and the avoiding of depot shortages when facing logistical disturbances. The underlying reasons for the results and 3E analysis are analyzed.

  • 329.
    Westholm, Lena Johansson
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Filter media for storm water treatment in sustainable cities: A review2023In: Frontiers in Chemical Engineering, ISSN 2673-2718, Vol. 5, article id 1149252Article in journal (Refereed)
    Abstract [en]

    Storm water treatment and management will be more important in the future due to climate changes, e.g., more frequent, and intense rain events that might cause flooding. To meet these challenges, low impact development (LID) technologies such as paved surfaces, green roofs and various bioretention systems have been suggested in urban areas. Various filter media, natural and engineered materials, have been used to amend the LID solutions in field experiments enhancing the removal of different contaminants present in storm water of different kinds. Researchers suggest locally available low-cost media having high capacity to remove pollutants. Other parameters to take into consideration when selecting filter media are clogging, hydraulic parameters. Climatic conditions in different regions, e.g., temperate, or cold climatic zones, do not seem to have a large impact on performance on LID solutions.

  • 330.
    Wu, W.
    et al.
    Tianjin University, Tianjin, 300072, China.
    Li, P.
    Tianjin University, Tianjin, 300072, China.
    Fu, X.
    Tianjin University, Tianjin, 300072, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wang, C.
    Tianjin University, Tianjin, 300072, China.
    Flexible Shifted-Frequency analysis for Multi-Timescale simulations of active distribution networks2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 321, article id 119371Article in journal (Refereed)
    Abstract [en]

    The growing proportion of distributed generators in active distribution networks highlights the importance of multi-timescale system dynamics. The electromagnetic transient simulators with detailed modeling have been widely used for high-fidelity simulations, which leads to a contradiction between the efficiency and accuracy in the studies of the multi-timescale property of the ADNs. The shifted-frequency analysis method integrated with state-space based exponential integration is introduced in this paper, which possesses both high accuracy of exponential integration and the advantage of system-level modeling. It accurately simulates the networks considering the nonlinearities with the advantage that allows large time-steps in the simulations wherein the signals have a small bandwidth around the fundamental frequency. A model-switching method based on the integral transformation of the shifted-frequency models is designed to address the inefficiency of multi-timescale simulations. In addition, a flexible discontinuity treatment in the shifted-frequency domain is introduced for the reduction of the errors brought by the detections and interpolations of discontinuities in the time-domain. Numerical studies are conducted considering the distributed generations, the shifted-frequency models are generated integrally from the original time-domain models. The results of the multi-timescale simulations with model-switching in different domains show the high efficiency of the proposed method, and the discontinuity treatment presents higher accuracy compared with the time-domain solution. Those combined advantages compose the flexible shifted-frequency analysis for the multi-timescale simulations of active distribution networks.

  • 331.
    Wu, Y.
    et al.
    The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Japan.
    Xia, T.
    The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Japan.
    Wang, Y.
    China University of Petroleum (Beijing), Changping, Beijing, China.
    Zhang, Haoran
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. The University of Tokyo, Japan.
    Feng, X.
    Xi'an Jiaotong University, Shaanxi, China.
    Song, X.
    Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China.
    Shibasaki, R.
    The University of Tokyo, Kashiwa-shi, Chiba, Japan.
    A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network2022In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 185, p. 302-320Article in journal (Refereed)
    Abstract [en]

    Offshore wind farms are increasingly becoming the focus of clean sources market because of the huge energy potential and fast-maturing technology. The existing researches normally optimize the wind turbine layout and two-dimensional cable routing independently. This work focuses on the synchronization optimization of site selection of the offshore wind farm, three-dimensional wind turbine layout and three-dimensional cable network routing based on meta-heuristic algorithms and geographic information systems. Several practical issues, i.e., restricted areas, power generation, cable network and energy loss, are taken into consideration. A two-layer model is proposed. The outer layer model is for the site selection and the wind turbine layout optimization. The inner layer model is for the obstacle-avoiding cable routing optimization. In this stage, the seabed terrain is considered for the first time. The proposed integrated model is complex and non-convex. Thus, a hybrid method including an improved ant colony optimization combined with genetic algorithm, dual-simplex method and Kruskal algorithm is proposed to search the solution more efficiently. The initialization stage of the hybrid method is improved from random assignment to directional assignment. The directional solution is obtained by the widely used genetic algorithm. A case study based on a real offshore wind farm is established to prove the effectiveness of the proposed methodology. The results show an over one million dollars increase in annual benefit compared with conventional methods.

