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  • 1.
    Abdelshafy, Alaaeldin M.
    et al.
    Egypt Japan Univ Sci & Technol, Energy Resources Eng Dept, Alexandria, Egypt.;Assiut Univ, Fac Engn, Elect Engn Dept, Assiut, Egypt..
    Jurasz, Jakob
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. AGH Univ Sci & Technol, Fac Management, Dept Eng Management, Krakow, Poland..
    Hassan, Hamdy
    Egypt Japan Univ Sci & Technol, Energy Resources Eng Dept, Alexandria, Egypt.;Assiut Univ, Fac Engn, Mech Engn Dept, Assiut, Egypt..
    Mohamed, Abdelfatah M.
    Assiut Univ, Fac Engn, Elect Engn Dept, Assiut, Egypt.;Egypt Japan Univ Sci & Technol, Dept Mechatron & Robot Engn, Alexandria, Egypt..
    Optimized energy management strategy for grid connected double storage (pumped storage-battery) system powered by renewable energy resources2020In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 192, article id 116615Article in journal (Refereed)
    Abstract [en]

    This paper presents a grid-connected double storage system (DSS) consisting of pumped-storage hydropower (PSH) and battery. The system is supplied by photovoltaics and wind turbines. In the proposed hybrid system, batteries absorb excess renewable energy that cannot be stored in PSH and they cover loads that cannot be supplied from the water turbine. To improve the system performance, a novel energy management strategy for the DSS is proposed. The strategy is based on an optimized factor that governs the charging process of the DSS. The problem of the optimal system design is solved by a non-dominated sorting genetic algorithm (NSGA-II). The multi-objective function considers simultaneously the minimal investment cost and minimal CO2 emissions. A comparative study of photovoltaic/wind/pumped-storage hydropower and photovoltaic/wind/double storage system is performed to show the effectiveness of the proposed strategy in terms of system economic and environmental performance. The considered location of the PSH station is on Attaqa Mountain at Suez (Egypt). The results indicate the effectiveness of the proposed energy management strategy for the storage system from economic and environmental perspectives. Coupling the battery with the PSH reduces the electricity cost by 22.2% and results in minimal energy exchange with the national grid (5% of the annual demand). A sensitivity analysis shows the largest variation of the electricity cost with changing the capital cost of the solar and wind generators. Also, it is observed that when the load increases, the optimal size of the system components increases, but it isn't proportional with the demand increase as could be expected. (C) 2019 Elsevier Ltd. All rights reserved.

  • 2.
    Alirahmi, S. M.
    et al.
    Department of Chemistry and Bioscience, Aalborg University, Niels Bohrs Vej, Esbjerg, Denmark.
    Behzadi, A.
    Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Ahmadi, P.
    School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran.
    Sadrizadeh, Sasan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    An innovative four-objective dragonfly-inspired optimization algorithm for an efficient, green, and cost-effective waste heat recovery from SOFC2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 263, article id 125607Article in journal (Refereed)
    Abstract [en]

    This work proposes a novel yet practical dragonfly optimization algorithm that addresses four competing objectives simultaneously. The proposed algorithm is applied to a hybrid system driven by the solid oxide fuel cell (SOFC) integrated with waste heat recovery units. A function-fitting neural network is developed to combine the thermodynamic model of the system with the dragonfly algorithm to mitigate the calculation time. According to the optimization outcomes, the optimum parameters create significantly more power and have a greater exergy efficiency and reduced product costs and CO2 emissions compared to the design condition. The sensitivity analysis reveals that while the turbine inlet temperatures of power cycles are ineffective, the fuel utilization factor and the current density significantly impact performance indicators. The scatter distribution indicates that the fuel cell temperature and steam-to-carbon ratio should be kept at their lowest bound. The Sankey graph shows that the fuel cell and afterburner are the main sources of irreversibility. According to the chord diagram, the SOFC unit with a cost rate of 13.2 $/h accounts for more than 29% of the overall cost. Finally, under ideal conditions, the flue gas condensation process produces an additional 94.22 kW of power and 760,056 L/day of drinkable water. 

  • 3.
    Blarke, Morten B
    et al.
    Aalborg University.
    Dotzauer, Erik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Intermittency-friendly and high-efficiency cogeneration: Operational optimisation of cogeneration with compression heat pump, flue gas heat recovery, and intermediate cold storage2011In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 36, no 12, p. 6867-6878Article in journal (Refereed)
    Abstract [en]

    This paper develops, implements, and applies a mathematical model for economic unit dispatch for a novel cogeneration concept (CHP-HP-FG-CS (CHP with compression heat pump and cold storage using flue gas heat)) that increases the plant's operational flexibility. The CHP-HP-FG-CS concept is a high-efficiency and widely applicable option in distributed cogeneration better supporting the co-existence between cogenerators and intermittent renewables in the energy system. The concept involves integrating an efficient high-temperature compression heat pump that uses only waste heat recovered from flue gases as low-temperature heat source, and an intermediate cold thermal storage allowing for non-concurrent operation of the cogeneration unit and the heat pump unit. The model is applied for a paradigmatic case study that shows how the integration of a heat pump affects the operational strategy of a cogeneration plant. It is found that CHP-HP-FG-CS offers significant reductions in fuel consumption (-8.9%) and operational production costs (-11.4%). The plant's fuel-to-energy efficiency increases from 88.9 to 95.5%, which is state-of-the-art. The plant's intermittency-friendliness coefficient Rc improves only marginally due to the constrained nature of the low-temperature heat source and the associated small capacity of the heat pump unit. Significant improvements in Rc are found when increasing the heat pump capacity assuming the availability of an unconstrained heat source

  • 4.
    Canales, Fausto A.
    et al.
    Univ Costa, Dept Civil & Environm, Calle 58 55-66, Barranquilla 080002, Atlantico, Colombia..
    Jurasz, Jakob
    AGH Univ Sci & Technol, Fac Management, Dept Engn Management, 30 Mickiewicza Ave, PL-30059 Krakow, Poland..
    Beluco, Alexandre
    Univ Fed Rio Grande do Sul, Inst Pesquisas Hidraul, Av Bento Goncalves 9500,Caixa Postal 15029, BR-91570901 Porto Alegre, RS, Brazil..
    Kies, Alexander
    Goethe Univ Frankfurt, Frankfurt Inst Adv Studies, Ruth Moufang Str 1, D-60438 Frankfurt, Germany..
    Assessing temporal complementarity between three variable energy sources through correlation and compromise programming2020In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 192, article id 116637Article in journal (Refereed)
    Abstract [en]

    Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. Nevertheless, the weather-dependent nature and variability of renewable energy sources often hinders their integration to national grids. The combination of different sources to profit from their beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity, as well as allowing for a linear assessment of complementarity. The method is employed to study the complementarity of wind, solar and hydropower generation on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the estimated value of the total temporal complementarity index. (C) 2019 Elsevier Ltd. All rights reserved.

  • 5.
    Dahlquist, Erik
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Vassileva, Iana
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Thorin, Eva
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Wallin, Fredrik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    How to save energy to reach a balance between production and consumptionof heat, electricity and fuels for vehicles2012In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 46, no 1, p. 16-20Article in journal (Refereed)
    Abstract [en]

    There is a potential to utilize a significant amount of renewable energy in Sweden and European union(EU). Biomass can fulfil some 8500e12,500 TW h/y in EU, while the total utilization was 16,084 TW h/y2009. Even though there is a significant amount of wind power, hydro power and potentially also solarpower, it still is most economical to reduce the consumption of heat, electricity and fuels for vehicles. Asaved kWh is normally cheaper than to produce one extra. In this paper different opportunities for savingenergy will be discussed. This includes manufacturing industries, process industries, power plants andenergy systems including distribution of power and smart grids, food production and transportation.There is also a major potential to save energy in buildings, both in the north where it is cold, and in thesouth where it can be very hot summer time. Here the potential is to avoid cooling instead. Technicalsolutions as well as economic incentives are covered. Environmental aspects are addressed, so that thesolutions will be long term sustainable.

