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  • 1.
    Aaltonen, Harri
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Kyrki, Ville
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Pourakbari-Kasmaei, Mahdi
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 14, article id 4960Article in journal (Refereed)
    Abstract [en]

    Battery storage is emerging as a key component of intelligent green electricitiy systems. The battery is monetized through market participation, which usually involves bidding. Bidding is a multi‐objective optimization problem, involving targets such as maximizing market compensation and minimizing penalties for failing to provide the service and costs for battery aging. In this article, battery participation is investigated on primary frequency reserve markets. Reinforcement learning is applied for the optimization. In previous research, only simplified formulations of battery aging have been used in the reinforcement learning formulation, so it is unclear how the optimizer would perform with a real battery. In this article, a physics‐based battery aging model is used to assess the aging. The contribution of this article is a methodology involving a realistic battery simulation to assess the performance of the trained RL agent with respect to battery aging in order to inform the selection of the weighting of the aging term in the RL reward formula. The RL agent performs day-ahead bidding on the Finnish Frequency Containment Reserves for Normal Operation market, with the objective of maximizing market compensation, minimizing market penalties and minimizing aging costs.

  • 2.
    Aaltonen, Harri
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Subramanya, Rakshith
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland; International Research Laboratory of Computer Technologies, ITMO University, 197101 St. Petersburg, Russia.
    A simulation environment for training a reinforcement learning agent trading a battery storage2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 17, article id 5587Article in journal (Refereed)
    Abstract [en]

    Battery storages are an essential element of the emerging smart grid. Compared to other distributed intelligent energy resources, batteries have the advantage of being able to rapidly react to events such as renewable generation fluctuations or grid disturbances. There is a lack of research on ways to profitably exploit this ability. Any solution needs to consider rapid electrical phenomena as well as the much slower dynamics of relevant electricity markets. Reinforcement learning is a branch of artificial intelligence that has shown promise in optimizing complex problems involving uncertainty. This article applies reinforcement learning to the problem of trading batteries. The problem involves two timescales, both of which are important for profitability. Firstly, trading the battery capacity must occur on the timescale of the chosen electricity markets. Secondly, the real-time operation of the battery must ensure that no financial penalties are incurred from failing to meet the technical specification. The trading-related decisions must be done under uncertainties, such as unknown future market prices and unpredictable power grid disturbances. In this article, a simulation model of a battery system is proposed as the environment to train a reinforcement learning agent to make such decisions. The system is demonstrated with an application of the battery to Finnish primary frequency reserve markets.

  • 3.
    Aldieri, Luigi
    et al.
    Department of Economic and Statistical Sciences, University of Salerno, 84084 Fisciano, Italy.
    Grafström, Jonas
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences. The Ratio Institute, 103 64 Stockholm, Sweden.
    Paolo Vinci, Concetto
    Department of Economic and Statistical Sciences, University of Salerno, 84084 Fisciano, Italy.
    The Effect of Marshallian and Jacobian Knowledge Spilloverson Jobs in the Solar, Wind and Energy Efficiency Sector2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 14, article id 4269Article in journal (Refereed)
    Abstract [en]

    The purpose of this paper is to establish if Marshallian and Jacobian knowledge spillovers affect job creation in the green energy sector. Whether these two effects exist is important for the number of jobs created in related fields and jobs pushed away in other sectors. In the analysis, the production efficiency, in terms of jobs and job spillovers, from inventions in solar, wind and energy efficiency, is explored through data envelopment analysis (DEA), based on the Malmquist productivity index, and tobit regression. A panel dataset of American and European firms over the period of 2002–2017 is used. The contribution to the literature is to show the role of the spillovers from the same technology sector (Marshallian externalities), and of the spillovers from more diversified activity (Jacobian externalities). Since previous empirical evidence concerning the innovation effects on the production efficiency is yet weak, the paper attempts to bridge this gap. The empirical findings suggest negative Marshallian externalities, while Jacobian externalities have no statistical impact on the job creation process. The findings are of strategic importance for governments who are developing industrial strategies for renewable energy.

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  • 4.
    Alfieri, Luisa
    et al.
    Department of Engineering, University of Naples Parthenope, Centro Direzionale of Naples.
    Bracale, Antonio
    Department of Engineering, University of Naples Parthenope, Centro Direzionale of Naples.
    Carpinelli, Guido
    Department of Electrical Engineering and Information Technology, University of Naples Federico II.
    Larsson, Anders
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    A Wavelet-Modified ESPRIT Hybrid Method for Assessment of Spectral Components from 0 to 150 kHz2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 1, article id 97Article in journal (Refereed)
    Abstract [en]

    Waveform distortions are an important issue in distribution systems. In particular, the assessment of very wide spectra, that include also components in the 2-150 kHz range, has recently become an issue of great interest. This is due to the increasing presence of high-spectral emission devices like end-user devices and distributed generation systems. This study proposed a new sliding-window wavelet-modified estimation of signal parameters by rotational invariance technique (ESPRIT) method, particularly suitable for the spectral analysis of waveforms that have very wide spectra. The method is very accurate and requires reduced computational effort. It can be applied successfully to detect spectral components in the range of 0-150 kHz introduced both by distributed power plants, such as wind and photovoltaic generation systems, and by end-user equipment connected to grids through static converters, such as fluorescent lamps.

  • 5.
    Alfieri, Luisa
    et al.
    Department of Electrical Engineering and Information Technology, University of Naples Federico II, Italy.
    Bracale, Antonio
    Department of Engineering, University of Naples Parthenope, Centro Direzionale of Naples.
    Larsson, Anders
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    New Power Quality Indices for the Assessment of Waveform Distortions from 0 to 150 kHz in Power Systems with Renewable Generation and Modern Non-Linear Loads2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 10, article id 1633Article in journal (Refereed)
    Abstract [en]

    The widespread use of power electronics converters, e.g., to interface renewable generation systems with the grid or to supply some high-efficiency loads, has caused increased levels of waveform distortions in the modern distribution system. Voltage and current waveforms include spectral components from 0 kHz to 150 kHz, characterized by a non-uniform time-frequency behavior. This wide interval of frequencies is currently divided into "low-frequency" (from 0 kHz to 2 kHz) and "high-frequency" (from 2 kHz to 150 kHz). While the low-frequencies have been exhaustively investigated in the relevant literature and are covered by adequate standardization, studies for the high-frequencies have been addressed only in the last decade to fill current regulatory gaps. In this paper, new power quality (PQ) indices for the assessment of waveform distortions from 0 kHz to 150 kHz are proposed. Specifically, some currently available indices have been properly modified in order to extend their application also to wide-spectrum waveforms. In the particular case of waveform distortions due to renewable generation, numerical applications prove that the proposed indices are useful tools for the characterization of problems (e.g., overheating, equipment malfunctioning, losses due to skin effects, hysteresis losses or eddy current losses) in cases of both low-frequency and high-frequency distortions

  • 6.
    Bagheri, Azam
    et al.
    AI & Future Technologies, Industrial and Digital Solutions, ÅF Pöyry AB (Afry), 411 19 Gothenburg, Sweden.
    de Oliveira, Roger Alves
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Bollen, Math H. J.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Gu, Irene Y. H.
    Department Electrical Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden.
    A Framework Based on Machine Learning for Analytics of Voltage Quality Disturbances2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 4, article id 1283Article in journal (Refereed)
    Abstract [en]

    This paper proposes a machine-learning-based framework for voltage quality analytics, where the space phasor model (SPM) of the three-phase voltages before, during, and after the event is applied as input data. The framework proceeds along with three main steps: (a) event extraction, (b) event characterization, and (c) additional information extraction. During the first step, it utilizes a Gaussian-based anomaly detection (GAD) technique to extract the event data from the recording. Principal component analysis (PCA) is adopted during the second step, where it is shown that the principal components correspond to the semi-minor and semi-major axis of the ellipse formed by the SPM. During the third step, these characteristics are interpreted to extract additional information about the underlying cause of the event. The performance of the framework was verified through experiments conducted on datasets containing synthetic and measured power quality events. The results show that the combination of semi-major axis, semi-minor axis, and direction of the major axis forms a sufficient base to characterize, classify, and eventually extract additional information from recorded event data.

  • 7.
    Baidar, Binaya
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Nicolle, Jonathan
    Institut de recherche d’Hydro-Québec (IREQ), Varennes, QC J3X 1S1, Canada.
    Gandhi, Bhupendra K.
    Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India.
    Cervantes, Michel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Numerical Study of the Winter–Kennedy Flow Measurement Method in Transient Flows2020In: Energies, E-ISSN 1996-1073, Vol. 13, no 6, article id 1310Article in journal (Refereed)
    Abstract [en]

    This paper explores the possibility of using the Winter–Kennedy (WK) method for transient flow rate measurement in hydraulic turbines. Computational fluid dynamic (CFD) analysis of a numerical model of an axial turbine was carried out for accelerating and decelerating flows. Those were obtained by linearly opening and closing of the guide vanes, respectively, while retaining the inlet pressure constant during the simulations. The behavior of several WK configurations on a cross-sectional plane and along the azimuthal direction of the spiral casing was studied during the transients. The study showed that there are certain WK configurations that are more stable than others. The physical mechanism behind the stability (or instability) of the WK method during transients is presented. Using the steady WK coefficient obtained at the best efficiency point (BEP), the WK method could estimate the transient flow rate with a deviation of about 7.5% and 3.5%, for accelerating and decelerating flow, respectively.