  • 332.
    Xie, Y.
    et al.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, China.
    Wang, L.
    SINTEF Energy Research, P.O. Box 4761, Torgarden, 7465, Trondheim, Norway.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Westholm, Lena Johansson
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Carvalho, Lara
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yu, Z.
    Department of Energy and Petroleum Engineering, University of Stavanger, Stavanger, 4036, Norway.
    Yu, X.
    Key Laboratory of Pressure Systems and Safety, Ministry of Education, School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China.
    Skreiberg, Ø.
    SINTEF Energy Research, P.O. Box 4761, Torgarden, 7465, Trondheim, Norway.
    A critical review on production, modification and utilization of biochar2022In: Journal of Analytical and Applied Pyrolysis, ISSN 0165-2370, E-ISSN 1873-250X, Vol. 161, article id 105405Article in journal (Refereed)
    Abstract [en]

    There has been an increased interest in the production of sustainable biochar in the past years, as biochar shows versatile physicochemical properties and, can have a wide applicability in diverse fields. Comprehensive studies have been made to characterize biochar produced from various biomass materials, using different production technologies and under different process conditions. However, research is still lacking in correlating biochar properties needed for certain applications with (i) feedstock, (ii) biochar production processes and conditions and (iii) biochar upgrading and modification strategies. To produce biochar with desired properties, there is a great need to establish and clarify such correlations, which can guide the selection of feedstock, tuning and optimization of the production process and more efficient utilization of biochar. On the other hand, further elucidation of these correlations is also important for biochar-stakeholder and end-users for predicting physiochemical properties of biochar from certain feedstock and production conditions, assessing potential effects of biochar utilization and clearly address needs towards biochar critical properties. This review summarizes a wide range of literature on the impact of feedstocks and production processes and reactions conditions on the biochar properties and the most important biochar properties required for the different potential applications. Based on collected data, recommendations are provided for mapping out biochar production for different biochar applications. Knowledge gaps and perspectives for future research have also been identified regarding the characterization and production of biochar. 

  • 333.
    Xiong, R.
    et al.
    Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, China.
    Kim, J.
    Energy Storage and Conversion Laboratory, Department of Electrical Engineering, College of Engineering, Chungnam National University, Daejeon, South Korea.
    Shen, W.
    School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, Victoria, Australia.
    Lv, C.
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zhu, X.
    School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China.
    Zhao, W.
    Department of Vehicle Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
    Gao, B.
    Clean Energy Automotive Engineering Center, Tongji University, Shanghai, China.
    Guo, H.
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, China.
    Zhang, C.
    Department of Electrical Engineering, Harbin Institute of Technology, Harbin, China.
    Sun, F.
    Department of Electrical Engineering, Harbin Institute of Technology, Harbin, China.
    Key technologies for electric vehicles2022In: Green Energy and Intelligent Transportation, ISSN 2773-1537, Vol. 1, no 2, article id 100041Article in journal (Refereed)
  • 334.
    Xiong, R.
    et al.
    Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Beijing, Haidian District, 100081, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yu, Q.
    School of Automotive Engineering, Harbin Institute of Technology, Shandong, Weihai, 264209, China.
    Romagnoli, A.
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Singapore.
    Jurasz, J.
    Faculty of Environmental Engineering, Wrocław University of Science and Technology, Wrocław, 50-370, Poland.
    Yang, X. -G
    Department of Vehicle Engineering, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Beijing, Haidian District, 100081, China.
    Applications of AI in advanced energy storage technologies2023In: Energy and AI, ISSN 2666-5468, article id 100268Article in journal (Refereed)
  • 335.
    Xiong, R.
    et al.
    School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China.
    Li, X.
    School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zhu, B.
    School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China.
    Avelin, Anders
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Neural network and physical enable one sensor to estimate the temperature for all cells in the battery pack2024In: Journal of Energy Storage, ISSN 2352-152X, E-ISSN 2352-1538, Vol. 80, article id 110387Article in journal (Refereed)
    Abstract [en]

