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  • 1.
    Atif, Yacine
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Ding, Jianguo
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Lindström, Birgitta
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Jeusfeld, Manfred
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Andler, Sten F.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Yuning, Jiang
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Brax, Christoffer
    CombiTech AB, Skövde, Sweden.
    Gustavsson, Per M.
    CombiTech AB, Skövde, Sweden.
    Cyber-Threat Intelligence Architecture for Smart-Grid Critical Infrastructures Protection2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    Critical infrastructures (CIs) are becoming increasingly sophisticated with embedded cyber-physical systems (CPSs) that provide managerial automation and autonomic controls. Yet these advances expose CI components to new cyber-threats, leading to a chain of dysfunctionalities with catastrophic socio-economical implications. We propose a comprehensive architectural model to support the development of incident management tools that provide situation-awareness and cyber-threats intelligence for CI protection, with a special focus on smart-grid CI. The goal is to unleash forensic data from CPS-based CIs to perform some predictive analytics. In doing so, we use some AI (Artificial Intelligence) paradigms for both data collection, threat detection, and cascade-effects prediction. 

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  • 2.
    Ding, Jianguo
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi. Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden.
    Naserinia, Vahid
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Blockchain for future renewable energy2022Ingår i: Decentralized Frameworks for Future Power Systems: Operation, Planning and Control Perspectives / [ed] Mohsen Parsa Moghaddam; Reza Zamani; Hassan Haes Alhelou; Pierluigi Siano, Academic Press, 2022, s. 129-146Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    To better optimize and control the renewable energy system and its integration with traditional grid systems and other energy systems, corresponding technologies are needed to meet its growing practical application requirements: decentralized management and control, support for decentralized decision-making, fine-grained and timely data sharing, maintain data and business privacy, support fast and low-cost electricity market transactions, maintain the security and reliability of system operation data, and prevent malicious cyberattacks. Blockchain is based on core technologies such as distributed ledgers, asymmetric encryption, consensus mechanisms, and smart contracts and has some excellent features such as decentralization, openness, independence, security, and anonymity. These characteristics seem to meet the technical requirements of future renewable energy systems partially. This chapter will systematically review how blockchain technology can potentially solve the challenges with decentralized solutions for future renewable energy systems and show a guideline to implement blockchain-based corresponding applications for future renewable energy. 

  • 3.
    Ding, Jianguo
    et al.
    Blekinge Tekniska Högskola, Institutionen för datavetenskap.
    Tadesse Aklilu, Yohannes
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling.
    Blockchain for Smart Grid Operations, Control and Management2022Rapport (Övrigt vetenskapligt)
    Abstract [sv]

    Elproduktion, -distribution, -överföring och -förbrukning står inför pågående utmaningar som smart näthantering, kontroll och drift, som är ett resultat av hög energiefterfrågan, mångfald av energikällor och miljö- eller regelfrågor. För att bättre optimera och kontrollera det förnybara energisystemet och dess integration med traditionella nätsystem och andra energisystem, behövs motsvarande teknik för att möta dess växande praktiska tillämpningskrav: decentraliserad förvaltning och kontroll, stöd för decentraliserat beslutsfattande, finkornigt och aktuellt datadelning, upprätthålla data och affärsintegritet, stödja snabba och billiga elmarknadstransaktioner och upprätthålla säkerheten och tillförlitligheten för systemdriftsdata och förhindra skadliga cyberattacker. Blockkedja är baserad på kärnteknologier som distribuerade reskontra, asymmetrisk kryptering, konsensusmekanismer och smarta kontrakt och har några utmärkta funktioner som decentralisering, öppenhet, oberoende, säkerhet och anonymitet. Dessa egenskaper ska delvis uppfylla de tekniska kraven för framtida förnybara energisystem.