  • 8.
    Bin Asad, S M Sayeed
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Lundström, Staffan
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Andersson, Anders
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Study the Flow behind a Semi-Circular Step Cylinder (Laser Doppler Velocimetry (LDV) and Computational Fluid Dynamics (CFD))2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 3, article id 332Article in journal (Refereed)
    Abstract [en]

    Laser Doppler Velocimetry (LDV) measurements, flow visualizations and unsteadyReynolds-Averaged Navier-Stokes (RANS) Computational Fluid Dynamics (CFD) simulations havebeen carried out to study the turbulent wake that is formed behind a semi-circular step cylinder ata constant flow rate. The semi-circular cylinder has two diameters, a so-called step cylinder. Theresults from the LDV measurements indicate that wake length and vortex shedding frequency varieswith the cylinder diameter. This implies that a step cylinder can be used to attract fish of differentsize. By visualizations of the formation of a recirculation region and the well-known von Kármánvortex street behind the cylinder are disclosed. The simulation results predict the wake length andshedding frequency well for the flow behind the large cylinder but fail to capture the dynamics ofthe flow near the step in diameter to some extent and the flow behind the small cylinder to a largerextent when compared with measurements.

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  • 9.
    Bokde, Neeraj
    et al.
    Department of Engineering Renewable Energy and Thermodynamics, Aarhus University, Aarhus, Denmark.
    Feijóo, Andrés
    Departamento de Enxeñería Eléctrica Universidade de Vigo, Campus de Lagoas-Marcosende, Vigo, Spain.
    Al-Ansari, Nadhir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Tao, Siyu
    School of Electrical Engineering, Southeast University, Nanjing, China.
    Yaseen, Zaher Mundher
    Sustainable Developments in Civil Engineering Research Group, Faculty of Civil Engineering, Ton DucThang University, Ho Chi Minh City, Vietnam.
    The Hybridization of Ensemble Empirical Mode Decomposition with Forecasting Models: Application of Short-Term Wind Speed and Power Modeling2020In: Energies, E-ISSN 1996-1073, Vol. 13, no 7, p. 1-23, article id 1666Article in journal (Refereed)
    Abstract [en]

    In this research, two hybrid intelligent models are proposed for prediction accuracy enhancement for wind speed and power modeling. The established models are based on the hybridisation of Ensemble Empirical Mode Decomposition (EEMD) with a Pattern Sequence-based Forecasting (PSF) model and the integration of EEMD-PSF with Autoregressive Integrated Moving Average (ARIMA) model. In both models (i.e., EEMD-PSF and EEMD-PSF-ARIMA), the EEMD method is used to decompose the time-series into a set of sub-series and the forecasting of each sub-series is initiated by respective prediction models. In the EEMD-PSF model, all sub-series are predicted using the PSF model, whereas in the EEMD-PSF-ARIMA model, the sub-series with high and low frequencies are predicted using PSF and ARIMA, respectively. The selection of the PSF or ARIMA models for the prediction process is dependent on the time-series characteristics of the decomposed series obtained with the EEMD method. The proposed models are examined for predicting wind speed and wind power time-series at Maharashtra state, India. In case of short-term wind power time-series prediction, both proposed methods have shown at least 18.03 and 14.78 percentage improvement in forecast accuracy in terms of root mean square error (RMSE) as compared to contemporary methods considered in this study for direct and iterated strategies, respectively. Similarly, for wind speed data, those improvement observed to be 20.00 and 23.80 percentages, respectively. These attained prediction results evidenced the potential of the proposed models for the wind speed and wind power forecasting. The current proposed methodology is transformed into R package ‘decomposedPSF’ which is discussed in the Appendix.

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  • 10.
    Bollen, Math
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Rönnberg, Sarah
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Hosting Capacity of the Power Grid for Renewable Electricity Production and New Large Consumption Equipment2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 9, article id 1325Article in journal (Refereed)
    Abstract [en]

    After a brief historical introduction to the hosting-capacity approach, the hosting capacity is presented in this paper as a tool for distribution-system planning under uncertainty. This tool is illustrated by evaluating the readiness of two low-voltage networks for increasing amounts of customers with PV panels or with EV chargers. Both undervoltage and overvoltage are considered in the studies presented here. Probability distribution functions are calculated for the worst-case overvoltage and undervoltage as a function of the number of customers with PV or EV chargers. These distributions are used to obtain 90th percentile values that act as a performance index. This index is compared with an overvoltage or undervoltage limit to get the hosting capacity. General aspects of the hosting-capacity calculations (performance indices, limits, and calculation methods) are discussed for a number of other phenomena: overcurrent; fast voltage magnitude variations; voltage unbalance; harmonics and supraharmonics. The need for gathering data and further development of models for existing demand is emphasised in the discussion and conclusions

  • 11.
    Bonturi, Nemailla
    et al.
    Department of Materials and Bioprocess Engineering, School of Chemical Engineering, State University of Campinas.
    Matsakas, Leonidas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Nilsson, Robert
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Miranda, Everson Alves
    Department of Materials and Bioprocess Engineering, School of Chemical Engineering, State University of Campinas.
    Berglund, Kris
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Single Cell Oil Producing Yeasts Lipomyces starkeyi and Rhodosporidium toruloides: Selection of Extraction Strategies and Biodiesel Property Prediction2015In: Energies, E-ISSN 1996-1073, Vol. 8, no 6, p. 5040-5052Article in journal (Refereed)
    Abstract [en]

    Single cell oils (SCOs) are considered potential raw material for the production of biodiesel. Rhodosporidium sp. and Lipomyces sp. are good candidates for SCO production. Lipid extractability differs according to yeast species and literature on the most suitable method for each oleaginous yeast species is scarce. This work aimed to investigate the efficiency of the most cited strategies for extracting lipids from intact and pretreated cells of Rhodosporidium toruloides and Lipomyces starkeyi. Lipid extractions were conducted using hexane or combinations of chloroform and methanol. The Folch method resulted in the highest lipid yields for both yeasts (42% for R. toruloides and 48% for L. starkeyi). Also, this method eliminates the cell pretreatment step. The Bligh and Dyer method underestimated the lipid content in the tested strains (25% for R. toruloides and 34% for L. starkeyi). Lipid extractability increased after acid pretreatment for the Pedersen, hexane, and Bligh and Dyer methods. For R. toruloides unexpected fatty acid methyl esters (FAME) composition were found for some lipid extraction strategies tested. Therefore, this work provides useful information for analytical and process development aiming at biodiesel production from the SCO of these two yeast species.

  • 12.
    Brännvall, Rickard
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab. ICE Data Center, RISE Research Institutes of Sweden AB, 973 47 Luleå, Sweden.
    Gustafsson, Jonas
    ICE Data Center, RISE Research Institutes of Sweden AB, 973 47 Luleå, Sweden.
    Sandin, Fredrik
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Modular and Transferable Machine Learning for Heat Management and Reuse in Edge Data Centers2023In: Energies, E-ISSN 1996-1073, Vol. 16, no 5, article id 2255Article in journal (Refereed)
    Abstract [en]

    This study investigates the use of transfer learning and modular design for adapting a pretrained model to optimize energy efficiency and heat reuse in edge data centers while meeting local conditions, such as alternative heat management and hardware configurations. A Physics-Informed Data-Driven Recurrent Neural Network (PIDD RNN) is trained on a small scale-model experiment of a six-server data center to control cooling fans and maintain the exhaust chamber temperature within safe limits. The model features a hierarchical regularizing structure that reduces the degrees of freedom by connecting parameters for related modules in the system. With a RMSE value of 1.69, the PIDD RNN outperforms both a conventional RNN (RMSE: 3.18), and a State Space Model (RMSE: 2.66). We investigate how this design facilitates transfer learning when the model is fine-tuned over a few epochs to small dataset from a second set-up with a server located in a wind tunnel. The transferred model outperforms a model trained from scratch over hundreds of epochs.

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  • 13.
    Busatto, Tatiano
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Rönnberg, Sarah
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Bollen, Math
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Comparison of Models of Single-Phase Diode Bridge Rectifiers for Their Use in Harmonic Studies with Many Devices2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 1, article id 66Article in journal (Refereed)
    Abstract [en]

    Harmonic modeling of low-voltage networks with many devices requires simple but accurate models. This paper investigates the advantages and drawbacks of such models to predict the current harmonics created by single-phase full-bridge rectifiers. An overview is given of the methods, limiting the focus to harmonic analysis. The error of each method, compared to an accurate numerical simulation model, is quantified in frequency and time domain considering realistic input scenarios, including background voltage distortion and different system impedances. The results of the comparison are used to discuss the applicability of the models depending on the harmonic studies scale and the required level of detail. It is concluded that all models have their applicability, but also limitations. From the simplest and fastest model, which does not require a numerical solution, to the more accurate one that allows discontinuous conduction mode to be included, the trade-off involves accuracy and computational complexity.