    The performance of lithium-ion batteries (LIBs) is sensitive to the operating temperature, and the design and operation of battery thermal management systems reply on accurate information of LIBs' temperature. This study proposes a data-driven model based on neural network (NN) for estimating the temperature profile of a LIB module. Only one temperature measurement is needed for the battery module, which can assure a low cost. The method has been tested for battery modules consisting of prismatic and cylindrical batteries. In general, a good accuracy can be observed that the root mean square error (RMSE) of esitmated temperatures is less than 0.8 °C regardless of the different operating conditions, ambient temperatures, and heat dissipation conditions.

  • 336.
    Xiong, R.
    et al.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Sun, Y.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Wang, C.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Tian, J.
    Joint Laboratory for Advanced Energy Storage and Application, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China.
    Chen, X.
    Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zhang, Q.
    Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
    A data-driven method for extracting aging features to accurately predict the battery health2023In: Energy Storage Materials, ISSN 2405-8289, E-ISSN 2405-8297, Vol. 57, p. 460-470Article in journal (Refereed)
    Abstract [en]

    Data-driven methods have been widely used for estimating the state of health (SOH) of lithium-ion batteries (LiBs). The aging process can be characterized by degrading features. To achieve high accuracy, a novel method combining four algorithms, i.e. the correlation coefficient, least absolute shrinkage and selection operator regression, neighborhood component analysis, and ReliefF algorithm, is proposed to select the most important features, which are derived from the measured and calculated parameters. To demonstrate the effectiveness of the proposed method, it is adopted to estimate the SOH of two types of LiBs: i.e. NCA and LFP batteries. Compared to the case using all features, using the selected features can improve the accuracy of SOH estimation by 63.5% and 71.1% for the NCA and LFP batteries, respectively. The method can also enable the use of data obtained in partial voltage ranges, based on which the minimum root mean square errors on SOH estimation are 1.2% and 1.6% for the studied NCA and LFP batteries, respectively. It demonstrates the capability for onboard applications. 

  • 337.
    Xu, N.
    et al.
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130022, China.
    Kong, Y.
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130022, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Chemical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Zhang, Y.
    School of Mechanical and Aerospace Engineering, Queen's University of Belfast, Northern Ireland, United Kingdom.
    Sui, Y.
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130022, China.
    Ju, H.
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130022, China.
    Liu, H.
    State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, 130022, China.
    Xu, Z.
    Research and Development Center, China FAW Group Corporation, China.
    Global optimization energy management for multi-energy source vehicles based on “Information layer - Physical layer - Energy layer - Dynamic programming” (IPE-DP)2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 312, article id 118668Article in journal (Refereed)
    Abstract [en]