    Den här rapporten ger en omfattande översikt över blockkedjebaserade lösningar för smart näthantering, kontroll och drift. Rapporten jämför med relaterade recensioner och belyser utmaningarna inom förvaltning, kontroll och drift för ett blockkedjebaserat smart nät, såväl som framtida forskningsriktningar inom fem kategorier: samarbete mellan aktörer, dataanalys och hantering, kontroll av nätobalanser, decentralisering av nätförvaltning och drift, säkerhet och integritet.

    Rapporten går igenom hur blockkedjeteknik potentiellt kan lösa utmaningarna med decentraliserade lösningar för framtida förnybara energisystem. Som ett resultat diskuteras flera tillämpningar av blockkedja för förnybar energi såsom elektriska fordon, decentraliserade P2P-energitransaktioner, certifiering och handel med koldioxidutsläpp, fysisk informationssäkerhet, energiöverföring, Energi-to-X och Internet för Energi.

    En riktlinje för implementering av blockkedja till motsvarande tillämpningar för framtida förnybar energi presenteras också i denna rapport. Detta inkluderar olika blockkedja -systemarkitektur, dataflöde från elnätet bearbetas och registreras, val av lämplig konsensus samt de olika blockkedja -ramverken

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  • 4.
    Johansson, Björn
    et al.
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden.
    Skoogh, Anders
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden.
    Andersson, Jon
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden.
    Ahlberg, Karin
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden.
    Hanson, Lars
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden ; Industrial Development, Scania, Södertälje, Sweden.
    Power-level sampling of metal cutting machines for data representation in discrete event simulation2014Ingår i: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 53, nr 23, s. 7060-7070Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An extension to the application area for discrete event simulation (DES) has been ongoing since the last decade and focused only on economic aspects to include ecologic sustainability. With this new focus, additional input parameters, such as electrical power consumption of machines, are needed. This paper aim at investigating how NC machine power consumption should be represented in simulation models of factories. The study includes data-sets from three different factories. One factory producing truck engine blocks, one producing brake disc parts for cars and one producing forklift components. The total number of data points analysed are more than 2,45,000, where of over 1,11,000 on busy state for 11 NC machines. The low variability between busy cycles indicates that statistical representations are not adding significant variability. Furthermore, results show that non-value-added activities cause a substantial amount of the total energy consumption, which can be reduced by optimising the production flow using dynamic simulations such as DES.

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  • 5.
    Karabulut, Mehmet
    et al.
    Department of Electrical and Computer Engineering, Yildirim Beyazit University, Ankara, Turkey.
    Kusetogullari, Huseyin
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi. Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden.
    Kivrak, Sinan
    Department of Electrical and Electronic Engineering, Yildirim Beyazit University, Ankara, Turkey.
    Outdoor Performance Assessment of New and Old Photovoltaic Panel Technologies Using a Designed Multi-Photovoltaic Panel Power Measurement System2020Ingår i: International Journal of Photoenergy (Online), ISSN 1110-662X, E-ISSN 1687-529X, Vol. 2020, s. 1-18, artikel-id 8866412Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a new multi-photovoltaic panel measurement and analysis system (PPMAS) developed for measurement of atmospheric parameters and generated power of photovoltaic (PV) panels. Designed system presented with an experimental study evaluates performance of four new and four 5-year-old PV panel technologies which are based on polycrystalline (Poly), monocrystalline (Mono), copper indium selenide (CIS), and cadmium telluride (CdTe) in real time, under same atmospheric conditions. The PPMAS system with the PV panels is installed in Yildirim Beyazit University, Ankara Province, in Turkey. The designed PPMAS consists of three different subsystems which are (1) photovoltaic panel measurement subsystem (PPMS), (2) meteorology measurement subsystem (MMS), and (3) data acquisition subsystem (DAS). PPMS is used to measure the power generation for PV panels. MMS involves different types of sensors, and it is designed to determine atmospheric conditions including wind speed, wind direction, outdoor temperature, humidity, ambient light, and panel temperatures. The measured values by PPMS and MMS are stored in a database using DAS subsystem. In order to improve the measurement accuracy, PPMS and MMS are calibrated. This study also focuses on outdoor testing performances of four new and four 5-year-old PV panels. Average monthly panel efficiencies are estimated as 8.46%, 8.11%, 5.65%, and 3.88% for new Mono, new Poly, new CIS, and new CdTe PV panels, respectively. Moreover, average monthly panel efficiencies of old panels are calculated as 8.22%, 7.85%, 5.35%, and 3.63% in the same order. Test results obtained from the experimental system are also statistically examined and discussed to analyze the performance of PV panels in terms of monthly panel efficiencie