  • 14.
    Daugela, Ignas
    et al.
    Department of Geodesy and Cadaster, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania; Antanas Gustaitis’ Aviation Institute, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania.
    Suziedelyte Visockiene, Jurate
    Department of Geodesy and Cadaster, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania.
    Kumpiene, Jurate
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Geosciences and Environmental Engineering.
    Suzdalev, Ivan
    Antanas Gustaitis’ Aviation Institute, Vilnius Gediminas Technical University, Vilnius, 10223, Lithuania.
    Measurements of flammable gas concentration in landfill areas with a low‐cost sensor2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 13, article id 3967Article in journal (Refereed)
    Abstract [en]

    Global warming, as the result of the negative impact of humans on climate change, has been observed based on various data sources. Various measures have aimed to reduce anthropogenic factors, and also to lower carbon dioxide (CO2) and methane CH4 emissions. One of the main contributors to anthropogenic factors is organic waste in municipal solid waste landfills. There are many landfills where cost‐effective rapid technologies for the identification and quantification of CH4 emission sites are not applied. There is still a need for the development of accessible and cost-effective methods that react in a real‐time manner for the rapid detection and monitoring of methane emissions. This paper’s main goal is to create a prototype sensor suitable for operational measurement of the gas value, suitable for integration into geodetic equipment or an unmanned aerial vehicle system. A sensor system (device) was developed, which consisted of three semiconductor sen-sors—MQ2, MQ4, and MQ135—which aimed to capture flammable gases (CO2, CH4, O2 purity) and to evaluate the averages of the measured values from the components mounted on the board—the semiconductor sensors. The sensors were calibrated in a laboratory and tested in a closed landfill. The measurement data consisted of the read resistances (analog signal) from the MQ2, MQ4, and MQ135 sensors, and the relative humidity and the temperature (digital signal) of the DHT2 sensor with a timestamp calculated by the RTC module. The use of the method was confirmed because the sensors reacted as expected when placed in the vicinity of the gas collection well. Furthermore, the sensor will be tested and improved for field work in landfill sites.

  • 15.
    de Oliveira, Tiago Elias Castelo
    et al.
    Electrical Energy Systems, Technological University of Eindhoven, Eindhoven, The Netherlands.
    Bollen, Math
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Ribeiro, Paulo Fernando
    Advanced Power Technologies and Innovations in Systems and Smart Grids Group, Federal University of Itajuba, Itajuba, Brazil.
    de Carvalho, Pedro M. S.
    Energy Scientific Area, Instituto Superior Tecnico, Lisbon, Portugal.
    Zambroni, Antônio C.
    Advanced Power Technologies and Innovations in Systems and Smart Grids Group, Federal University of Itajuba, Itajuba, Brazil.
    Bonatto, Benedito D.
    Advanced Power Technologies and Innovations in Systems and Smart Grids Group, Federal University of Itajuba, Itajuba, Brazil.
    The Concept of Dynamic Hosting Capacity for Distributed Energy Resources: Analytics and Practical Considerations2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 13, article id 2576Article in journal (Refereed)
    Abstract [en]

    The hosting capacity approach is presented as a planning, improving, and communication tool for electrical distribution systems operating under specific uncertainties, such as power quality issues, power stabilities, and reliability, among others. In other words, it is an important technique, when renewable sources are present, to answer the amount of power that is possible to supply to the system without trespassing power performance limits. However, the power flow in a distribution system, for instance, can change throughout time due to the penetration of distributed generation, as well as load consumption. Based on the dynamic nature existing in distribution grids nowadays, it is important to highlight that the hosting capacity should not be calculated in a specifically chosen time only, but must be analyzed throughout a period of time. Thus, this paper introduces an extended concept of hosting capacity in relation to an integrated impact of harmonic voltage distortion and voltage rise as a function of time for daily, weekly, monthly, or even yearly periods. This extended concept is named as Dynamic Hosting Capacity (DHC(t)). General aspects of DHC(t) are demonstrated via measured data on a photovoltaic system (PV) connected at a low-voltage (LV) side of a university building.

  • 16.
    Efkarpidis, Nikolaos
    et al.
    Institute of Electric Power Systems, University of Applied Sciences and Arts Northwestern Switzerland, (FHNW), Klosterzelgstrasse 2, CH-5210 Windisch, Switzerland.
    Goranovic, Andrija
    Institute of Computer Technology, TU Wien, Gusshaus Str. 27-29/e384, AT-1040 Vienna, Austria.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Geidl, Martin
    Institute of Electric Power Systems, University of Applied Sciences and Arts Northwestern Switzerland, (FHNW), Klosterzelgstrasse 2, CH-5210 Windisch, Switzerland.
    Herbst, Ingo
    Siemens Schweiz AG Smart Infrastructure, Freilagerstrasse 40, CH-8047 Zurich, Switzerland.
    Wilker, Stefan
    Institute of Computer Technology, TU Wien, Gusshaus Str. 27-29/e384, AT-1040 Vienna, Austria.
    Sauter, Thilo
    Institute of Computer Technology, TU Wien, Gusshaus Str. 27-29/e384, AT-1040 Vienna, Austria.
    A Generic Framework for the Definition of Key Performance Indicators for Smart Energy Systems at Different Scales2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 4, article id 1289Article in journal (Refereed)
    Abstract [en]

    The growing integration of intermittent renewable energy sources (RESs) and the increasing trend of shutting down fossil-fuel-based power plants has brought about the need for additional flexibility in energy systems. This flexibility can be provided in various forms, including controllable generation and consumption, storage, conversions, and exchanges with interconnected systems. In this context, an increasing focus is placed on the development of smart energy systems (SESs) that combine different types of distributed energy resources (DERs), information and communication technologies (ICTs), demand side management (DSM), and energy conversion technologies. The utilization of SESs can lead to multiple benefits for the stakeholders involved; therefore, the assessment of their performance is a primary concern. Due to their multidisciplinary nature, there are no known or universally accepted standards for assessing the performance of SESs. Previous efforts only define key performance indicators (KPIs) for individual homogeneous subsystems, focusing on a specific SES type and application area. This paper focuses on the development of a novel comprehensive KPI framework that can be applied to any type of SES, regardless of the application area. The proposed framework consists of four layers that specify the application area, the main SES requirements, and the involved stakeholders’ objectives. Next, the KPIs are identified for each of the stakeholders’ objectives. The proposed KPI framework is applied to the use case of a European research project with different application areas, to demonstrate its features. Finally, a repository of KPIs is identified for each use case with respect to the aforementioned SES requirements.

  • 17.
    Fischer, Robert
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Elfgren, Erik
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Toffolo, Andrea
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Energy Supply Potentials in the Northern Counties of Finland, Norway and Sweden towards Sustainable Nordic Electricity and Heating Sectors: A Review2018In: Energies, E-ISSN 1996-1073, Vol. 11, no 4, article id 751Article in journal (Refereed)
    Abstract [en]

    The lands in the northernmost corner of Europe present contradictory aspects in their social and economic development. Urban settlements are relatively few and small-sized, but rich natural resources (minerals, forests, rivers) attract energy-intensive industries. Energy demand is increasing as a result of new investments in mining and industries, while reliable energy supply is threatened by the planned phase out of Swedish nuclear power, the growth of intermittent power supplies and the need to reduce fossil fuel consumption, especially in the Finnish and Norwegian energy sectors. Given these challenges, this paper investigates the potentials of so far unexploited energy resources in the northern counties of Finland, Norway and Sweden by comparing and critically analyzing data from statistic databases, governmental reports, official websites, research projects and academic publications. The criteria for the technical and economic definition of potentials are discussed separately for each resource. It is concluded that, despite the factors that reduce the theoretical potentials, significant sustainable techno-economic potentials exist for most of the resources, providing important insights about the possible strategies to contribute to a positive socio-economic development in the considered regions.

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  • 18.
    Fischer, Robert
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Elfgren, Erik
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Toffolo, Andrea
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Towards Optimal Sustainable Energy Systems in Nordic Municipalities2020In: Energies, E-ISSN 1996-1073, Vol. 13, no 2, article id 290Article in journal (Refereed)
    Abstract [en]

    Municipal energy systems in the northern regions of Finland, Norway, and Sweden facemultiple challenges: large-scale industries, cold climate, and a high share of electric heatingcharacterize energy consumption and cause significant peak electricity demand. Local authoritiesare committed in contributing to national goals on CO2 emission reductions by improving energyefficiency and investing in local renewable electricity generation, while considering their ownobjectives for economic development, increased energy self-sufficiency, and affordable energy costs.This paper formulates a multi-objective optimization problem about these goals that is solved byinterfacing the energy systems simulation tool EnergyPLAN with a multi-objective evolutionaryalgorithm implemented in Matlab. A sensitivity analysis on some key economic parameters is alsoperformed. In this way, optimal alternatives are identified for the integrated electricity and heatingsectors and valuable insights are offered to decision-makers in local authorities. Piteå (Norrbotten,Sweden) is used as a case study that is representative of Nordic municipalities, and results showthat CO2 emissions can be reduced by 60% without a considerable increase in total costs and thatpeak electricity import can be reduced by a maximum of 38%.

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  • 19.
    Forsberg, Jonas
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Krook-Riekkola, Anna
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Recoupling Climate Change and Air Quality: Exploring Low-Emission Options in Urban Transportation Using the TIMES-City Model2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 11, article id 3220Article in journal (Refereed)
    Abstract [en]

    Fossil fuels in transportation are a significant source of local emissions in and around cities; thus, decarbonising transportation can reduce both greenhouse gases (GHGs) and air pollutants (APs). However, the degree of these reductions depends on what replaces fossil fuels. Today, GHG and AP mitigation strategies are typically ‘decoupled’ as they have different motivations and responsibilities. This study investigates the ancillary benefits on (a) APs if the transport sector is decarbonised, and (b) GHGs if APs are drastically cut and (c) the possible co-benefits from targeting APs and GHGs in parallel, using an energy-system optimisation model with a detailed and consistent representation of technology and fuel choices. While biofuels are the most cost-efficient option for meeting ambitious climate-change-mitigation targets, they have a very limited effect on reducing APs. Single-handed deep cuts in APs require a shift to zero-emission battery electric and hydrogen fuel cell vehicles (BEVs, HFCVs), which can result in significant upstream GHG emissions from electricity and hydrogen production. BEVs powered by ‘green’ electricity are identified as the most cost-efficient option for substantially cutting both GHGs and APs. A firm understanding of these empirical relationships is needed to support comprehensive mitigation strategies that tackle the range of sustainability challenges facing cities.