  • 6.
    Dai, B.
    et al.
    Tianjin University of Commerce, Tianjin, China.
    Liu, S.
    Tianjin University of Commerce, Tianjin, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin University of Commerce, Tianjin, China.
    Sun, Z.
    Tianjin University of Commerce, Tianjin, China.
    Song, M.
    The University of Tokyo, Chiba, Japan.
    Yang, Q.
    Tianjin University of Commerce, Tianjin, China.
    Ma, Yitai
    The University of Tokyo, Chiba, Japan.
    Energetic performance of transcritical CO2 refrigeration cycles with mechanical subcooling using zeotropic mixture as refrigerant2018In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 150, p. 205-221Article in journal (Refereed)
    Abstract [en]

    Transcritical CO2 refrigeration cycle integrated with mechanical subcooling (MS) cycle operating with zeotropic mixture is proposed in this study, based on the concept of Lorenz cycle. An energetic model is developed and analyses are conducted in detail. A maximum overall coefficient of performance (COP) is achieved at the optimum discharge pressure and optimum subcooling degree. The maximum overall COP, optimum subcooling degree and discharge pressure are closely related to the temperature glide of the mixtures. The energy efficiency of the transcritical CO2 refrigeration cycle can be efficiently improved, and the high pressure can be reduced when mixtures with proper temperature glide are used as MS cycle refrigerant. Compared with pure R32, the overall COP is enhanced by 4.91%, and the discharge pressure decreases by 0.11 MPa at evaporation temperature of −5 °C and ambient temperature of 35 °C when R32/R1234ze(Z) (55/45) is employed as MS refrigerant. The mixtures with proper temperature glide are recommended. The thermal performance of the overall cycle can be enhanced more significantly for hot and warm climate regions, or relative low evaporation temperature applications, though a high subcooling degree is required to meet the optimum operation condition.

  • 7.
    Han, Song
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Dotzauer, Erik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Eva, Thorin
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Bozena, Guziana
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Tuomas, Huopana
    University of Eastern Finland.
    Jinyue, Yan
    Mälardalen University, School of Sustainable Development of Society and Technology.
    A dynamic model to optimize a regional energy system with waste and crops as energy resources for greenhouse gases mitigation2012In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 46, no 1, p. 522-532Article in journal (Other academic)
    Abstract [en]

    A dynamic model of a regional energy system has been developed to support sustainable waste treatmentwith greenhouse gases (GHG) mitigation, addressing the possibility for development towardsa regional fossil fuel-free society between 2011 and 2030. The model is based on conventional mixedinteger linear programming (MILP) techniques to minimize the total cost of regional energy systems. TheCO2 emission component in the developed model includes both fossil and biogenic origins whenconsidering waste, fossil fuels and other renewable sources for energy production. A case study for thecounty of Västmanland in central Sweden is performed to demonstrate the applicability of the developedMILP model in five distinct scenarios. The results show significant potential for mitigating CO2 emissionby gradually replacing fossil fuels with different renewable energy sources. The MILP model can be usefulfor providing strategies for treating wastes sustainably and mitigating GHG emissions in a regionalenergy system, which can function as decision bases for formulating GHG reduction policies andassessing the associated economic implications.

  • 8.
    Han, Song
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Dotzauer, Erik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Thorin, Eva
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Yan, Jinyue
    School of Chemical Science, Royal Institute of Technology, Stockholm, Sweden.
    Techno-economic analysis of an integrated biorefinerysystem for poly-generation of power, heat, pelletand bioethanol2014In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, no 38, p. 551-563Article in journal (Refereed)
    Abstract [en]

    Abstract: Bioethanol is considered an alternative to fossil fuels in the transportation sector. The use of pellets for heating is another efficient way to mitigate greenhouse gas emissions. This paper evaluates the techno-economic performance of a biorefinery system in which an existing combined heat and power plant integrates with the productions of bioethanol and pellets using straw as feedstock. A two-stage acid hydrolysis process for bioethanol production is used, and two different drying technologies are chosen for drying hydrolysis solid residues. A sensitivity analysis on critical parameters, such as the bioethanol selling price and feedstock price, is performed. The bioethanol production cost is also calculated for two cases at the conditions of ten-year and five-year payback time. The results show that the first case is a more feasible economic configuration at present, having an over 30% production cost reduction compared with the conventional cogeneration plants of bioethanol and solid fuel.

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  • 9.
    Huang, Qingxi
    et al.
    Shandong Univ, Inst Adv Technol, Jinan 250061, Peoples R China..
    Yao, Jinduo
    Tianjin Univ Commerce, Sch Mech Engn, Tianjin Key Lab Refrigerat Technol, Tianjin, Peoples R China..
    Hu, Yukun
    UCL, Dept Civil Environm & Geomat Engn, London WC1E 6BT, England..
    Liu, Shengchun
    Tianjin Univ Commerce, Sch Mech Engn, Tianjin Key Lab Refrigerat Technol, Tianjin, Peoples R China..
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin Univ Commerce, Sch Mech Engn, Tianjin Key Lab Refrigerat Technol, Tianjin, Peoples R China..
    Sun, Qie
    Shandong Univ, Inst Adv Technol, Jinan 250061, Peoples R China.;Shandong Univ, Inst Thermal Sci & Technol, Jinan 250061, Peoples R China..
    Integrating compressed CO(2 )energy storage in an oxy-coal combustion power plant with CO2 capture2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 254, article id 124493Article in journal (Refereed)
    Abstract [en]

    To compensate for the high cost of CO2 capture, this study proposes a novel solution that integrates a compressed CO2 energy storage (CCES) system into an oxy-coal combustion power plant with CO2 capture (Oxy_CCES). The integration of energy storage has the potential to create arbitrage from variations in electricity prices. The proposed Oxy_CCES system can achieve a higher net efficiency of 34.1%, and a higher exergy efficiency of 57.5%, than that of a liquified oxygen storage-integrated oxy-coal combustion power plant (Oxy_O-2). Two scenarios, i.e., retrofitting an existing oxy-coal combustion power plant (S-I) and building a new plant (S-II), were established to compare the Oxy_CCES and Oxy_O-2. In S-I, the payback time of the Oxy_CCES is one year and in the S-II the levelized cost of electricity (LCOE) of the Oxy_CCES increases by 1.8%, which is lower than that of the Oxy_O-2. The sensitivity analysis shows that, when the difference between the peak and the valley electricity prices and the capacities of the energy storage systems increase by 50%, the net present value (NPV) and LCOE of the Oxy_CCES system increase by 113.4% and 1.7% respectively, which are lower than the NPV and LCOE increase of the Oxy_O-2.