    To reveal the energy-saving mechanisms of global energy management, we propose a global optimization framework of “information layer-physical layer-energy layer-dynamic programming” (IPE-DP), which can realize the unity of different information scenarios, different vehicle configurations and energy conversions. The deterministic dynamic programing (DP) and adaptive dynamic programming (ADP) are taken as the core algorithms. As a benchmark for assessing the optimality, DP strategy has four main challenges: standardization, real-time application, accuracy, and satisfactory drivability. To solve the above problems, the IPE-DP optimization framework is established, which consists of three main layers, two interface layers and an application layer. To be specific, the full-factor trip information is acquired from three scenarios in the information layer, and then the feasible work modes of the vehicle are determined in the physical layer based on the proposed conservation framework of “kinetic/potential energy & onboard energy“. The above lays a foundation for the optimal energy distribution in the energy layer. Then, a global domain-searching algorithm and action-dependent heuristic dynamic programming (ADHDP) model are developed for different information acquisition scenarios to obtain the optimal solution. To improve the computational efficiency under the deterministic information, a fast DP is developed based on the statistical rules of DP behavior, the core of which is to restrict the exploring region based on a reference SOC trajectory. Regarding the stochastic trip information, the ADHDP model is established, including determining the utility function, network design and training process. Finally, two case studies are given to compare the economic performance of the vehicle under different information acquisition scenarios, which lays a foundation for analyzing the relationship between the amount of information input and energy-saving potential of the vehicle. Simulation results demonstrate that the proposed method gains a better performance in both real-time performance and global optimality. 

  • 338.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Energy transition: Time matters2022In: Advances in Applied Energy, ISSN 2666-7924, Vol. 5, article id 100082Article in journal (Refereed)
    Abstract [en]

    Energy transition from fossil-based to zero carbon is the pathway for the world to meet future climate goals by 2050 according to the Paris Agreement. However, a real challenge faces us: how to rapidly manage the implications of variable renewable energy sources (VREs)? The increased share of sources such as solar and wind calls for the new development of system operating procedures and market implementation, including real time forecasting, faster scheduling, and ancillary services with more active engagement on the demand side. A radical transformation is important, in the way we supply, convert, transfer, and use energy, with more attention to handling dynamic balance: time matters.

  • 339.
    Yan, Jinyue
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH-Royal Institute of Technology, Sweden.
    Chou, S. K.
    National University of Singapore, Singapore, Singapore.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Nian, Victor
    National University of Singapore, Singapore, Singapore.
    Editorial: Leveraging Energy Technologies and Policy Options for Low Carbon Cities2017In: Energy Procedia, Elsevier Ltd , 2017, Vol. 143, p. 1-2Conference paper (Refereed)
  • 340.
    Yan, Jinyue
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Hong Kong Polytechnic University, Hong Kong.
    Salman, Chaudhary Awais
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Siemens Energy, Sweden.
    Waste Biorefineries: Advanced Design Concepts for Integrated Waste to Energy Processes2023Book (Other academic)
    Abstract [en]

    Waste Biorefineries: Advanced Design Concepts for Integrated Waste to Energy Processes presents a detailed guide to the design of energy-efficient and cost-effective waste-integrated biorefineries. Integrating thermochemical processing of waste with existing waste-to-energy technologies, the book includes the latest developments and technologies. It introduces current waste valorization techniques and examines reasons to modify existing waste-to-energy systems through the integration of new processes. In addition, the book explains the design of novel biorefineries and methods to assess these processes alongside detailed results, including the integration of waste-based CHP plants with waste gasification and the integration of pyrolysis technologies and biogas plants with waste thermochemical processing. Other sections discuss the issues and challenges of commercializing waste-to-energy technologies, including uncertainty in waste thermochemical process designs, the environmental impact of waste-integrated biorefineries, and the role of integrated waste-to-energy management in smart cities and urban energy systems. This book will be an invaluable reference for students, researchers and those in industry who are interested in the design and implementation of waste-to-energy systems, waste biomass-based combined heat and power plants, biogas plants and forest-based industries.

  • 341.
    Yang, C.
    et al.
    Key Laboratory of Low-Grade Energy Utilization Technologies and Systems, Ministry of Education of China, Chongqing University, China.
    Sun, L.
    Key Laboratory of Low-Grade Energy Utilization Technologies and Systems, Ministry of Education of China, Chongqing University, China.
    Chen, Hao
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thermodynamics Analysis of a Novel Compressed Air Energy Storage System Combined with Solid Oxide Fuel Cell–Micro Gas Turbine and Using Low-Grade Waste Heat as Heat Source2023In: Energies, E-ISSN 1996-1073, Vol. 16, no 19, article id 7010Article in journal (Refereed)
    Abstract [en]