  • 20.
    Gantasala, Sudhakar
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Luneno, Jean-Claude
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Aidanpää, Jan-Olov
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Influence of Icing on the Modal Behavior of Wind Turbine Blades2016In: Energies, E-ISSN 1996-1073, Vol. 9, no 11, article id 862Article in journal (Refereed)
    Abstract [en]

    Wind turbines installed in cold climate sites accumulate ice on their structures. Icing of the rotor blades reduces turbine power output and increases loads, vibrations, noise, and safety risks due to the potential ice throw. Ice accumulation increases the mass distribution of the blade, while changes in the aerofoil shapes affect its aerodynamic behavior. Thus, the structural and aerodynamic changes due to icing affect the modal behavior of wind turbine blades. In this study, aeroelastic equations of the wind turbine blade vibrations are derived to analyze modal behavior of the Tjaereborg 2 MW wind turbine blade with ice. Structural vibrations of the blade are coupled with a Beddoes-Leishman unsteady attached flow aerodynamics model and the resulting aeroelastic equations are analyzed using the finite element method (FEM). A linearly increasing ice mass distribution is considered from the blade root to half-length and thereafter constant ice mass distribution to the blade tip, as defined by Germanischer Lloyd (GL) for the certification of wind turbines. Both structural and aerodynamic properties of the iced blades are evaluated and used to determine their influence on aeroelastic natural frequencies and damping factors. Blade natural frequencies reduce with ice mass and the amount of reduction in frequencies depends on how the ice mass is distributed along the blade length; but the reduction in damping factors depends on the ice shape. The variations in the natural frequencies of the iced blades with wind velocities are negligible; however, the damping factors change with wind velocity and become negative at some wind velocities. This study shows that the aerodynamic changes in the iced blade can cause violent vibrations within the operating wind velocity range of this turbine.

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  • 21.
    Gantasala, Sudhakar
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Luneno, Jean-Claude
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Aidanpää, Jan-Olov
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Investigating How an Artificial Neural Network Model Can Be Used to Detect Added Mass on a Non-Rotating Beam Using Its Natural Frequencies: A Possible Application for Wind Turbine Blade Ice Detection2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 2, article id 184Article in journal (Refereed)
    Abstract [en]

    Structures vibrate with their natural frequencies when disturbed from their equilibrium position. These frequencies reduce when an additional mass accumulates on their structures, like ice accumulation on wind turbines installed in cold climate sites. The added mass has two features: the location and quantity of mass. Natural frequencies of the structure reduce differently depending on these two features of the added mass. In this work, a technique based on an artificial neural network (ANN) model is proposed to identify added mass by training the neural network with a dataset of natural frequencies of the structure calculated using different quantities of the added mass at different locations on the structure. The proposed method is demonstrated on a non-rotating beam model fixed at one end. The length of the beam is divided into three zones in which different added masses are considered, and its natural frequencies are calculated using a finite element model of the beam. ANN is trained with this dataset of natural frequencies of the beam as an input and corresponding added masses used in the calculations as an output. ANN approximates the non-linear relationship between these inputs and outputs. An experimental setup of the cantilever beam is fabricated, and experimental modal analysis is carried out considering a few added masses on the beam. The frequencies estimated in the experiments are given as an input to the trained ANN model, and the identified masses are compared against the actual masses used in the experiments. These masses are identified with an error that varies with the location and the quantity of added mass. The reason for these errors can be attributed to the unaccounted stiffness variation in the beam model due to the added mass while generating the dataset for training the neural network. Therefore, the added masses are roughly estimated. At the end of the paper, an application of the current technique for detecting ice mass on a wind turbine blade is studied. A neural network model is designed and trained with a dataset of natural frequencies calculated using the finite element model of the blade considering different ice masses. The trained network model is tested to identify ice masses in four test cases that considers random mass distributions along the blade. The neural network model is able to roughly estimate ice masses, and the error reduces with increasing ice mass on the blade.

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  • 22.
    Gantasala, Sudhakar
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Tabatabaei, Narges
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Cervantes, Michel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Aidanpää, Jan-Olov
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Product and Production Development.
    Numerical Investigation of the Aeroelastic Behavior of a Wind Turbine with Iced Blades2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 12, article id 2422Article in journal (Refereed)
    Abstract [en]

    Wind turbines installed in cold-climate regions are prone to the risks of ice accumulation which affects their aeroelastic behavior. The studies carried out on this topic so far considered icing in a few sections of the blade, mostly located in the outer part of the blade, and their influence on the loads and power production of the turbine are only analyzed. The knowledge about the influence of icing in different locations of the blade and asymmetrical icing of the blades on loads, power, and vibration behavior of the turbine is still not matured. To improve this knowledge, multiple simulation cases are needed to run with different ice accumulations on the blade considering structural and aerodynamic property changes due to ice. Such simulations can be easily run by automating the ice shape creation on aerofoil sections and two-dimensional (2-D) Computational Fluid Dynamics (CFD) analysis of those sections. The current work proposes such methodology and it is illustrated on the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine model. The influence of symmetrical icing in different locations of the blade and asymmetrical icing of the blade assembly is analyzed on the turbine’s dynamic behavior using the aeroelastic computer-aided engineering tool FAST. The outer third of the blade produces about 50% of the turbine’s total power and severe icing in this part of the blade reduces power output and aeroelastic damping of the blade’s flapwise vibration modes. The increase in blade mass due to ice reduces its natural frequencies which can be extracted from the vibration responses of the turbine operating under turbulent wind conditions. Symmetrical icing of the blades reduces loads acting on the turbine components, whereas asymmetrical icing of the blades induces loads and vibrations in the tower, hub, and nacelle assembly at a frequency synchronous to rotational speed of the turbine.

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  • 23.
    Giovanelli, Christian
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University.
    Ryutaro, Ichise
    National Institute of Informatics, Tokyo .
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University.
    Exploiting Artificial Neural Networks for the Prediction of Ancillary Energy Market Prices2018In: Energies, E-ISSN 1996-1073, Vol. 115, no 7, article id 1906Article in journal (Refereed)
    Abstract [en]

    The increase of distributed energy resources in the smart grid calls for new ways to profitably exploit these resources, which can participate in day-ahead ancillary energy markets by providing flexibility. Higher profits are available for resource owners that are able to anticipate price peaks and hours of low prices or zero prices, as well as to control the resource in such a way that exploits the price fluctuations. Thus, this study presents a solution in which artificial neural networks are exploited to predict the day-ahead ancillary energy market prices. The study employs the frequency containment reserve for the normal operations market as a case study and presents the methodology utilized for the prediction of the case study ancillary market prices. The relevant data sources for predicting the market prices are identified, then the frequency containment reserve market prices are analyzed and compared with the spot market prices. In addition, the methodology describes the choices behind the definition of the model validation method and the performance evaluation coefficient utilized in the study. Moreover, the empirical processes for designing an artificial neural network model are presented. The performance of the artificial neural network model is evaluated in detail by means of several experiments, showing robustness and adaptiveness to the fast-changing price behaviors. Finally, the developed artificial neural network model is shown to have better performance than two state of the art models, support vector regression and ARIMA, respectively

  • 24.
    Havilah, Pulla Rose
    et al.
    Department of Chemical Engineering, School of Engineering, University of Petroleum and Energy Studies, Energy Acres Building, Bidholi, Dehradun 248007, India.
    Sharma, Amit Kumar
    Department of Chemistry, Centre for Alternate and Renewable Energy Research, R & D, University of Petroleum and Energy Studies (UPES), Energy Acres Building, Bidholi, Dehradun 248007, India.
    Govindasamy, Gopalakrishnan
    Department of Chemical Engineering, School of Engineering, University of Petroleum and Energy Studies, Energy Acres Building, Bidholi, Dehradun 248007, India.
    Matsakas, Leonidas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Patel, Alok
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Biomass Gasification in Downdraft Gasifiers: A Technical Review on Production, Up-Gradation and Application of Synthesis Gas2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 11, article id 3938Article, review/survey (Refereed)
    Abstract [en]

    Rapid climate change and forecasted damage from fossil fuel combustion, forced researchers to investigate renewable and clean energy sources for the sustainable development of societies throughout the world. Biomass-based energy is one of the most important renewable energy sources for meeting daily energy needs, which are gaining in popularity daily. Gasification-based bioenergy production is an effective way to replace fossil fuels and reduce CO2 emissions. Even though biomass gasification has been studied extensively, there is still much opportunity for improvement in terms of high-quality syngas generation (high H2/CO ratio) and reduced tar formation. Furthermore, the presence of tar has a considerable impact on syngas quality. Downdraft gasifiers have recently shown a significant potential for producing high-quality syngas with lower tar concentrations. This article presents a comprehensive review on the advancement in biomass downdraft gasification technologies for high-quality synthesis gas. In addition, factors affecting syngas production and composition e.g., equivalency ratio, temperature, particle size, and gasification medium on synthesis gas generation are also comprehensively studied. The up-gradation and various applications of synthesis gas are also discussed in brief in this review article.