  • 10.
    Javed, Muhammad Shahzad
    et al.
    Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China..
    Ma, Tao
    Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China..
    Jurasz, Jakob
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. AGH Univ Sci & Technol, Fac Management, Krakow, Poland..
    Ahmed, Salman
    Shanghai Jiao Tong Univ, Sch Mech Engn, Shanghai, Peoples R China..
    Mikulik, Jerzy
    AGH Univ Sci & Technol, Fac Management, Krakow, Poland..
    Performance comparison of heuristic algorithms for optimization of hybrid off-grid renewable energy systems2020In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 210, article id 118599Article in journal (Refereed)
    Abstract [en]

    Hybrid renewable energy systems have been widely acknowledged as a clean, affordable and reliable mechanism to generate electricity and to accomplish global sustainable development goals. In this study, first, an operating strategy and an optimization problem are developed for a hybrid, off-grid, solar-wind system based on pumped hydro battery storage, and then a non-linear optimization problem is described for the considered system. To solve the optimization problem, four different optimization techniques are employed i.e. ant colony (ACO), firefly algorithm (FA), particle swarm optimization (PSO) and genetic algorithm (GA) and their performance is compared using statistical parameters like relative error, mean absolute error and root mean square error. Each optimization technique's working principle is discussed in detail and formulated considering the proposed optimization problem. The exploration and exploitation behavior of each algorithm is comprehensively analyzed explaining that ACO and FA have higher exploitation behavior, while GA and PSO have more exploration behavior, revealing that these behavior depend on the range of operator controlling parameters, type of optimization problem and formulation structure of the optimizers. The reference controlling parameters of each optimizer (which are operator dependent) are defined for the proposed optimization problem. The results reveal that FA performs better - i.e. with the least relative error (0.126) - while PSO outperforms best in terms of least objective function value (0.2435 $/kWh). The mean efficiency of each algorithm in terms of repeated executions (30 times) is ACO = 95.94%, FA = 96.20%, GA = 93.93%, PSO = 96.20%. The proposed study could help decision-makers to choose an optimization method to solve non-linear problems in the context of storage-based, off-grid systems under different scenarios. (C) 2020 Elsevier Ltd. All rights reserved.

  • 11.
    Ji, H.
    et al.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Chen, S.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Yu, H.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Li, P.
    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.
    Song, J.
    Global Energy Interconnection Research Institute of State Grid, Beijing, 100000, China.
    Wang, C.
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, 300072, China.
    Robust operation for minimizing power consumption of data centers with flexible substation integration2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 248, article id 123599Article in journal (Refereed)
    Abstract [en]

    The rapid development of digital economy has led to a dramatic increasement of internet data centers (IDCs), which consume a large amount of electricity. The diverse data-processing demands, high power consumption and workload uncertainty put forward a high requirement for the economical and secure operation of IDCs. As information technology (IT) devices are driven by direct current (DC), flexible substation (FS) has been gradually utilized to provide DC power for IDCs. This paper proposes robust operation strategies for minimizing IDC power consumption with FS integration. First, the linearized IDC power consumption model based on the technology of dynamic voltage and frequency scaling (DVFS) is proposed to describe the operating state of IT devices. Then, considering the FS-based coordinated operation of IDC, photovoltaic (PV) station and energy storage system (ESS), the deterministic power consumption minimization model of IDCs is established. Considering the workload uncertainty, the operation strategies based on distributionally robust optimization (DRO) for IDCs are further proposed. Finally, the effectiveness of proposed method is validated on a modified practical network with IDCs integrated. Results show that through the dispatch of workload and power flow regulation of FS, the power consumption and dropping workload of IDCs are effectively reduced. 

  • 12.
    Jurasz, Jakob
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. AGH Univ Sci & Technol, Krakow, Poland.;MDH Univ, Vasteras, Sweden..
    Kies, Alexander
    Goethe Univ Frankfurt, FIAS, Frankfurt, Germany..
    Zajac, Pawel
    AGH Univ Sci & Technol, Krakow, Poland..
    Synergetic operation of photovoltaic and hydro power stations on a day-ahead energy market2020In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 212, article id 118686Article in journal (Refereed)
    Abstract [en]

    Hydropower has huge potential for a technically feasible and economically justified integration of variable, renewable energy sources with the power system. On the other hand, the operational intricacies of hydropower stations with a reservoir are limited by various constraints. Many previous works addressed the idea of solar-hydro resources complementarity, optimal sizing of such systems or their optimal dispatch. However, no one has ever established such a system in a highly competitive energy market with strongly fluctuating energy prices. Therefore, in this paper, we analyse the potential operation of a photovoltaic-hydro (PV-hydro) hybrid power station on a day-ahead electricity market. Due to its relatively small size such a station can be considered on the market as a price taker. The mathematical model which is used takes into consideration the irradiation and inflow uncertainty. A bidding strategy is created; based on the forecasted availability of solar and hydro energy during the day. The electricity prices on the market are taken from historical data and the optimized bidding strategy which is the repeatable for each day of the year. The operation of solar and hydropower stations on the day-ahead market as independent power stations is used as a benchmark for the hybrid system. The results of our analysis are promising and indicate a 5% increase of revenue for a joint operation (comparing to independent operations) providing the energy price increases by 3% per year. The hybrid system not only provides a greater profit to the owner, but also improves the small water retention during the hot period in summer. Over the whole year, the average monthly reservoir state of filling is greater than 73%. In the joint operation mode, the capacity factors of both sources are kept on a relatively high level of no less than 95% of their initial values based on resources availability. 

  • 13. Leduc, Sylvain
    et al.
    Starfelt, Fredrik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Dotzauer, Erik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Kinderman, Georg
    McCallum, Ian
    Obersteiner, Mickael
    Lundgren, Joachim
    Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden2010In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 35, no 6, p. 2709-2716Article in journal (Refereed)
    Abstract [en]

    The integration of ethanol production with combined heat and power plants is considered in this paper. An energy balance process model has been used to generate data for the production of ethanol, electricity, heat and biogas. The geographical position of such plants becomes of importance when using local biomass and delivering transportation fuel and heat. An optimization model has thus been used to determine the optimal locations for such plants in Sweden. The entire energy supply and demand chain from biomass outtake to gas stations filling is included in the optimization. Input parameters have been studied for their influence on both the final ethanol cost and the optimal locations of the plants. The results show that the biomass cost, biomass availability and district heating price are crucial for the positioning of the plant and the ethanol to be competitive against imported ethanol. The optimal location to set up polygeneration plants is demonstrated to be in areas where the biomass cost is competitive and in the vicinity of small to medium size cities. Carbon tax does not influence the ethanol cost, but solicits the production of ethanol in Sweden, and changes thus the geography of the plant locations.

  • 14.
    Li, Hailong
    et al.
    SINTEF Energy Research.
    Ditaranto, M
    SINTEF Energy Research.
    Berstad, D
    SINTEF Energy Research.
    Technologies for increasing CO2 concentration in exhaust gas from natural gas-fired power production with post-combustion, amine-based CO2 capture2011In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 36, no 2, p. 1124-1133Article in journal (Refereed)
    Abstract [en]

    Enhanced CO2 concentration in exhaust gas is regarded as a potentially effective method to reduce thehigh electrical efficiency penalty caused by CO2 chemical absorption in post-combustion capturesystems. The present work evaluates the effect of increasing CO2 concentration in the exhaust gas of gasturbine based power plant by four different methods: exhaust gas recirculation (EGR), humidification(EvGT), supplementary firing (SFC) and external firing (EFC). Efforts have been focused on the impacts oncycle efficiency, combustion, gas turbine components, and cost. The results show that the combined cyclewith EGR has the capability to change the molar fraction of CO2 with the largest range, from 3.8 mol% toat least 10 mol%, and with the highest electrical efficiency. The EvGT cycle has relatively low additionalcost impact as it does not require any bottoming cycle. The externally fired method was found to have theminimum impacts on both combustion and turbomachinery.

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  • 15.
    Li, Hailong
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wang, Bin
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH Royal Institute of Technology, Stockholm, Sweden.
    Salman, Chaudhary Awais
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Thorin, Eva
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Schwede, Sebastian
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Performance of flue gas quench and its influence on biomass fueled CHP2019In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 180, p. 934-945Article in journal (Refereed)
    Abstract [en]

    For biomass/waste fueled power plants, stricter regulations require a further reduction of the negative impacts on the environment caused by the release of pollutants and withdrawal of fresh water externally. Flue gas quench (FGQ) is playing an important role in biomass or waste fueled combined heat and power (CHP) plants, as it can link the flue gas (FG) cleaning, energy recovery and wastewater treatment. Enhancing water evaporation can benefit the concentrating of pollutant in the quench water; however, when FG condenser (FGC) is not in use, it results in a large consumption of fresh water. In order to deeply understand the operation of FGQ, a mathematic model was developed and validated against the measurements. Based on simulation results key parameters affecting FGQ have been identified, such as the flow rate and temperature of recycling water and the moisture content of FG. A guideline about how to reduce the discharge of wastewater to the external and the withdrawal of external water can be proposed. The mathematic model was also implemented into an ASPEN Plus model about a CHP plant to assess the impacts of FGQ on CHP. Results show that when the FGC was running, increasing the flow rate and decreasing the temperature of recycling water can result in a lower total energy efficiency. 