    As the next generation of advanced adiabatic compressed air energy storage systems is being developed, designing a novel integrated system is essential for its successful adaptation in the various grid load demands. This study proposes a novel design framework for a hybrid energy system comprising a CAES system, gas turbine, and high-temperature solid oxide fuel cells, aiming for power generation and energy storage solutions. The overall model of the hybrid power generation system was constructed in Aspen PlusTM, and the mass balance, energy balance, and thermodynamic properties of the thermal system were simulated and analyzed. The results demonstrate that the hybrid system utilizes the functional complementarity of CAES and solid oxide fuel cells (SOFCs), resulting in the cascade utilization of energy, a flexible operation mode, and increased efficiency. The overall round-trip efficiency of the system is 63%, and the overall exergy efficiency is 67%, with a design net power output of 12.5 MW. Additionally, thermodynamic analysis shows that it is advisable to operate the system under lower ambient temperatures of 25 °C, higher compressor and turbine isentropic efficiencies of 0.9, a higher fuel utilization of 0.62, and optimal SOFC/MGT split air flow rates of 1.1 kg/s. The results of this article provide guidance for designing innovative hybrid systems and system optimization.

  • 342.
    Yang, K.
    et al.
    School of Economics and Management, China University of Petroleum, Beijing, China.
    Zhang, Q.
    School of Economics and Management, China University of Petroleum, Beijing, China.
    Wang, G.
    School of Economics and Management, North China Electric Power University, Beijing, China.
    Chen, X.
    School of Economics and Management, China University of Petroleum, Beijing, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    A New Simulation Framework for Vehicle-to-grid Adoption in Heterogeneous Trade Mechanism Scenarios2024In: Energy Proceedings, Scanditale AB , 2024, Vol. 43Conference paper (Refereed)
    Abstract [en]

    The current vehicle-to-grid (V2G) project pilots generally face the problem of low user participation willingness, mainly due to the lack of detailed consideration of trade mechanisms and incentive policies. To address the potential threat posed by the large-scale application of electric vehicles (EVs) to the power grid system, an analysis of the promotion strategies of V2G technology among EV owners is deemed necessary. In this study, a new simulation framework for V2G adoption and heterogeneous trade mechanism evaluation based on social network theory is constructed. The diffusion process of V2G adoption and charging/discharging behavior is simulated under three trading mechanism scenarios: Time-of-Use (ToU) pricing + fixed service fee (ToU-F), regulated pricing + fixed service fee (Reg-F), and dynamic pricing + fixed service fee (Dyn-F). The research results indicate that (1) In terms of V2G adoption scale, both the Reg-F and Dyn-F scenarios have reached the maximum number of adopters, increasing by 41.8% compared to the ToU-F scenario. The main reason is that the former two trading mechanisms achieve a larger price difference, creating more opportunities for charge and discharge arbitrage. (2) Regarding EV load regulation, the discharge amount of EVs under the Reg-F and Dyn-F scenarios is much higher than that under the ToU-F scenario. The Dyn-F scenario further avoids drastic fluctuations in load. (3) In terms of benefit distribution, only under the Reg-F scenario have both the aggregator and V2G adopters gained higher profits.

  • 343.
    Yang, S.
    et al.
    National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China.
    Yuan, J.
    China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai, China.
    Nian, V.
    International Society for Energy Transition Studies, Sydney, Australia.
    Li, L.
    China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Economics of marinised offshore charging stations for electrifying the maritime sector2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 322, article id 119389Article in journal (Refereed)
    Abstract [en]