  • 25.
    Hiller, Sandro
    et al.
    Research Centre Energy, Vorarlberg University of Applied Sciences, Dornbirn, 6850, Austria.
    Hartmann, Christian
    Research Centre Energy, Vorarlberg University of Applied Sciences, Dornbirn, 6850, Austria.
    Hebenstreit, Babette
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science. Research Centre Energy, Vorarlberg University of Applied Sciences, Dornbirn, 6850, Austria.
    Arzbacher, Stefan
    Research Centre Energy, Vorarlberg University of Applied Sciences, Dornbirn, 6850, Austria.
    Solidified-Air Energy Storage: Conceptualization and Thermodynamic Analysis2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 6, article id 2159Article in journal (Refereed)
    Abstract [en]

    Grid-scale electrical energy storage (EES) is a key component in cost-effective transition scenarios to renewable energy sources. The requirement of scalability favors EES approaches such as pumped-storage hydroelectricity (PSH) or compressed-air energy storage (CAES), which utilize the cheap and abundant storage materials water and air, respectively. To overcome the site restriction and low volumetric energy densities attributed to PSH and CAES, liquid-air energy storage (LAES) has been devised; however, it suffers from a rather small round-trip efficiency (RTE) and challenging storage conditions. Aiming to overcome these drawbacks, a novel system for EES is developed using solidified air (i.e., clathrate hydrate of air) as the storable phase of air. A reference plant for solidified-air energy storage (SAES) is conceptualized and modeled thermodynamically using the software CoolProp for water and air as well as empirical data and first-order approximations for the solidified air (SA). The reference plant exhibits a RTE of 52% and a volumetric storage density of 47 kWh per m3 of SA. While this energy density relates to only one half of that in LAES plants, the modeled RTE of SAES is comparable already. Since improved thermal management and the use of thermodynamic promoters can further increase the RTEs in SAES, the technical potential of SAES is in place already. Yet, for a successful implementation of the concept—in addition to economic aspects—questions regarding the stability of SA must be first clarified and challenges related to the processing of SA resolved.

  • 26.
    Hou, Muzhou
    et al.
    School of Mathematics and Statistics, Central South University, Changsha, Hunan, China.
    Zhang, Tianle
    School of Mathematics and Statistics, Central South University, Changsha, Hunan, China.
    Weng, Futian
    School of Mathematics and Statistics, Central South University, Changsha, Hunan, China.
    Ali, Mumtaz
    School of Agricultural, Computational and Environmental Sciences Institute of Agriculture and Environment, University of Southern Queensland, Springfield, Australia.
    Al-Ansari, Nadhir
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
    Yaseen, Zaher Mundher
    Sustainable Developments in Civil Engineering Research Group, Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
    Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model2018In: Energies, E-ISSN 1996-1073, Vol. 11, no 12, article id 3415Article in journal (Refereed)
    Abstract [en]

    Accurate global solar radiation prediction is highly essential for related research on renewable energy sources. The cost implication and measurement expertise of global solar radiation

    emphasize that intelligence prediction models need to be applied. On the basis of long-term measured daily solar radiation data, this study uses a novel regularized online sequential extreme learning machine, integrated with variable forgetting factor (FOS-ELM), to predict global solar radiation at Bur Dedougou, in the Burkina Faso region. Bayesian Information Criterion (BIC) is applied to build the seven input combinations based on speed (Wspeed), maximum and minimum temperature (Tmax and Tmin), maximum and minimum humidity (Hmax and Hmin), evaporation (Eo) and vapor pressure deficiency (VPD). For the difference input parameters magnitudes, seven models were developed and evaluated for the optimal input combination. Various statistical indicators were computed for the prediction accuracy examination. The experimental results of the applied FOS-ELM model demonstrated a reliable prediction accuracy against the classical extreme learning machine (ELM) model for daily global solar radiation simulation. In fact, compared to classical ELM, the FOS-ELM model reported an enhancement in the root mean square error (RMSE) and mean absolute error(MAE) by (68.8–79.8%). In summary, the results clearly confirm the effectiveness of the FOS-ELM model, owing to the fixed internal tuning parameters.

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  • 27.
    Iovanel, Raluca Gabriela
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Dehkharqani, Arash Soltani
    R&D Engineer, Svenska Rotor Maskiner, Svarvarvägen 2, 132 38 Saltsjö-Boo, Sweden.
    Bucur, Diana Maria
    Department of Hydraulics, Hydraulic Equipment and Environmental Engineering, Politehnica University of Bucharest, 060042 Bucharest, Romania.
    Cervantes, Michel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Numerical Simulation and Experimental Validation of a Kaplan Prototype Turbine Operating on a Cam Curve2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 11, article id 4121Article in journal (Refereed)
    Abstract [en]

    The role of hydropower has become increasingly essential following the introduction of intermittent renewable energies. Quickly regulating power is needed, and the transient operations of hydropower plants have consequently become more frequent. Large pressure fluctuations occur during transient operations, leading to the premature fatigue and wear of hydraulic turbines. Investigations of the transient flow phenomena developed in small-scale turbine models are useful and accessible but limited. On the other hand, experimental and numerical studies of full-scale large turbines are challenging due to production losses, large scales, high Reynolds numbers, and computational demands. In the present work, the operation of a 10 MW Kaplan prototype turbine was modelled for two operating points on a propeller curve corresponding to the best efficiency point and part-load conditions. First, an analysis of the possible means of reducing the model complexity is presented. The influence of the boundary conditions, runner blade clearance, blade geometry and mesh size on the numerical results is discussed. Secondly, the results of the numerical simulations are presented and compared to experimental measurements performed on the prototype in order to validate the numerical model. The mean torque and pressure values were reasonably predicted at both operating points with the simplified model. An analysis of the pressure fluctuations at part load demonstrated that the numerical simulation captured the rotating vortex rope developed in the draft tube. The frequencies of the rotating and plunging components of the rotating vortex were accurately captured, but the amplitudes were underestimated compared to the experimental data.

  • 28.
    Iovanel, Raluca Gabriela
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Dehkharqani, Arash Soltani
    R&D Engineer, Svenska Rotor Maskiner, Svarvarvägen 2, 132 38 Saltsjö-boo, Sweden.
    Cervantes, Michel Jose
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Numerical Simulation of a Kaplan Prototype during Speed-No-Load Operation2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 14, article id 5072Article in journal (Refereed)
    Abstract [en]

    Hydropower plants often work in off-design conditions to regulate the power grid frequency. Frequent transient operation of hydraulic turbines leads to premature failure, fatigue and damage to the turbine components. The speed-no-load (SNL) operating condition is the last part of the start-up cycle and one of the most damaging operation conditions of hydraulic turbines. Hydraulic instabilities and high-stress pressure fluctuations occur due to the low flow rate and unsteady load on the runner blades. Numerical simulations can provide useful insight concerning the complex flow structures that develop inside hydraulic turbines during SNL operation. Together with experimental investigations, the numerical simulations can help diagnose failures and optimize the exploitation of hydraulic turbines. This paper introduces the numerical model of a full-scale 10 MW Kaplan turbine prototype operated at SNL. The geometry was obtained by scaling the geometry of the corresponding model turbine as the model and prototype are geometrically similar. The numerical model is simplified and designed to optimize the numerical precision and computational costs. The guide vane and runner domains are asymmetrical, the epoxy layer applied to two runner blades during the experimental measurements is not modelled and a constant runner blade clearance is employed. The unsteady simulation was performed using the SAS-SST turbulence model. The numerical results were validated with torque and pressure experimental data. The mean quantities obtained from the numerical simulation were in good agreement with the experiment. The mean pressure values were better captured on the pressure side of the runner blade compared to the suction side. However, the amplitude of the pressure fluctuations was more accurately predicted on the suction side of the runner blade. The amplitude of the torque fluctuations was considerably underestimated.

  • 29.
    Iovanel, Raluca Gabriela
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Dunca, Georgiana
    Department of Hydraulics, Hydraulic Equipment and Environmental Engineering, Politehnica University of Bucharest, Bucharest, Romania.
    Bucur, Diana M.
    Department of Hydraulics, Hydraulic Equipment and Environmental Engineering, Politehnica University of Bucharest, Bucharest, Romania.
    Cervantes, Michel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Numerical Simulation of the Flow in a Kaplan Turbine Model during Transient Operation from the Best Efficiency Point to Part Load2020In: Energies, E-ISSN 1996-1073, Vol. 13, no 12, article id 3129Article in journal (Refereed)
    Abstract [en]

    The aim of this study is to develop a reliable numerical model that provides additional information to experimental measurements and contributes to a better exploitation of hydraulic turbines during transient operation. The paper presents a numerical analysis of the flow inside a Kaplan turbine model operated at a fixed runner blade angle during load variation from the best efficiency point (BEP) to part load (PL) operation. A mesh displacement is defined in order to model the closure of the guide vanes. Two different types of inlet boundary conditions are tested for the transient numerical simulations: linear flow rate variation (InletFlow) and constant total pressure (InletTotalPressure). A time step analysis is performed and the influence of the time discretization over the fluctuating quantities is discussed. Velocity measurements at the corresponding operating points are available to validate the simulation. Spectrogram plots of the pressure signals show the times of appearance of the plunging and rotating modes of the rotating vortex rope (RVR) and the stagnation region developed around the centerline of the draft tube is captured.