  • 16.
    Li, Houpei
    et al.
    College of Civil Engineering, Hunan University, Changsha, 410082, China; Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, Changsha, China.
    Li, Jun
    Department of Materials Science and Engineering, University of Michigan, Ann Arbor, 48109, MI, United States.
    Li, Sihui
    College of Civil Engineering, Hunan University, Changsha, 410082, China; Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, Changsha, China.
    Peng, Jinqing
    College of Civil Engineering, Hunan University, Changsha, 410082, China; Key Laboratory of Building Safety and Energy Efficiency of the Ministry of Education, Changsha, China.
    Ji, Jie
    Department of Thermal Science and Energy Engineering, University of Science and Technology of China, Hefei, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Matching characteristics and AC performance of the photovoltaic-driven air conditioning system2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 264, article id 126509Article in journal (Refereed)
    Abstract [en]

    Photovoltaic-driven Air Conditioning systems (PVAC) use local electricity generated by distributed Photovoltaic (PV) to drive Air Conditioners (AC). Both the AC cooling load and the PV electricity generation are affected by solar radiation. The PV generation cannot dynamically supply the AC power consumption during the operation. In this study, the matching characteristics of a PVAC were investigated using a case in a 207.34 m2 office room. A coupled simulation model was built, which integrated with a building model, a PV calculation model, an AC model, and a control strategy. More specifically, the AC was modeled with two heat exchangers, a compressor, and a throttling device. Both the building and the PV were simulated in EnergyPlus. The AC compressor speed was controlled so the AC power consumption could match the PV generation when the indoor temperature was within the temperature control zone. The daily matching characteristics of PVAC were strongly affected by the PV capacity. The results showed that the PV factor (PVF) should be set to 1 in order to match the AC and PV power and maximize the AC efficiency. A battery factor of at least 0.7 could ensure the grid flexibility. Finally, the optimized design of PV, battery, and AC capacities was suggested.

  • 17.
    Li, Y.
    et al.
    Tsinghua University, Beijing, China .
    Jin, Y.
    School of Environment, Tsinghua University, Beijing, China.
    Li, J.
    School of Environment, Tsinghua University, Beijing, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yu, Z.
    University of Stavanger, Stavanger, Norway .
    Nie, Y.
    School of Environment, Tsinghua University, Beijing, China .
    Effects of thermal pretreatment on degradation kinetics of organics during kitchen waste anaerobic digestion2017In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 118, p. 377-386Article in journal (Refereed)
    Abstract [en]

    The influence of thermal pretreatment on degradation properties of organics in kitchen waste (KW) was investigated. The kinetics results showed that thermal pretreatment could enhance the degradation efficiency of crude protein (CP), fat, oil and grease (FOG), volatile solid (VS) and volatile fatty acids (VFA). Thermal pretreatment showed no significant difference in the final concentration of protein but could decrease the FOG degradation potential (7–36%), while increased the lag phase for degradation of protein and FOG respectively by 35–65% and 11–82% compared with untreated KW. Cumulative biogas yield increased linearly and exponentially with the removal efficiency of VS and other organics (CP and FOG) respectively. Additionally, the reduction of CP increased exponentially with FOG removal efficiency. The calculating methods of biogas yield, organics reduction and corresponding appropriate digestion retention based on FOG and CP reduction amount and pretreatment parameters were suggested.

  • 18.
    Li, Yangyang
    et al.
    Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China.;Tsinghua Univ, Minist Educ China, Key Lab Solid Waste Management & Environm Safety, Beijing 100084, Peoples R China..
    Jin, Yiying
    Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China.;Tsinghua Univ, Minist Educ China, Key Lab Solid Waste Management & Environm Safety, Beijing 100084, Peoples R China..
    Li, Jinhui
    Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China.;Tsinghua Univ, Minist Educ China, Key Lab Solid Waste Management & Environm Safety, Beijing 100084, Peoples R China..
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yu, Zhixin
    Univ Stavanger, Dept Petr Engn, N-4036 Stavanger, Norway..
    Nie, Yongfeng
    Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China.;Tsinghua Univ, Minist Educ China, Key Lab Solid Waste Management & Environm Safety, Beijing 100084, Peoples R China..
    Effects of thermal pretreatment on degradation kinetics of organics during kitchen waste anaerobic digestion (vol 118, pg 377, 2017)2018In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 153, p. 1089-1089Article in journal (Other academic)
  • 19.
    Lin, H.
    et al.
    Shandong University, Jinan, China; Harvard University, Cambridge, MA, United States.
    Bian, C.
    Nankai University, Tianjin, China.
    Wang, Y.
    Shandong University, Jinan, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Shandong University, Jinan, China; Hubei University of Arts and Science, Xiangyang City, Hubei Province, China.
    Sun, Q.
    Shandong University, Jinan, China.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Optimal planning of intra-city public charging stations2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 238, article id 121948Article in journal (Refereed)
    Abstract [en]

    Intra-city Public Charging Stations (PCSs) play a crucial role in promoting the mass deployment of Electric Vehicles (EVs). To motivate the investment on PCSs, this work proposes a novel framework to find the optimal location and size of PCSs, which can maximize the benefit of the investment. The impacts of charging behaviors and urban land uses on the income of PCSs are taken into account. An agent-based trip chain model is used to represent the travel and charging patterns of EV owners. A cell-based geographic partition method based on Geographic Information System is employed to reflect the influence of land use on the dynamic and stochastic nature of EV charging behaviors. Based on the distributed charging demand, the optimal location and size of PCSs are determined by mixed-integer linear programming. Västerås, a Swedish city, is used as a case study to demonstrate the model's effectiveness. It is found that the charging demand served by a PCS is critical to its profitability, which is greatly affected by the charging behavior of drivers, the location and the service range of PCS. Moreover, charging price is another significant factor impacting profitability, and consequently the competitiveness of slow and fast PCSs. 

  • 20.
    Lin, H.
    et al.
    Institute of Thermal Science and Technology, Shandong University, Jinan, China.
    Fu, K.
    Institute of Thermal Science and Technology, Shandong University, Jinan, China.
    Wang, Y.
    Institute of Thermal Science and Technology, Shandong University, Jinan, China.
    Sun, Q.
    Institute of Thermal Science and Technology, Shandong University, Jinan, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Hu, Y.
    UCL, Dept Civil Environm & Geomat Engn, London, England.
    Sun, B.
    Department of Civil, Environmental & Geomatic Engineering, University College London, London, United Kingdom.
    Wennersten, R.
    Institute of Thermal Science and Technology, Shandong University, Jinan, China.
    Characteristics of electric vehicle charging demand at multiple types of location - Application of an agent-based trip chain model2019In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 188, article id 116122Article in journal (Refereed)
    Abstract [en]

    This paper developed an agent-based trip chain model (ABTCM) to study the distribution of electric vehicles (EVs) charging demand and its dynamic characteristics, including flexibility and uncertainty, at different types of location. Key parameters affecting charging demand include charging strategies, i.e. uncontrolled charging (UC) and off-peak charging (OPC), and EV supply equipment, including three levels of charging equipment. The results indicate that the distributions of charging demand are similar as the travel patterns, featured by traffic flow at each location. A discrete peak effect was found in revealing the relation between traffic flow and charging demand, and it results in the smallest equivalent daily charging demand and peak load at public locations. EV charging and vehicle-to-grid (V2G) flexibility were examined by instantaneous adjustable power and accumulative adjustable amount of electricity. The EVs at home locations have the largest charging and V2G flexibility under the UC strategy, except for a period of regular working time. The V2G flexibility at work and public locations is generally larger than charging flexibility. Due to the fast charging application, the uncertainties of charging demand at public locations are the highest in all locations. In addition, the OPC strategy mitigates the uncertainty of charging demand. 