    Electrification of international maritime transport, despite rapidly falling battery prices and improvements in battery technologies, remains constrained by midway charging, as the range of electric ocean-going vehicles is limited on a full charge. Before countries pour trillions of dollars of investment, this study is commissioned as the first attempt to investigate the economics of offshore marinised charging stations for enabling long-distance shipping by full-electric vessels. Three offshore power generation technologies, namely, wind, solar, and floating nuclear power plants, are compared to demonstrate the economics of offshore charging stations. Compared to conventional vessels using bunker fuels, full-electric vessels are cost competitive even under the assumed first-of-a-kind costs. Among the three offshore power sources compared in this study, a marinised charging station with floating nuclear power plant is shown to be the most cost-competitive. Despite the absence of a pilot project, the technoeconomic parameters as assumed in this study serve as important reference indicators for decision makers to consider when building an ecosystem for sustainable international shipping. © 2022 Elsevier Ltd

  • 344.
    Yao, Yiming
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Key Laboratory of Advanced Battery Systems and Safety (CPCIF), School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China.
    Chen, Y.
    Key Laboratory of Advanced Battery Systems and Safety (CPCIF), School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China.
    Luan, W.
    Key Laboratory of Advanced Battery Systems and Safety (CPCIF), School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    In-situ Observation of Crack Initiation and Propagation in the NCM811 Cathode particles2024In: Energy Proceedings, Scanditale AB , 2024, Vol. 43Conference paper (Refereed)
    Abstract [en]

    Layered nickel-rich oxide LiNixCoyMn1-x-yO2 (0.6 ≤x<1) is a highly promising positive electrode material. However, the cycling stability of nickel-rich positive electrode materials is limited by particle fracture and a series of side reactions. A comprehensive understanding of particle cracking mechanisms is paramount for material optimization, but crack initiation and propagation have received limited research attention. This paper uses a quasi in-situ SEM observation method and an in-situ optical microscopy observation method to observe crack evolution in real time. The results show rapid cracking behavior under hazardous operating conditions and cracking during cycling under mild conditions. Center cracks and surface cracks are observed during cycling. The observation methods and these insights into the crack behavior offer theoretical guidance for the structural engineering of NCM cathode particles.

  • 345.
    Ye, Y.
    et al.
    School of Materials Science and Engineering, Sun Yat-Sen University, China.
    Lu, J.
    School of Materials Science and Engineering, Sun Yat-Sen University, China.
    Ding, J.
    School of Materials Science and Engineering, Sun Yat-Sen University, China.
    Wang, W.
    School of Materials Science and Engineering, Sun Yat-Sen University, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Division of Energy Processes, Royal Institute of Technology, Stockholm, Sweden.
    Performance improvement of metal hydride hydrogen storage tanks by using phase change materials2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 320, article id 119290Article in journal (Refereed)
    Abstract [en]

    In metal hydride based hydrogen storage tanks, heat transfer fluid (HTF) has been extensively used to continuously transfer the reaction heat for promoting the reaction via heat exchangers. In this study, the phase change material (PCM) is integrated with the tank to enhance heat transfer and recycle the reaction heat. A novel storage tank with a simple concentric straight-tube heat exchanger surrounded by PCM is put forward to improve the hydrogen storage performance. A numerical model is built to track the transfer and reaction process. By comparison, the new tank shows better heat transfer and storage performance, and the hydrogen absorption time is shortened by 60.2% than that of the tank without PCM. For the new tank, the optimal amount of PCM is obtained, based on which the increased absorption pressure could effectively accelerate the heat discharge and reaction rate during the absorption process. However, the increased inlet velocity of HTF has a limited improvement effect on heat transfer and reaction performance. Furthermore, on the PCM side of the tank, the addition of fins and increasing the thermal conductivity of PCM had little effect on the performance of the tank.