  • 30.
    Islam, Raihan Ul
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Ruci, Xhesika
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Hossain, Mohammad Shahadat
    Department of Computer Science and Engineering, University of Chittagong, Chittagong, Bangladesh.
    Andersson, Karl
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Kor, Ah-Lian
    School of Computing, Creative Technologies and Engineering Leeds Beckett University, Leeds, UK.
    Capacity Management of Hyperscale Data Centers Using Predictive Modelling2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 18, article id 3438Article in journal (Refereed)
    Abstract [en]

    Big Data applications have become increasingly popular with the emergence of cloud computing and the explosion of artificial intelligence. The increasing adoption of data-intensive machines and services is driving the need for more power to keep the data centers of the world running. It has become crucial for large IT companies to monitor the energy efficiency of their data-center facilities and to take actions on the optimization of these heavy electricity consumers. This paper proposes a Belief Rule-Based Expert System (BRBES)-based predictive model to predict the Power Usage Effectiveness (PUE) of a data center. The uniqueness of this model consists of the integration of a novel learning mechanism consisting of parameter and structure optimization by using BRBES-based adaptive Differential Evolution (BRBaDE), significantly improving the accuracy of PUE prediction. This model has been evaluated by using real-world data collected from a Facebook data center located in Luleå, Sweden. In addition, to prove the robustness of the predictive model, it has been compared with other machine learning techniques, such as an Artificial Neural Network (ANN) and an Adaptive Neuro Fuzzy Inference System (ANFIS), where it showed a better result. Further, due to the flexibility of the BRBES-based predictive model, it can be used to capture the nonlinear dependencies of many variables of a data center, allowing the prediction of PUE with much accuracy. Consequently, this plays an important role to make data centers more energy-efficient.

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  • 31.
    Jassim, Hassanean S. H.
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Industrilized and sustainable construction.
    Lu, Weizhuo
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Industrilized and sustainable construction.
    Olofsson, Thomas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Industrilized and sustainable construction.
    A Practical Method for Assessing the Energy Consumption and CO2 Emissions of Mass Haulers2016In: Energies, E-ISSN 1996-1073, Vol. 9, no 10, article id 802Article in journal (Refereed)
    Abstract [en]

    Mass hauling operations play central roles in construction projects. They typically use many haulers that consume large amounts of energy and emit significant quantities of CO2. However, practical methods for estimating the energy consumption and CO2 emissions of such operations during the project planning stage are scarce, while most of the previous methods focus on construction stage or after the construction stages which limited the practical adoption of reduction strategy in the early planning phase. This paper presents a detailed model for estimating the energy consumption and CO2 emissions of mass haulers that integrates the mass hauling plan with a set of predictive equations. The mass hauling plan is generated using a planning program such as DynaRoad in conjunction with data on the productivity of selected haulers and the amount of material to be hauled during cutting, filling, borrowing, and disposal operations. This plan is then used as input for estimating the energy consumption and CO2 emissions of the selected hauling fleet. The proposed model will help planners to assess the energy and environmental performance of mass hauling plans, and to select hauler and fleet configurations that will minimize these quantities. The model was applied in a case study, demonstrating that it can reliably predict energy consumption, CO2 emissions, and hauler productivity as functions of the hauling distance for individual haulers and entire hauling fleets.

  • 32.
    Jaunky, Vishal Chandr
    et al.
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Lundmark, Robert
    Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Social Sciences.
    Are Shocks to Wood Fuel Production Permanent? Evidence from the EU2015In: Energies, E-ISSN 1996-1073, Vol. 8, no 11, p. 12718-12728Article in journal (Refereed)
    Abstract [en]

    This paper investigates whether shocks (economic effects) to wood fuel production for 18 countries of the European Union (EU) over the period 1961–2012 are temporary or persistent. A variety of time-series and panel data unit root tests are employed. The presence of structural breaks is taken into account when performing those tests. Wood production in approximately 78% of the countries is found to follow a non-stationary process supported by the result that most of the panel unit root tests also point towards a non-stationary process. This indicates that the economic effect will tend to be persistent and suggests that policies affecting wood fuel production, implicitly or explicitly, will have enduring effects. For instance, forest conservation policies will persistently reduce the wood fuel production level.

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  • 33.
    Joy, Jesline
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Raisee, Mehrdad
    Hydraulic Machinery Research Institute, School of Mechanical Engineering, University of Tehran, Tehran 1417935840, Iran.
    Cervantes, Michel
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Hydraulic Performance of a Francis Turbine with a Variable Draft Tube Guide Vane System to Mitigate Pressure Pulsations2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 18, article id 6542Article in journal (Refereed)
    Abstract [en]

    The present paper demonstrates a proof-of-concept by introducing a variable guide vane system in the draft tube of a high-head Francis model turbine. The aim is to examine the hydraulic performance of the turbine while mitigating the pressure pulsations in the draft tube. The guide vanes can rotate about an axis up to ±45°. The pressure pulsations mitigation studies were performed at lower- and upper-part loads. The hydraulic performance was examined at all operating ranges within the turbine head. There were six guide vane configurations considered between ±45°. The findings demonstrate that the highest efficiency loss with a guide vane configuration that mitigates the pressure pulsations is marginal, with modest improvements at the best efficiency point. The pressure pulsations are 100% mitigated at the lower part load, and there is a maximum decrement in the pressure pulsations up to 80% at the upper part load. The study demonstrates that such a system can improve the operational flexibility of the hydro-turbine by mitigating the pressure pulsations and marginally affecting its hydraulic performance.

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  • 34.
    Kahawala, Sachin
    et al.
    Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC 3083, Australia.
    De Silva, Daswin
    Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC 3083, Australia.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Alahakoon, Damminda
    Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC 3083, Australia.
    Nawaratne, Rashmika
    Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC 3083, Australia.
    Osipov, Evgeny
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Jennings, Andrew
    Centre for Data Analytics and Cognition, La Trobe University, Bundoora, VIC 3083, Australia.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Robust Multi-Step Predictor for Electricity Markets with Real-Time Pricing2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 14, article id 4378Article in journal (Refereed)
    Abstract [en]

    Real-time electricity pricing mechanisms are emerging as a key component of the smart grid. However, prior work has not fully addressed the challenges of multi-step prediction (Predicting multiple time steps into the future) that is accurate, robust and real-time. This paper proposes a novel Artificial Intelligence-based approach, Robust Intelligent Price Prediction in Real-time (RIPPR), that overcomes these challenges. RIPPR utilizes Variational Mode Decomposition (VMD) to transform the spot price data stream into sub-series that are optimized for robustness using the particle swarm optimization (PSO) algorithm. These sub-series are inputted to a Random Vector Functional Link neural network algorithm for real-time multi-step prediction. A mirror extension removal of VMD, including continuous and discrete spaces in the PSO, is a further novel contribution that improves the effectiveness of RIPPR. The superiority of the proposed RIPPR is demonstrated using three empirical studies of multi-step price prediction of the Australian electricity market.

  • 35.
    Kalogiannis, Konstantinos G.
    et al.
    Chemical Process and Energy Resources Institute (CPERI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece.
    Matsakas, Leonidas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Lappas, Angelos A.
    Chemical Process and Energy Resources Institute (CPERI), Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Aromatics from Beechwood Organosolv Lignin through Thermal and Catalytic Pyrolysis2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 9, article id 1606Article in journal (Refereed)
    Abstract [en]

    Biomass fractionation, as an alternative to biomass pretreatment, has gained increasing research attention over the past few years as it provides separate streams of cellulose, hemicellulose, and lignin. These streams can be used separately and can provide a solution for improving the economics of emerging biorefinery technologies. The sugar streams are commonly used in microbial conversions, whereas during recent years lignin has been recognized as a valuable compound as it is the only renewable and abundant source of aromatic chemicals. Successfully converting lignin into valuable chemicals and products is key in achieving both environmental and economic sustainability of future biorefineries. In this work, lignin retrieved from beechwood sawdust delignification pretreatment via an organosolv process was depolymerized with thermal and catalytic pyrolysis. ZSM-5 commercial catalyst was used in situ to upgrade the lignin bio-oil vapors. Lignins retrieved from different modes of organosolv pretreatment were tested in order to evaluate the effect that upstream pretreatment has on the lignin fraction. Both thermal and catalytic pyrolysis yielded oils rich in phenols and aromatic hydrocarbons. Use of ZSM-5 catalyst assisted in overall deoxygenation of the bio-oils and enhanced aromatic hydrocarbons production. The oxygen content of the bio-oils was reduced at the expense of their yield. Organosolv lignins were successfully depolymerized towards phenols and aromatic hydrocarbons via thermal and catalytic pyrolysis. Hence, lignin pyrolysis can be an effective manner for lignin upgrading towards high added value products

  • 36.
    Karhula, Niko
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland; International Research Laboratory of Computer Technologies, ITMO University, 197101 St. Petersburg, Russia .
    Validating the Real-Time Performance of Distributed Energy Resources Participating on Primary Frequency Reserves2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 21Article in journal (Refereed)
    Abstract [en]

    A significant body of research has emerged for adapting diverse intelligent distributed energy resources to provide primary frequency reserves (PFR). However, such works are usually vague about the technical specifications for PFR. Industrial practitioners designing systems for PFR markets must pre-qualify their PFR resources against the specifications of the market operator, which is usually a transmission system operator (TSO) or independent system operator (ISO). TSO and ISO requirements for PFR have been underspecified with respect to real-time performance, but as fossil-fuel based PFR is being replaced by various distributed energy resources, these requirements are being tightened. The TSOs of Denmark, Finland, Norway, and Sweden have recently released a joint pilot phase specification with novel requirements on the dynamic performance of PFR resources. This paper presents an automated procedure for performing the pre-qualification procedure against this specification. The procedure is generic and has been demonstrated with a testbed of light emitting diode (LED) lights. The implications of low bandwidth Internet of Things communications, as well as the need to avoid abrupt control actions that irritate human users, have been investigated in the automated procedure.