  • 21.
    Liu, L.
    et al.
    Institute of Thermal Science and Technology, Shandong University, Jinan, 250061, China.
    Bai, F.
    School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, 4072, QLD, Australia.
    Su, C.
    Institute of Thermal Science and Technology, Shandong University, Jinan, 250061, China.
    Ma, C.
    Institute of Thermal Science and Technology, Shandong University, Jinan, 250061, China.
    Yan, R.
    School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, 4072, QLD, Australia.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Institute for Advanced Science and Technology, Shandong University, Jinan, 250061, China.
    Sun, Q.
    Institute of Thermal Science and Technology, Shandong University, Jinan, 250061, China.
    Wennersten, R.
    Institute of Thermal Science and Technology, Shandong University, Jinan, 250061, China.
    Forecasting the occurrence of extreme electricity prices using a multivariate logistic regression model2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 247, article id 123417Article in journal (Refereed)
    Abstract [en]

    Extreme electricity prices occur with a higher frequency and a larger magnitude in recent years. Accurate forecasting of the occurrence of extreme prices is of great concern to market operators and participants. This paper aims to forecast the occurrence probability of day-ahead extremely low and high electricity prices and investigate the relative importance of different influencing variables. The data obtained from the Australian National Electricity Market (NEM) were employed, including historical prices (one day before and one week before), reserve capacity, load demand, variable renewable energy (VRE) proportion and interconnector flow. A Multivariate Logistic Regression (MLgR) model was proposed, which showed good forecasting capability in terms of model fitness and classification accuracy with different thresholds of extreme prices. In addition, the performance of the MLgR model was verified by comparing with two other models, i.e., Multi-Layer Perceptron (MLP) and Radical Basis Function (RBF) neural network. Relative importance analysis was performed to quantify of the contribution of the variables. The proposed method enriches the theories of electricity price forecast and advances the understanding of the dynamics of extreme prices. By applying the model in practice, it will contribute to promoting the management of operation and establishment of a robust energy market. 

  • 22.
    Liu, S.
    et al.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Lu, F.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Dai, B.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Nian, V.
    Energy Studies Institute, National University of Singapore, Singapore.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Qi, H.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Li, J.
    Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, China.
    Performance analysis of two-stage compression transcritical CO2 refrigeration system with R290 mechanical subcooling unit2019In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 189, article id 116143Article in journal (Refereed)
    Abstract [en]

    The use of carbon dioxide (CO2) as refrigerant is driven by the need to phase down the traditional synthetic refrigerant so as to mitigate the warming climate. In this study, the thermal performance of a two-stage compression transcritical CO2 refrigeration system with R290 mechanical subcooling unit is conducted. The goal is to obtain the maximum coefficient of performance (COP) of five different mechanical subcooling systems under the optimal subcooling temperature and compressor discharge pressure. The two-throttling and two-stage compression high-pressure mechanical subcooling system is found to have a higher COP. When the evaporation temperature is −30 °C, the COP of the two-throttling and two-stage compression high-pressure mechanical subcooling system is improved by 76.74%. The COP of the two-throttling and two-stage compression high-pressure mechanical subcooling system is 1.52 at an ambient temperature of 40 °C, which is 21.87% higher than that of the two-throttling and two-stage compression low-pressure mechanical subcooling system. The power consumption ratio of one-throttling and two-stage compression low-pressure mechanical subcooling system is significantly higher than that of other systems. From a comprehensive analysis of the proposed four systems, the two-throttling and two-stage compression high-pressure mechanical subcooling system has the best performance over all other systems. 

  • 23.
    Liu, Z.
    et al.
    Qingdao Univ Sci & Technol., China.
    Cao, X.
    Qingdao Univ Sci & Technol., China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yang, X.
    ‎ Xi An Jiao Tong Univ, China.
    Self-condensing transcritical CO2 cogeneration system with extraction turbine and ejector refrigeration cycle: A techno-economic assessment study2020In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 208, article id 118391Article in journal (Refereed)
    Abstract [en]

    This paper attempts to provide guidance for practical applications in utilizing low-grade heat sources by designing a novel combined cooling and power system. This system is integrated with a self-condensing transcritical CO2 Rankine cycle, an extraction turbine and a transcritical CO2 ejector refrigeration cycle. A mathematical model is established to analyze the thermodynamic performance and the model is validated through comparing results with data in open literature. System sensitivity analysis under various conditions is carried out to assess the relationships between key functioning variables and the system performance with regard to both thermal and economic perspectives. Results demonstrate that a favorable adaptability for balancing the cooling and power outputs is achieved by this combined system, and the user demand and plenty of net power can be remained. Besides, decreasing the turbine back pressure can maximally increase the refrigeration capacity of the system. The refrigeration capacity is greatly improved by 866.14% with a decrease in turbine back pressure from 10.4 MPa to 9 MPa at the cost of reducing net power by 50.11%. It is favorable and reasonable to increase liquefaction pressure and decrease cooling temperature to achieve goals of improving system energy and exergy efficiency and simultaneously reducing the product unit cost. 

  • 24.
    Liu, Zhan
    et al.
    Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R China.
    Liu, Xu
    Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R China.
    Zhang, Weifeng
    Qingdao Univ Sci & Technol, Coll Electromech Engn, Qingdao 266061, Peoples R China.
    Yang, Shanju
    Northwest A&F Univ, Coll Mech & Elect Engn, Yangling 712100, Shaanxi, Peoples R China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yang, Xiaohu
    Xi An Jiao Tong Univ, Sch Human Settlements & Civil Engn, Xian 710049, Peoples R China.
    Thermodynamic analysis on the feasibility of a liquid energy storage system using CO2-based mixture as the working fluid2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 238, article id 121759Article in journal (Refereed)
    Abstract [en]

    Pioneering investigation is conducted on the feasibility of designing novel liquid energy storage system by using working fluid blending CO2 with organic fluids to address the condensation problem of subcritical CO2. Organic substances are cautiously screened according to the criteria of environment effect, temperature glide, critical temperature and flammability of working fluid as well as the system performance. Mathematical model of the system is built for thermodynamic examination. An in-house code is developed to complete the system simulations combing with REFPROP subroutine. Results demonstrate that compared to the system with pure CO2, the system with mixture produces an improvement of net power output and energy density and a reduction of charge pressure at an expense of slightly decreasing round trip efficiency. The payment of 6.45 % for round trip efficiency can reduce 55.59 % of charge pressure by taking CO2/R32 as an instance. The system round trip efficiency, energy density and charge pressure decrease with the increase in organic fluid composition. An optimal compression ratio can be identified to reach a maximal round trip efficiency for all mixtures. The cooler outlet temperature is suggested being at the critical temperature of working fluid to reach better system performance. 

  • 25.
    Maher, Azaza
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Multi objective particle swarm optimization of hybrid micro-grid system: A case study in Sweden2017In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 123, p. 108-118Article in journal (Refereed)
    Abstract [en]

    Distributed energy resources DERs are small scale energy system which could provide local supply when placed at customers' premises. They aggregate multiple local and diffuse production installations, consumer facilities, storage facilities and monitoring tools and demand management. The main challenges when assessing the performance of an off-grid hybrid micro-grid system HMGS are the reliability of the system, the cost of electricity production and the operation environmental impact. Hence the tradeoff between three conflicting objectives makes the design of an optimal HMGS seen as a multi-objective optimization task. In this paper, we consider the optimization and the assessment of a HMGS in different Swedish cities to point out the potential of each location for HMGS investment. The HMGS consists of photovoltaic panels, wind turbines, diesel generator and battery storage. The HMGS model was simulated under one-year weather conditions data. A multi objective particle swarm optimization is used to find the optimal system configuration and the optimal component size for each location. An energy management system is applied to manage the operation of the different component of the system when feeding the load. The techno economics analysis shows the potential of HMGS in the Swedish rural development. (C) 2017 Elsevier Ltd. All rights reserved.