  • 346.
    Yu, H.
    et al.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Tian, W.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Li, P.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Zhao, K.
    State Grid Customer Service Center, Tianjin, 300300, China.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wang, C.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Improved triangle splitting based bi-objective optimization for community integrated energy systems with correlated uncertainties2022In: Sustainable Energy Technologies and Assessments, ISSN 2213-1388, E-ISSN 2213-1396, Vol. 49, article id 101682Article in journal (Refereed)
    Abstract [en]

    Economic and environmental benefits are the most important in the operation of community integrated energy systems (CIES), modeled as a bi-objective optimization problem. In the case of the uncertainties from loads and renewable energy generators, the effectiveness of the operation strategies may be degraded in the practical applications of CIES. In this paper, an improved triangle splitting based bi-objective optimization method is proposed to search for the Pareto optimal solution of the CIES operation. The general preference of decision-makers in practical applications is utilized in the search process to reduce the detailed search interval and consequently improve the optimization efficiency. In addition, a bi-objective uncertain optimization framework is established for the economic-environmental operation of the CIES under uncertainties. The correlation between uncertainties is considered to generate the operation scenarios, in which the solution probability function is employed to determine the final operation strategy with robustness. A comprehensive case study is conducted based on a practical CIES in China, proving the feasibility and effectiveness of the proposed methods.

  • 347.
    Yu, Q.
    et al.
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
    Xie, Y.
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
    Li, W.
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
    Zhang, Haoran
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan.
    Liu, X.
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
    Shang, W. -L
    Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing University of Technology, Beijing, 100124, China.
    Chen, J.
    Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan.
    Yang, D.
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement2022In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 322, article id 119533Article in journal (Refereed)
    Abstract [en]

    As a newly-emerging option of shared transportation, Internet-enabled dockless bicycle sharing is well accepted by the public. The implementation of electric fences has great potential to tackle the problem of random parking in bicycle sharing services. However, the deployment of electric fences would have a negative impact on the convenience of bicycle sharing services, which might lead to an increase in energy consumption among customers who switch their methods of transportation. This paper proposes a dynamic electric fence planning method with an assessment of resource-saving and potential energy consumption increasement. An agent-based model is proposed to simulate the trips and evaluated the performance of static and dynamic electric fences. The results show that dynamic electric fences require significantly shorter walking distances than static electric fences. The implementation of electric fences in the city center can significantly avoid random parking and improve the parking tidiness of bicycles. The implementation of dynamic and static electric fences can averagely save 25.31% and 27.76% bicycle resources. By estimating travel mode shifting, dynamic electric fence can reduce energy consumption by 5.79% per day compared to the static electric fence situation. 

  • 348.
    Zaccaria, Valentina
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Fentaye, Amare Desalegn
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    BAYESIAN INFORMATION FUSION FOR GAS TURBINES DIAGNOSTICS AND PROGNOSTICS2023In: Proc. ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2023Conference paper (Refereed)
    Abstract [en]

    Prognosis, or the forecasting of remaining operational life of a component, is a fundamental step for predictive maintenance of turbomachines. While diagnostics gives important information on the current conditions of the engine, it is through prognostics that a suitable maintenance interval can be determined, which is critical to minimize costs. However, mature prognostic models are still lacking in industry, which still heavily relies on human experience or generic statistical quantifications. Predicting future conditions is very challenging due to many factors that introduce significant uncertainty, including unknown future machine operations, interaction between multiple faults, and inherent errors in diagnostic and prognostic models. Given the importance to quantify this uncertainty and its impact on operational decisions, this work presents an information fusion approach for gas turbine prognostics. Condition monitoring performed by a Bayesian network is fused with a particle filter for prognosis of gas turbine degradation, and the effect of diagnostic models uncertainty on the prognosis are estimated through probabilistic analysis. Gradual and rapid degradation are simulated on a gas turbine performance model and the impact of sensor noise and initial conditions for the particle filter estimation are assessed. This work demonstrates that the combination of Bayesian networks and particle filters can give good results for short-term prognosis.