  • 37.
    Khalil, Ashraf
    et al.
    DTU Engineering Technology, Technical University of Denmark, DK-2750 Kongens Lyngby, Denmark.
    Laila, Dina Shona
    Electrical & Electronic Engineering Department, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei.
    An Accurate Method for Computing the Delay Margin in Load Frequency Control System with Gain and Phase Margins2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 9, article id 3434Article in journal (Refereed)
  • 38.
    Kovacevic-Badstuebne, Ivana
    et al.
    Advanced Power Semiconductor Laboratory, ETH Zurich, Zurich, 8092, Switzerland.
    Romano, Daniele
    UAq EMC Laboratory, Università degli Studi dell’Aquila, L’Aquila, 67100, Italy.
    Antonini, Giulio
    UAq EMC Laboratory, Università degli Studi dell’Aquila, L’Aquila, 67100, Italy.
    Ekman, Jonas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Grossner, Ulrike
    Advanced Power Semiconductor Laboratory, ETH Zurich, Zurich, 8092, Switzerland.
    Broadband Circuit-Oriented Electromagnetic Modeling for Power Electronics: 3-D PEEC Solver vs. RLCG-Solver2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 10, article id 2835Article in journal (Refereed)
    Abstract [en]

    Broadband electromagnetic (EM) modeling increases in importance for virtual prototyping of advanced power electronics systems (PES), enabling a more accurate prediction of fast switching converter operation and its impact on energy conversion efficiency and EM interference. With the aim to predict and reduce an adverse impact of parasitics on the dynamic performance of fast switching power semiconductor devices, the circuit-oriented EM modeling based on the extraction of equivalent lumped R-L-C-G circuits is frequently selected over the Finite Element Method (FEM)-based EM modeling, mainly due to its lower computational complexity. With requirements for more accurate virtual prototyping of fast-switching PES, the modeling accuracy of the equivalent-RLCG-circuit-based EM modeling has to be re-evaluated. In the literature, the equivalent-RLCG-circuit-based EM techniques are frequently misinterpreted as the quasi-static (QS) 3-D Partial Element Equivalent Circuit (PEEC) method, and the observed inaccuracies of modeling HF effects are attributed to the QS field assumption. This paper presents a comprehensive analysis on the differences between the QS 3-D PEEC-based and the equivalent-RLCG-circuit-based EM modeling for simulating the dynamics of fast switching power devices. Using two modeling examples of fast switching power MOSFETs, a 3-D PEEC solver developed in-house and the well-known equivalent-RLCG-circuit-based EM modeling tool, ANSYS Q3D, are compared to the full-wave 3-D FEM-based EM tool, ANSYS HFSS. It is shown that the QS 3-D PEEC method can model the fast switching transients more accurately than Q3D. Accordingly, the accuracy of equivalent-RLCG-circuit-based modeling approaches in the HF range is rather related to the approximations made on modeling electric-field induced effects than to the QS field assumption.

  • 39.
    Lazzaretto, Andrea
    et al.
    Department of Industrial Engineering, University of Padova, Padova, Italy.
    Toffolo, Andrea
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Optimum choice of energy system configuration and storages for a proper match between energy conversion and demands2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 20, article id 3957Article in journal (Refereed)
    Abstract [en]

    This Special Issue addresses the general problem of a proper match between the demands of energy users and the units for energy conversion and storage, by means of proper design and operation of the overall energy system configuration. The focus is either on systems including single plants or groups of plants, connected or not to one or more energy distribution networks. In both cases, the optimum design and operation involve decisions about thermodynamic processes, about the type, number, design parameters of components/plants, and storage capacities, and about mutual interconnections and the interconnections with the distribution grids. The problem is very wide, can be tackled with different methodologies and may have several, more or less valuable and complicated solutions. The twelve accepted papers certainly represent a good contribution to perceive its difficulty.

  • 40.
    Lennerhag, Oscar
    et al.
    Independent Insulation Group Sweden AB, Ludvika, Sweden.
    Lundquist, Jan
    Independent Insulation Group Sweden AB, Ludvika, Sweden.
    Engelbrecht, Christiaan
    Engelbrecht Consulting B.V., The Netherlands.
    Karmokar, Tanumay
    NKT HV Cables AB, Lyckeby, Sweden.
    Bollen, Math
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    An Improved Statistical Method for Calculating Lightning Overvoltages in HVDC Overhead Line/Cable Systems2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 16, article id 3121Article in journal (Refereed)
    Abstract [en]

    HVDC cable systems connected to HVDC overhead lines are subject to fast front overvoltages emanating from the line when lightning strikes a shield wire (backflashover) or a pole conductor (shielding failure). Representative fast front overvoltage levels for HVDC cable systems are usually established without considering their statistical characteristics. A statistical method to determine overvoltages related to the acceptable mean time between failure (MTBF) for the cable system was developed previously. The method accounts for the statistical distribution of lightning current magnitudes as well as the attenuation of the overvoltage wave due to corona discharges on the line, since this effect dominates for system voltages up to about ±320 kV. To make the method suitable for higher system voltages as well, this article introduces an improved statistical method which also accounts for surge attenuation through resistive effects, soil ionization, and statistical treatment of overvoltages due to shielding failures. To illustrate the improved method, it is applied to a case study for a ±525 kV DC line. 

  • 41.
    Matsakas, Leonidas
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Nitsos, Christos
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Vörös, Dimitrij
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    High-Titer Methane from Organosolv-Pretreated Spruce and Birch2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 3, article id 263Article in journal (Refereed)
    Abstract [en]

    The negative impact of fossil fuels and the increased demand for renewable energy sources has led to the use of novel raw material sources. Lignocellulosic biomass could serve as a possible raw material for anaerobic digestion and production of biogas. This work is aimed at using forest biomass, both softwood (spruce) and hardwood (birch), as a raw material for anaerobic digestion. We examined the effect of different operational conditions for the organosolv pretreatment (ethanol content, duration of treatment, and addition of acid catalyst) on the methane yield. In addition, we investigated the effect of addition of cellulolytic enzymes during the digestion. We found that inclusion of an acid catalyst during organosolv pretreatment improved the yields from spruce, but it did not affect the yields from birch. Shorter duration of treatment was advantageous with both materials. Methane yields from spruce were higher with lower ethanol content whereas higher ethanol content was more beneficial for birch. The highest yields obtained were 185 mL CH4/g VS from spruce and 259.9 mL CH4/g VS from birch. Addition of cellulolytic enzymes improved these yields to 266.6 mL CH4/g VS and 284.2 mL CH4/g VS, respectively.

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  • 42.
    Mesfun, Sennai
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Anderson, Jan-Olof
    Process Energy Engineering, Solvina, SE-42130 Västra Frölunda.
    Umeki, Kentaro
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Toffolo, Andrea
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Integrated SNG Production in a Typical Nordic Sawmill2016In: Energies, E-ISSN 1996-1073, Vol. 9, no 5, article id 333.Article in journal (Refereed)
    Abstract [en]

    Advanced biomass-based motor fuels and chemicals are becoming increasingly important to replace fossil energy sources within the coming decades. It is likely that the new biorefineries will evolve mainly from existing forest industry sites, as they already have the required biomass handling infrastructure in place. The main objective of this work is to assess the potential for increasing the profit margin from sawmill byproducts by integrating innovative downstream processes. The focus is on the techno-economic evaluation of an integrated site for biomass-based synthetic natural gas (bio-SNG) production. The option of using the syngas in a biomass-integrated gasification combined cycle (b-IGCC) for the production of electricity (instead of SNG) is also considered for comparison. The process flowsheets that are used to analyze the energy and material balances are modelled in MATLAB and Simulink. A mathematical process integration model of a typical Nordic sawmill is used to analyze the effects on the energy flows in the overall site, as well as to evaluate the site economics. Different plant sizes have been considered in order to assess the economy-of-scale effect. The technical data required as input are collected from the literature and, in some cases, from experiments. The investment cost is evaluated on the basis of conducted studies, third party supplier budget quotations and in-house database information. This paper presents complete material and energy balances of the considered processes and the resulting process economics. Results show that in order for the integrated SNG production to be favored, depending on the sawmill size, a biofuel subsidy in the order of 28–52 €/MWh SNG is required.

  • 43.
    Mesfun, Sennai
    et al.
    RISE Research Institutes of Sweden, P.O. Box 5604, 114 86 Stockholm, Sweden.
    Gustafsson, Gabriel
    Bioshare AB, 655 92 Karlstad, Sweden.
    Larsson, Anton
    Bioshare AB, 655 92 Karlstad, Sweden.
    Samavati, Mahrokh
    Department of Energy Technology, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden.
    Furusjö, Erik
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science. RISE Research Institutes of Sweden, P.O. Box 5604, 114 86 Stockholm, Sweden.
    Electrification of Biorefinery Concepts for Improved Productivity—Yield, Economic and GHG Performances2023In: Energies, E-ISSN 1996-1073, Vol. 16, no 21, article id 7436Article in journal (Refereed)
    Abstract [en]

    Demand for biofuels will likely increase, driven by intensifying obligations to decarbonize aviation and maritime sectors. Sustainable biomass is a finite resource, and the forest harvesting level is a topic of ongoing discussions, in relation to biodiversity preservation and the short-term role of forests as carbon sinks. State-of-the-art technologies for converting lignocellulosic feedstock into transportation biofuels achieves a carbon utilization rate ranging from 25% to 50%. Mature technologies like second-generation ethanol and gasification-based processes tend to fall toward the lower end of this spectrum. This study explores how electrification can enhance the carbon efficiency of biorefinery concepts and investigates its impact on energy, economics and greenhouse gas emissions. Results show that electrification increases carbon efficiency from 28% to 123% for gasification processes, from 28% to 45% for second-generation ethanol, and from 50% to 65% for direct liquefaction processes. Biofuels are produced to a cost range 60–140 EUR/MWh-biofuel, depending on the chosen technology pathway, feedstock and electricity prices. Notably, production in electrified biorefineries proves cost-competitive when compared to pure electrofuel (E-fuels) tracks. Depending on the selected technology pathway and the extent of electrification, a reduction in GHG emissions ranging from 75% to 98% is achievable, particularly when powered by a low-carbon electricity mix.