  • 26.
    Mahian, Omid
    et al.
    Ningbo Univ, Ningbo, Peoples R China..
    Yang, Liu
    Southeast Univ, Nanjing, Peoples R China..
    Poncet, Sebastien
    Univ Sherbrooke, Mech Engn Dept, Sherbrooke, PQ, Canada..
    Mesgarpour, Mehrdad
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Micro/nano energy2024In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 301, article id 131503Article in journal (Other academic)
  • 27.
    Markovska, N.
    et al.
    Macedonian Academy of Sciences and Arts (RCESD-MASA), Macedonia.
    Klemeš, J. J.
    University of Pannonia Veszprém, Hungary.
    Duić, N.
    University of Zagreb, Croatia.
    Guzović, Z.
    University of Zagreb, Croatia.
    Vad Mathiesen, B.
    Aalborg University, Denmark.
    Lund, H.
    Aalborg University, Denmark.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Sustainable development of energy, water and environment systems2014In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 76, p. 1-3Article in journal (Other academic)
  • 28.
    Marzi, E.
    et al.
    Department of Engineering and Architecture, University of Parma, Parma, Italy.
    Morini, M.
    Department of Engineering and Architecture, University of Parma, Parma, Italy.
    Saletti, C.
    Department of Engineering and Architecture, University of Parma, Parma, Italy.
    Vouros, Stavros
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zaccaria, Valentina
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Kyprianidis, Konstantinos
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Gambarotta, A.
    Department of Engineering and Architecture, University of Parma, Parma, Italy.
    Power-to-Gas for energy system flexibility under uncertainty in demand, production and price2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 284, article id 129212Article in journal (Refereed)
    Abstract [en]

    The growing penetration of non-programmable renewable energy sources and the consequent fluctuations in energy prices and availability lead to the need to enhance energy system flexibility and synergies between different energy vectors. This can be reached through sector integration. Among the most relevant technologies used for this purpose, Power-to-Gas systems allow excess renewable electricity to be converted directly into fuels that can be then stored or used. A smart energy system, however, which includes these innovative solutions, requires intelligent management methods to optimize its operation. This work investigates the operational strategy of energy systems integrated with Power-to-Gas solutions for seasonal storage, by developing an optimization model for the system, formulated as Mixed-Integer Linear Programming problem. The algorithm tackles the uncertain nature of future disturbances, such as energy needs, generation and price using two-stage stochastic programming. The algorithm is tested on grid-connected and 100% renewable energy supply case studies. The novel stochastic algorithm allows a more robust optimization compared to a deterministic optimization, and system management is ensured under several future disturbances realization. Furthermore, the integration of Power-to-Gas solutions warrants the energy security of the energy systems and acts as a buffer to forestall unpredictable behavior of the disturbances.

  • 29.
    Mohan, Sooraj
    et al.
    Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
    Dinesha, P.
    Department of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
    Campana, Pietro Elia
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    ANN-PSO aided selection of hydrocarbons as working fluid for low-temperature organic Rankine cycle and thermodynamic evaluation of optimal working fluid2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 259, article id 124968Article in journal (Refereed)
    Abstract [en]

    Organic Rankine cycle (ORC) has been demonstrated to extract useful work output from low-grade heat sources like solar-thermal, biomass/biofuel combustion, geothermal, and waste heat. However, working fluid selection for ORC is a complex process and calls for careful optimization. To address this problem, the current work constitutes a design of experiments approach with a full-factorial design. A heat source temperature of 150 °C is selected, and a list of 11 possible candidates of working fluid mixtures (among hydrocarbons) is taken. Work output and efficiencies from each fluid are determined based on the design of experiments, and the results are used to model an artificial neural network (ANN). Equations for work output and first law efficiency are developed using tan sigmoid function and ANN constants which act as objective functions that are maximized using multi-objective particle swarm optimization (PSO). The results of the ANN-PSO model is validated with the values from thermodynamic analysis with less than 2% error. The optimal working fluid obtained for maximum work output is R600a operating at an evaporator pressure of 1.88 MPa without any superheating. The resulting maximum work output is 7.15 kW at 8.05% thermal efficiency and an exergy efficiency of 38.13%.

  • 30.
    Neshat, M.
    et al.
    Center for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, 4006, QLD, Australia.
    Majidi Nezhad, Meysam
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Mirjalili, S.
    University Research and Innovation Center (EKIK), Óbuda University, Budapest, 1034, Hungary.
    Garcia, D. A.
    Department of Planning, Design, and Technology of Architecture, Sapienza University of Rome, Italy.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Gandomi, A. H.
    Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, 2007, NSW, Australia.
    Short-term solar radiation forecasting using hybrid deep residual learning and gated LSTM recurrent network with differential covariance matrix adaptation evolution strategy2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 278, article id 127701Article in journal (Refereed)
    Abstract [en]

    Developing an accurate and robust prediction of long-term average global solar irradiation plays a crucial role in industries such as renewable energy, agribusiness, and hydrology. However, forecasting solar radiation with a high level of precision is historically challenging due to the nature of this source of energy. Challenges may be due to the location constraints, stochastic atmospheric parameters, and discrete sequential data. This paper reports on a new hybrid deep residual learning and gated long short-term memory recurrent network boosted by a differential covariance matrix adaptation evolution strategy (ADCMA) to forecast solar radiation one hour-ahead. The efficiency of the proposed hybrid model was enriched using an adaptive multivariate empirical mode decomposition (MEMD) algorithm and 1+1EA-Nelder–Mead simplex search algorithm. To compare the performance of the hybrid model to previous models, a comprehensive comparative deep learning framework was developed consisting of five modern machine learning algorithms, three stacked recurrent neural networks, 13 hybrid convolutional (CNN) recurrent deep learning models, and five evolutionary CNN recurrent models. The developed forecasting model was trained and validated using real meteorological and Shortwave Radiation (SRAD1) data from an installed offshore buoy station located in Lake Michigan, Chicago, United States, supported by the National Data Buoy Centre (NDBC). As a part of pre-processing, we applied an autoencoder to detect the outliers in improving the accuracy of solar radiation prediction. The experimental results demonstrate that, firstly, the hybrid deep residual learning model performed best compared with other machine learning and hybrid deep learning methods. Secondly, a cooperative architecture of gated recurrent units (GRU) and long short-term memory (LSTM) recurrent models can enhance the performance of Xception and ResNet. Finally, using an effective evolutionary hyper-parameters tuner (ADCMA) reinforces the prediction accuracy of solar radiation.

  • 31.
    Nian, V.
    et al.
    Energy Studies Institute, National University of Singapore, Singapore.
    Jindal, G.
    Energy Studies Institute, National University of Singapore, Singapore.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    A feasibility study on integrating large-scale battery energy storage systems with combined cycle power generation – Setting the bottom line2019In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 185, p. 396-408Article in journal (Refereed)
    Abstract [en]

    Strong attention has been given to the costs and benefits of integrating battery energy storage systems (BESS) with intermittent renewable energy systems. What's neglected is the feasibility of integrating BESS into the existing fossil-dominated power generation system to achieve economic and environmental objectives. In response, a life cycle cost-benefit analysis method is introduced in this study taking into consideration three types of battery technologies, namely, vanadium redox flow battery, zinc bromine flow battery, and lithium-iron-phosphate battery. The objective is to evaluate the life cycle carbon emissions and cost of electricity production by combined cycle power generation with grid-connected BESS. Findings from the Singapore case study suggest a potential 3–5% reduction in the life cycle carbon emission factors which could translate to a cumulative carbon emission reduction of 9–16 million tonnes from 2018 to 2030 from electricity generation. Grid-connected BESS could reduce the levelized cost of electricity by 4–7%. A synergistic planning of CCGT and BESS could theoretically reduce the system level power generation capacity by 26% albeit a potential increase in the overall capital cost at the current cost of batteries. The projected battery cost reduction is critical in improving the feasibility of large-scale deployment. 