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  • 6.
    Kourentzes, Nikolaos
    Department of Management Science, Lancaster University Management School, Lancaster, Lancashire, United Kingdom.
    On intermittent demand model optimisation and selection2014Ingår i: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 156, s. 180-190Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Intermittent demand time series involve items that are requested infrequently, resulting in sporadic demand. Crostons method and its variants have been proposed in the literature to address this forecasting problem. Recently other novel methods have appeared. Although the literature provides guidance on the suggested range for model parameters, a consistent and valid optimisation methodology is lacking. Growing evidence in the literature points against the use of conventional accuracy error metrics for model evaluation for intermittent demand time series. Consequently these may be inappropriate for parameter or model selection. This paper contributes to the discussion by evaluating a series of conventional time series error metrics, along with two novel ones for parameter optimisation for intermittent demand methods. The proposed metrics are found to not only perform best, but also provide consistent parameters with the literature, in contrast to conventional metrics. Furthermore, this work validates that employing different parameters for smoothing the non-zero demand and the inter-demand intervals of Crostons method and its variants is beneficial. The evaluated error metrics are considered for automatic model selection for each time series. Although they are found to perform similar to theory driven model selection schemes, they fail to outperform single models substantially. These findings are validated using both out-of-sample forecast evaluation and inventory simulations. 

  • 7.
    Ladrón de Guevara Muñoz, M. Carmen
    et al.
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    Martín Márquez, Javier
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    Mini-grid system study applied to a stand-alone house located in Málaga, Spain2015Självständigt arbete på grundnivå (kandidatexamen), 15 poäng / 22,5 hpStudentuppsats (Examensarbete)
    Abstract [en]

    A study of an off-grid photovoltaic system for the electrification of a stand-alone single residential house in a rural area located in the city of Málaga, Spain, is presented. The load of an average family house is analysed keeping in mind the available solar energy at this location. A preliminary sizing of the system is carried out considering predefined values for the efficiency of the different technologies employed in the system: photovoltaic (PV) array, batteries as energy storages, inverters to convert the energy obtained from the sun, and diesel gensets to ensure supply under any circumstances. Later, precise brands of the available technologies in the market are selected, and the system is re-sized using the new parameters. The life cycle cost of the mini-grid (MG) system shows that the amortization of the system in 20 years for a stand-alone house is not possible. Although it is not confirmed that 20 years will be sufficient to make the system profitable, other aspects are considered and discussed in terms of their feasibility in Málaga.

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  • 8.
    Liu, Yu
    et al.
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling.
    Syberfeldt, Anna
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling.
    Strand, Mattias
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningsmiljön Virtuell produkt- och produktionsutveckling.
    Applying Life Cycle Assessment to Simulation-Based Decision Support: A Swedish Waste Collection Case Study2020Ingår i: Advances and New Trends in Environmental Informatics: ICT for Sustainable Solutions: Conference proceedings / [ed] Rüdiger Schaldach; Karl-Heinz Simon; Jens Weismüller; Volker Wohlgemuth, Cham: Springer, 2020, Vol. 1, s. 165-178Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method of integrating life cycle assessment into a simulation-based decision support system has been developed to help decision-makers take environmental impact into account during daily operations. The method was demonstrated in a real-world case study involving eight different trucks, which were selected and maintained by the case company. The trucks used different fuels, namely diesel, biodiesel, vehicle gas, and electricity. Compared to conventional diesel trucks, those using biodiesel emitted 37% less greenhouse gas (GHG) emissions. Gas trucks reduced GHG emissions by a further 40%. Overall, electric trucks have the lowest emissions. This paper also addresses the development of the methodology for this study. In particular, comparisons are made regarding the selection of different functional units and system activity mapping. Ways of achieving more accurate conclusions in future studies are discussed. 