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  • 44.
    Mesfun, Sennai
    et al.
    RISE Research Institute of Sweden, Stockholm, Sweden.
    Matsakas, Leonidas
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Technoeconomic Assessment of Hybrid Organosolv–Steam Explosion Pretreatment of Woody Biomass2019In: Energies, E-ISSN 1996-1073, Vol. 2, no 21, article id 4206Article in journal (Refereed)
    Abstract [en]

    This study investigates technoeconomic performance of standalone biorefinery concepts that utilize hybrid organic solvent and steam explosion pretreatment technique. The assessments were made based on a mathematical process model developed in UniSim Design software using inhouse experimental data. The work was motivated by successful experimental applications of the hybrid pretreatment technique on lignocellulosic feedstocks that demonstrated high fractionation efficiency into a cellulose-rich, a hemicellulose-rich and lignin streams. For the biorefinery concepts studied here, the targeted final products were ethanol, organosolv lignin and hemicellulose syrup. Minimum ethanol selling price (MESP) and Internal rate of return (IRR) were evaluated as economic indicators of the investigated biorefinery concepts. Depending on the configuration, and allocating all costs to ethanol, MESP in the range 0.53–0.95 €/L were required for the biorefinery concepts to break even. Under the assumed ethanol reference price of 0.55 €/L, the corresponding IRR were found to be in the range −1.75–10.7%. Hemicellulose degradation and high steam demand identified as major sources of inefficiencies for the process and economic performance, respectively. Sensitivity of MESP and IRR towards the most influential technical, economic and market parameters performed.

  • 45.
    Mololoth, Vidya Krishnan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Saguna, Saguna
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Åhlund, Christer
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Blockchain and Machine Learning for Future Smart Grids: A Review2023In: Energies, E-ISSN 1996-1073, Vol. 16, no 1, article id 528Article, review/survey (Refereed)
    Abstract [en]

    Developments such as the increasing electrical energy demand, growth of renewable energy sources, cyber–physical security threats, increased penetration of electric vehicles (EVs), and unpredictable behavior of prosumers and EV users pose a range of challenges to the electric power system. To address these challenges, a decentralized system using blockchain technology and machine learning techniques for secure communication, distributed energy management and decentralized energy trading between prosumers is required. Blockchain enables secure distributed trust platforms, addresses optimization and reliability challenges, and allows P2P distributed energy exchange as well as flexibility services between customers. On the other hand, machine learning techniques enable intelligent smart grid operations by using prediction models and big data analysis. Motivated from these facts, in this review, we examine the potential of combining blockchain technology and machine learning techniques in the development of smart grid and investigate the benefits achieved by using both techniques for the future smart grid scenario. Further, we discuss research challenges and future research directions of applying blockchain and machine learning techniques for smart grids both individually as well as combining them together. The identified areas that require significant research are demand management in power grids, improving the security of grids with better consensus mechanisms, electric vehicle charging systems, scheduling of the entire grid system, designing secure microgrids, and the interconnection of different blockchain networks.

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  • 46.
    Moreno-Garcia, Isabel M.
    et al.
    University of Cordoba, Electronics and Electronic Technology Area, University of Cordoba.
    Moreno-Munoz, Antonio
    University of Cordoba, Electronics and Electronic Technology Area, University of Cordoba.
    Gil-de-Castro, Aurora
    University of Cordoba, Electronics and Electronic Technology Area, University of Cordoba.
    Bollen, Math
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Gu, Irene Y.H.
    Chalmers University of Technology.
    Novel technique for segmentation of measured three-phase voltage dips2015In: Energies, E-ISSN 1996-1073, Vol. 8, no 8, p. 8319-8338Article in journal (Refereed)
    Abstract [en]

    This paper focuses on issues arising from the need to automatically analyze disturbances in the future (smart) grid. Accurate time allocation of events and the sequences of events is an important part of such an analysis. The performance of a joint causal and anti-causal (CaC) segmentation method has been analyzed with a set of real measurement signals, using an alternative detection technique based on a cumulative sum (CUSUM) algorithm. The results show that the location in time of underlying transitions in the power system can be more accurately estimated by combining CaC segmentation methods.

  • 47.
    Nefedov, Evgeny
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University.
    Sierla, Seppo
    Department of Automation and Systems Technology, School of Electrical Engineering, Aalto University.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Automation and Systems Technology, School of Electrical Engineering, Aalto University.
    Internet of Energy Approach for Sustainable Use of Electric Vehicles as Energy Storage of Prosumer Buildings2018In: Energies, E-ISSN 1996-1073, Vol. 11, no 8, article id 2165Article in journal (Refereed)
    Abstract [en]

    Vehicle-to-building (V2B) technology permits bypassing the power grid in order to supply power to a building from electric vehicle (EV) batteries in the parking lot. This paper investigates the hypothesis stating that the increasing number of EVs on our roads can be also beneficial for making buildings sustainably greener on account of using V2B technology in conjunction with local photovoltaic (PV) generation. It is assumed that there is no local battery storage other than EVs and that the EV batteries are fully available for driving, so that the EVs batteries must be at the intended state of charge at the departure time announced by the EV driver. Our goal is to exploit the potential of the EV batteries capacity as much as possible in order to permit a large area of solar panels, so that even on sunny days all PV power can be used to supply the building needs or the EV charging at the parking lot. A system architecture and collaboration protocols that account for uncertainties in EV behaviour are proposed. The proposed approach is proven in simulation covering one year period for three locations in different climatic regions of the US, resulting in the electricity bill reductions of 15.8%, 9.1% and 4.9% for California, New Jersey and Alaska, respectively. These results are compared to state-of-the-art research in combining V2B with PV or wind power generation. It is concluded that the achieved electricity bill reductions are superior to the state-of-the-art, because previous work is based on problem formulations that exploit only a part of the potential EV battery capacity

  • 48.
    Nitsos, Christos
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Rova, Ulrika
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Christakopoulos, Paul
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Chemical Engineering.
    Organosolv fractionation of softwood biomass for biofuel and biorefinery applications2018In: Energies, E-ISSN 1996-1073, Vol. 11, no 1, article id 50Article in journal (Refereed)
    Abstract [en]

    Softwoods represent a significant fraction of the available lignocellulosic biomass for conversion into a variety of bio-based products. Its inherent recalcitrance, however, makes its successful utilization an ongoing challenge. In the current work the research efforts for the fractionation and utilization of softwood biomass with the organosolv process are reviewed. A short introduction into the specific challenges of softwood utilization, the development of the biorefinery concept, as well as the initial efforts for the development of organosolv as a pulping method is also provided for better understanding of the related research framework. The effect of organosolv pretreatment at various conditions, in the fractionation efficiency of wood components, enzymatic hydrolysis and bioethanol production yields is then discussed. Specific attention is given in the effect of the pretreated biomass properties such as residual lignin on enzymatic hydrolysis. Finally, the valorization of organosolv lignin via the production of biofuels, chemicals, and materials is also described. 

  • 49.
    Nömm, Jakob
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Rönnberg, Sarah
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Bollen, Math
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    An Analysis of Frequency Variations and its Implications on Connected Equipment for a Nanogrid during Islanded Operation2018In: Energies, E-ISSN 1996-1073, article id en11092456Article in journal (Refereed)
    Abstract [en]

    Frequency, voltage and reliability data have been collected in a nanogrid for 48 weeks during islanded operation. Frequency values from the 48 week measurements were analyzed and compared to relevant limits. During 19.5% of the 48 weeks, the nanogrid had curtailed the production due to insufficient consumption in islanded operation. The curtailment of production was also the main cause of the frequency variations above the limits. When the microgrid operated on stored battery power, the frequency variations were less than in the Swedish national grid. 39.4% of all the interruptions that occurred in the nanogrid are also indirectly caused by the curtailment of solar production. Possible solutions for mitigating the frequency variations and lowering the number of interruptions are also discussed.

  • 50.
    Nömm, Jakob
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Rönnberg, Sarah
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Bollen, Math
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    An analysis of voltage quality in a nanogrid during islanded operation2019In: Energies, E-ISSN 1996-1073, Vol. 12, no 4, article id 614Article in journal (Refereed)
    Abstract [en]

    Voltage quality data has been collected in a single house nanogrid during 48 weeks of islanded operation and 54 weeks of grid-connected operation. The voltage quality data contains the voltage total harmonic distortion (THD), odd harmonics 3 to 11 and 15, even harmonics 4 to 8, voltage unbalance, short-term flicker severity (Pst) and long-term flicker severity (Plt) values, and voltage variations at timescales below 10 min. A comparison between islanded and grid-connected operation values was made, were some of the parameters were compared to relevant grid standard limits. It is shown that some parameters exceed the defined limits in the grid-standards during islanded operation. It was also found that the islanded operation has two modes of operation, one in which higher values of the short circuit impedance, individual harmonic impedance, harmonic voltage distortion and voltage unbalance were reached.

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