  • 349.
    Zade, F. A.
    et al.
    Mechanical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
    Ghafurian, M. M.
    Mechanical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
    Mesgarpour, Mehrdad
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Fluid Mechanics, Thermal Engineering and Multiphase Flow Research Laboratory (FUTURE), Mechanical Engineering Department, Faculty of Engineering, King Mongkut's University of Technology Thonburi (KMUTT), Bangmod, Bangkok, 10140, Thailand.
    Niazmand, H.
    Mechanical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
    Predictive machine learning models for optimization of direct solar steam generation2023In: Journal of Water Process Engineering, E-ISSN 2214-7144, Vol. 56, article id 104304Article in journal (Refereed)
    Abstract [en]

    Direct solar steam generation (DSSG) has gained significant consideration in the recent decade because of its ability to generate freshwater, relying on renewable solar energy. Despite experimental data abundance, it is still difficult to optimize DSSG under certain conditions regarding fluid surface temperature changes (Ttop) and evaporation efficiency (η). This study investigates six predictive machine learning models, including multilayer perceptron (MLP), support vector regression (SVR), decision tree (DT), random forest (RF), adaptive boosting ensemble (ADA-BE), and combinations of them, to model Ttop and η in interfacial and volumetric DSSG systems. The models are trained on experimental data, and their performance is evaluated using various metrics. Based on the findings of the study, the DT (total R2 = 0. 9900) and DT-SVR combo (total R2 = 0.9829) are the best models to predict η in interfacial and volumetric systems, respectively. Results show that interfacial DT-MLP combo (total R2 = 0.9964) and volumetric DT-ADA-BE (total R2 = 0.9870) models predict Ttop more accurately. The study predicts that the ηmax of 85 ± 5 % and 90.91 ± 5 % will be obtained under one sun (1 kW/m2) using GNP-MWCNT with 0.015 weight percentage in volumetric and using Au-HT-wood with a thickness of 14.78 mm in interfacial approaches, respectively. 

  • 350.
    Zahraoui, Y.
    et al.
    Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), 7034 Trondheim, Norway.
    Korotko, T.
    Finest Centre for Smart Cities, Tallinn University of Technology, 19086 Tallinn, Estonia. Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia.
    Rosin, A.
    Finest Centre for Smart Cities, Tallinn University of Technology, 19086 Tallinn, Estonia. Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia.
    Zidane, Tekai Eddine Khalil
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Agabus, H.
    Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia.
    Mekhilef, S.
    School of Software and Electrical Engineering, Faculty of Science, Engineering and Technology, Swinburne University of Technology, Victoria, VIC 3122, Australia. Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
    A Competitive Framework for the Participation of Multi-Microgrids in the Community Energy Trading Market: A Case Study2024In: IEEE Access, E-ISSN 2169-3536, Vol. 12, p. 68232-68248Article in journal (Refereed)
    Abstract [en]

    An increase in the deployment of Distributed Energy Resources (DERs) and Renewable Energy (RE) resources is a promising paradigm in the decentralized energy era. It has motivated multi-Microgrids (MGs) to trade energy directly with others in the Local Energy Market (LEM), as well as with the main grid. The LEM has become a popular platform that covers several shortcomings of surplus/deficient energy, which can also manage the increasing connection of multi-microgrids, meet internal balance, and maximize the social welfare of the community Microgrid (MG). Moreover, in the LEM, the MGs would like to provide some payoff to encourage each other to exchange their energy locally. However, designing an appropriate market framework, privacy protection, and the community's unbalanced energy supply and demand is challenging. To cope with these challenges, in this study, an LEM for a multi-microgrid system is designed to maximize the social welfare of the community, and a decentralized clearing algorithm based on the Alternating Direction Method of Multipliers (ADMM) is proposed for local market clearing and privacy protection. The Community Manager (CM) is used as an intermediate coordinator between the interconnected MGs. This way, the computation process will be completely distributed, and the privacy of each MG will be protected. Moreover, considering the utility function for the consumers and energy providers, an equivalent cost model based on internal pricing is proposed to state the willingness of the utility and motivate the participants to join LEM. Finally, an illustrative example and a case study are used to demonstrate the efficiency and effectiveness of the proposed design of LEM and algorithm in terms of social welfare and power balance. In our study, we found that by using dynamic pricing in conjunction with our proposed model, the social welfare of the energy community can be increased by 14.25%. This demonstrates the significant economic benefits and effectiveness of our approach in the Local Energy Market (LEM).

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