  • 9.
    Spiliotis, Evangelos
    et al.
    Forecasting and Strategy Unit, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
    Petropoulos, Fotios
    School of Management, University of Bath, Bath, United Kingdom.
    Kourentzes, Nikolaos
    Lancaster University Management School, Department of Management Science, Lancaster, United Kingdom.
    Assimakopoulos, Vassilios
    Forecasting and Strategy Unit, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
    Cross-temporal aggregation: Improving the forecast accuracy of hierarchical electricity consumption2020Ingår i: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 261, artikel-id 114339Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Achieving high accuracy in energy consumption forecasting is critical for improving energy management and planning. However, this requires the selection of appropriate forecasting models, able to capture the individual characteristics of the series to be predicted, which is a task that involves a lot of system and region level, not only the model selection problem is expanded to multiple time series, but we also require aggregation consistency of the forecasts across levels. Although hierarchical forecasting, such as the bottom-up, the top-down, and the optimal reconciliation methods, can address the aggregation consistency concerns, it does not resolve the model selection uncertainty. To address this issue, we rely on Multiple Temporal Aggregation (MTA), which has been shown to mitigate the model selection problem for low-frequency time series. We propose a modification of the Multiple Aggregation Prediction Algorithm, a special implementation of MTA, for high-frequency time series to better handle the undesirable effect of seasonality shrinkage that MTA implies and combine it with conventional cross-sectional hierarchical forecasting. The impact of incorporating temporal aggregation in hierarchical forecasting is empirically assessed using a real data set from five bank branches. We show that the proposed MTA approach, combined with the optimal reconciliation method, demonstrates superior accuracy, aggregation consistency, and reliable automatic forecasting. 

  • 10.
    Trapero, Juan R.
    et al.
    Universidad de Castilla-La Mancha, Departamento de Administracion de Empresas, Ciudad Real, Spain.
    Kourentzes, Nikolaos
    Lancaster University, Department of Management Science, United Kingdom.
    Martin, A.
    Universidad de Castilla-La Mancha, Departamento de Administracion de Empresas, Ciudad Real, Spain.
    Short-term solar irradiation forecasting based on Dynamic Harmonic Regression2015Ingår i: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 84, s. 289-295Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Solar power generation is a crucial research area for countries that have high dependency on fossil energy sources and is gaining prominence with the current shift to renewable sources of energy. In order to integrate the electricity generated by solar energy into the grid, solar irradiation must be reasonably well forecasted, where deviations of the forecasted value from the actual measured value involve significant costs. The present paper proposes a univariate Dynamic Harmonic Regression model set up in a State Space framework for short-term (1-24h) solar irradiation forecasting. Time series hourly aggregated as the Global Horizontal Irradiation and the Direct Normal Irradiation will be used to illustrate the proposed approach. This method provides a fast automatic identification and estimation procedure based on the frequency domain. Furthermore, the recursive algorithms applied offer adaptive predictions. The good forecasting performance is illustrated with solar irradiance measurements collected from ground-based weather stations located in Spain. The results show that the Dynamic Harmonic Regression achieves the lowest relative Root Mean Squared Error; about 30% and 47% for the Global and Direct irradiation components, respectively, for a forecast horizon of 24h ahead. 

  • 11.
    Wigblad, Rune
    Strömstad akademi.
    En spaning på internationell massproduktion av perovskite solceller2024Rapport (Övrigt vetenskapligt)
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