  • 32.
    Qiu, R.
    et al.
    National Engineering Laboratory for Pipeline Safety/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.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Klemeš, J. J.
    Sustainable Process Integration Laboratory – SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology – VUT Brno, Technická 2896/2, Brno, 616 69, Czech Republic.
    Liang, Y.
    National Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No.18, Changping District, Beijing, 102249, China.
    Guo, Z.
    Sinopec Engineering Incorporation, No.21, Anhui North Li'an Garden, Chaoyang District, Beijing, 100101, China.
    Chen, J.
    Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8563, Japan.
    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, Chiba, 277-8563, Japan.
    Roadmap to urban energy internet with wind electricity-natural gas nexus: Economic and environmental analysis2022In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 245Article in journal (Refereed)
    Abstract [en]

    Electrolysis hydrogen generation technology is one of the feasible ways to alleviate the problem of wind electricity curtailment. One promising hydrogen value-added application is to blend hydrogen into the natural gas grid and sell it as the heat energy carrier. This paper aims to discuss the feasibility of a roadmap to urban energy internet with wind electricity-natural gas nexus. Firstly, a framework is raised to integrate wind electricity generation, electrolysis hydrogen generation, and hydrogen-natural gas blending systems. Secondly, a series of reasonable hydrogen supply profiles are provided based on annual electricity curtailment and realistic natural gas scheduling. Then, an energy optimisation model and a techno-economic model are applied to simulate the generation of electricity and hydrogen, as well as determine the most economical hydrogen supply scheme. Finally, a case study in the Beijing-Tianjin-Hebei region of China is taken to validate the benefits of the proposed roadmap. The preferred scheme is worked out with the net present value of 88.8 M$, including the economy configurations of the electricity-hydrogen hybrid generation system, as well as the hydrogen-natural gas blending plan. The results also indicate that annual electricity curtailment and annual carbon emission are decreased by 204 GWh (48.8%) and 40.2 kt (49.9%).

  • 33.
    Shabani, Masoume
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Wallin, Fredrik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Dahlquist, Erik
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Department of Building Environment and Energy Engineering, Hong Kong Polytechnic University, Hong Kong.
    The impact of battery operating management strategies on life cycle cost assessment in real power market for a grid-connected residential battery application2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 270, article id 126829Article in journal (Refereed)
    Abstract [en]

    The relatively short lifetime of batteries is one of the crucial factors that affects its economic viability in current electricity markets. Thus, to make batteries a more viable technology in real power market from life cycle cost assessment perspective, full understanding of battery ageing parameters and which operating control strategies cause slower degradation rate is essential and still an open problem. This study deals with the 32 different battery operating control strategies to evaluate their importance on cyclic and calendric degradation, lifetime, and life cycle cost assessment of a battery system in a grid-connected residential application. In other words, it is evaluated that at which operating control strategy the system simulation results in a more beneficial system from techno-economic perspective. A battery modelling scenario is proposed to accurately estimate battery performance, degradation, and lifetime under real operational condition given different operating control strategies. An operational strategy, which benefits from the dynamic real-time electricity price scheme, is conducted to simulate the system operation. The key results show that selecting a proper state-of-charge control strategy positively affects the battery lifetime and consequently its net-present-value, in which the best strategy led to 30% improvement in net-present-value compared to the worst strategy.

  • 34.
    Sun, H.
    et al.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Chen, B.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Li, K.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Song, Y.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Yang, M.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Jiang, L.
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian, 116024, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Methane hydrate re-formation and blockage mechanism in a pore-level water-gas flow process2023In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 263, article id 125851Article in journal (Refereed)
    Abstract [en]

    Hydrate re-formation increases blockage risk and further reduces gas production efficiency. Considering the huge water production and gas migration, it is essential to determine the key parameters that control hydrate re-formation and blockage in the two-phase flow process. However, little research reveals the mechanism of hydrate re-formation in the water-dominated two-phase flow system. In this study, two-phase flow in hydrate sediment is simulated by controlling the water-gas flow rate, and the effect of effective sectional velocity on hydrate re-formation characteristics is analyzed. The experimental results showed that temperature and pressure followed a three-stage change trend in the water-dominated two-phase flow process: including hydrate re-formation induction stage I, mass hydrate re-formation and agglomeration stage II, and pore gas consumption stage III. Moreover, a lower effective sectional velocity of water (WESV) would reduce the gas concentration gradient between water and hydrate to enhance the hydrate re-formation process. Meanwhile, the gas phase impeded the mass transfer on the water-hydrate interface and acted as the nucleation site to promote hydrate re-formation. Furthermore, it was noticed that the relationship between the onset time of flow blockage and WESV was linearly positive, however, the amount of hydrate re-formation reduced with increasing WESV. 

  • 35.
    Tang, Y.
    et al.
    Academy of Chinese Energy Strategy, China University of Petroleum-Beijing, Changping, Beijing, China.
    Zhang, Q.
    Academy of Chinese Energy Strategy, China University of Petroleum-Beijing, Changping, Beijing, China.
    Mclellan, B.
    Graduate School of Energy Science, Kyoto University, Japan.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin, China.
    Study on the impacts of sharing business models on economic performance of distributed PV-Battery systems2018In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 161, p. 544-558Article in journal (Refereed)
    Abstract [en]

    In order to promote the development of energy storage industry and relieve the retirement pressure of EV batteries, the application of retired EV batteries in energy storage for second-life use has gained significant attentions. Considering that distributed battery storages are still not economically attractive enough at present, the booming of sharing economy may provide a more feasible option. Based on a non-cooperative game theoretical model, this study aims to explore the impact of sharing business models on economic performance of retired EV batteries integrated with distributed PV systems. Four scenarios were proposed, including: a traditional scenario of S1 - individual battery storages, the sharing scenarios of S2 - shared battery storage, S3 - shared PV generation, and S4 - shared battery storage and shared PV generation. Through a case study in Beijing, the obtained results show that: (i)although sharing business models may not guarantee to bring economic benefits to each individual, they can contribute to a reduction in electricity expenses of the whole community; (ii) sharing business models can enhance PV self-consumption ratio and battery utilization ratio; (iii) sharing business models can improve the NPV by 1995 RMB-6975 RMB compared to the traditional scenario.

  • 36.
    Vassileva, Iana
    et al.
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Campillo, Javier
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tecnol Bolivar Univ, Fac Engn, Cartagena 130001, Colombia..
    Adoption barriers for electric vehicles: Experiences from early adopters in Sweden2017In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 120, p. 632-641Article in journal (Refereed)
    Abstract [en]

    Electric vehicles are considered as one of the most effective technologies for reducing current greenhouse gas emissions from the transport sector. Although in many countries, local and national governments have introduced incentives and subsidies to facilitate the electric vehicle market penetration, in Sweden, such benefits have been limited. Results from a survey carried out among private owners of electric vehicles are presented in this paper, including the analysis of the respondents socio-demographic characteristics, reasons for choosing an electric vehicle, charging locations and driving preferences, among others. The main results characterize current electric vehicle drivers as male, well-educated, with medium-high income; electric vehicles are used mainly for private purposes and charged at home during night time. Furthermore, the paper presents an analysis of the impact of large-scale penetration of electric vehicles on existing power distribution systems. The findings presented in this paper provide important insights for assuring a sustainable large-scale penetration of electric vehicles by learning from the experiences of early adopters of the technology and by analyzing the impact of different EV penetration scenarios on the power distribution grid.

  • 37.
    Vassileva, Iana
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Wallin, Fredrik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Dahlquist, Erik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Understanding energy consumption behavior for future demand response strategy development2012In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 46, no 1, p. 94-100Article in journal (Refereed)
    Abstract [en]

    Encouraging consumers to use less electricity through information is essential for sustainable use of energy and demand response is indeed a key component of the smart grids concept. The aim with this study is to understand differences between consumer categories and what this could mean e.g. to develop effective demand response measures. In-depth analyses of answers from a questionnaire sent out to 2000 households, contribute to a better understanding of Swedish households' energy related behavior. The households have been provided with a web-site enabling them to check their daily electricity consumption compared to previous months/years and even get advice and tips on how to reduce electricity consumption. The results show clear differences in the response rates from different type of residence, different income areas of the city and in the most preferred ways of receiving information-feedback. The web based feedback, provided by the local energy company, received more visits (and more frequently) from respondents living in houses than from apartments.

    The analysis of the answers raises questions about the effectiveness of using only one tool of providing energy consumption information to the customers (web-site, in this case) and stresses the importance of applying an individual approach to different energy users.

  • 38.
    Wang, F.
    et al.
    Tianjin University, Ministry of Education of China, Tianjin, China.
    Deng, S.
    Tianjin University, Ministry of Education of China, Tianjin, China.
    Zhao, J.
    Tianjin University, Ministry of Education of China, Tianjin, China.
    Wang, J.
    Tianjin University, Ministry of Education of China, Tianjin, China.
    Sun, T.
    Tianjin University, Ministry of Education of China, Tianjin, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin University, Ministry of Education of China, Tianjin, China; Royal Institute of Technology, Stockholm, Sweden.
    Performance and economic assessments of integrating geothermal energy into coal-fired power plant with CO2 capture2017In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 119, p. 278-287Article in journal (Refereed)
    Abstract [en]

    A novel carbon capture and storage system integrated with geothermal energy was proposed to reduce energy consumption in the post-combustion CO2 capture (PCC) process. Geothermal energy at medium temperature was used to provide the heat required for solvent regeneration. A technical and economic assessment was conducted based on a 300 MWe coal-fired power plant. Additionally, the integrated system was also compared with a stand-alone geothermal power (GP) plant to evaluate individual advantages. Both an enhanced geothermal system (EGS) and a hot sedimentary aquifer (HSA) reservoir were selected to identify the effect of geological properties and heat characteristics on system performance. The results indicated that the geothermal-assisted post-combustion CO2 capture (GPCC) plant exhibited better performance than the PCC plant. The net plant average efficiency increased 5.56% and 4.42% in the EGS scenario and HSA scenario, respectively. Furthermore, the net incremental geothermal efficiency obtained corresponded to 21.34% and 20.35% in the EGS scenario and HSA scenario, respectively. The economic assessment indicated that the GPCC systems in both the EGS scenario and HSA scenario had lower marginal cost of electricity (70.84 $/MWh and 101.06 $/MWh) when compared with that of the stand-alone GP systems (151.09 $/MWh and 101.95 $/MWh). 

  • 39.
    Wang, F.
    et al.
    Sichuan University, Chengdu, China.
    Xu, J.
    Sichuan University, Chengdu, China.
    Liu, L.
    Sichuan University, Chengdu, China.
    Yin, G.
    tate Grid Power Supply Branch of Huili County, Liangshan Autonomous Prefecture, 615100, China.
    Wang, J.
    Water Resource Institute, China Institute of Water Resources and Hydropower Research, Beijing, 100048, China.
    Yan, Jinyue
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Optimal design and operation of hybrid renewable energy system for drinking water treatment2021In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 219, article id 119673Article in journal (Refereed)
    Abstract [en]

    The industrial process of drinking water treatment requires intensive energy, leading to high enterprise costs and abundant carbon emissions. To ensure cost-effective and low polluting power supply for the above process, this paper proposes to deploy the grid-connected hybrid renewable system. A multi-objective nonlinear dynamic model mixed with integer variables is established for the decision makers, in which both system configurations and operations as well as benefits trade-offs from four dimensions are simultaneously considered. The ε-constraint method and system planner attitude parameters are introduced to transform the proposed model into its equivalent single objective form, which is further been solved by the LINGO software. A case study in China is given to assess the viability of the proposed model, in which optimal system configuration, economically feasible self-sufficiency ratio and optimal energy balance are obtained. Influences of electricity pricing strategies and natural resource changes on the systems are also analyzed and compared. It is found that the deployment of grid-connected hybrid wind/PV/storage system can help power users to cope with the future electricity price variation risks, with the feasible self-sufficiency ratio reaching 95%. 

  • 40.
    Wetterlund, Elisabeth
    et al.
    Linkoping Univ.
    Leduc, Sylvain
    Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria.
    Dotzauer, Erik
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Kindermann, Georg
    Int Inst Appl Syst Anal, A-2361 Laxenburg, Austria.
    Optimal localisation of biofuel production on a European scale2012In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 41, no 1, p. 462-472Article in journal (Refereed)
    Abstract [en]

    This paper presents the development and use of an optimisation model suitable for analysis of biofuel production scenarios in the EU, with the aim of examining second generation biofuel production. Two policy instruments are considered - targeted biofuel support and a CO2 cost. The results show that over 3% of the total transport fuel demand can be met by second generation biofuels at a cost of approximately 65-73 EUR/MWh. With current energy prices, this demands biofuel support comparable to existing tax exemptions (around 30 EUR/MWh), or a CO2 cost of around 60 EUR/t(CO2). Parameters having large effect on biofuel production include feedstock availability, fossil fuel price and capital costs. It is concluded that in order to avoid suboptimal energy systems, heat and electricity applications should also be included when evaluating optimal bioenergy use. It is also concluded that while forceful policies promoting biofuels may lead to a high biofuel share at reasonable costs, this is not a certain path towards maximised CO2 emission mitigation. Policies aiming to promote the use of bioenergy thus need to be carefully designed in order to avoid conflicts between different parts of the EU targets for renewable energy and CO2 emission mitigation. (C) 2012 Elsevier Ltd. All rights reserved.

  • 41.
    Zhu, K.
    et al.
    Tianjin University of Commerce, China.
    Cui, Z.
    Tianjin University of Commerce, China.
    Wang, Y.
    Tianjin University of Commerce, China.
    Li, Hailong
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Tianjin University of Commerce, China.
    Zhang, X.
    ABB Corporate Research, Sweden.
    Franke, C.
    Estimating the maximum energy-saving potential based on IT load and IT load shifting2017In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 138, p. 902-909Article in journal (Refereed)
    Abstract [en]

    Cooling system consumes more than 35% of total electricity in most data centers. The provided cooling normally exceeds the actual demand of IT equipment in order to assure the safe operation, resulting in a low energy efficiency. In this paper, a novel method based on demand response was proposed to precisely control the cooling supply, and the energy saving potential was assessed systematically. Compared to the reference case, in which the cooling demand is determined by assuming all of servers are in the running status, when the cooling demand was determined based on the measured dynamic IT load at room level, row level, rack level and server level, it can be reduced by 7.9%, 14.2%, 15.6% and 17.9% respectively for the random selected 48 h. In addition, IT load shifting also has a big potential to save energy, as it can make the cooling system working at a higher energy efficiency, which varies with loads. Two cases were studied: even distribution of IT load and optimized IT load shifting. Compared to the best case that determines the cooling demand according to the IT load at server level, they can further reduce the electricity consumption of cooling systems by 0.9%, and 1.2%. 

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