TY - INPR A1 - Mosavi, Amir A1 - Torabi, Mehrnoosh A1 - Hashemi, Sattar A1 - Saybani, Mahmoud Reza A1 - Shamshirband, Shahaboddin T1 - A Hybrid Clustering and Classification Technique for Forecasting Short-Term Energy Consumption N2 - Electrical energy distributor companies in Iran have to announce their energy demand at least three 3-day ahead of the market opening. Therefore, an accurate load estimation is highly crucial. This research invoked methodology based on CRISP data mining and used SVM, ANN, and CBA-ANN-SVM (a novel hybrid model of clustering with both widely used ANN and SVM) to predict short-term electrical energy demand of Bandarabbas. In previous studies, researchers introduced few effective parameters with no reasonable error about Bandarabbas power consumption. In this research we tried to recognize all efficient parameters and with the use of CBA-ANN-SVM model, the rate of error has been minimized. After consulting with experts in the field of power consumption and plotting daily power consumption for each week, this research showed that official holidays and weekends have impact on the power consumption. When the weather gets warmer, the consumption of electrical energy increases due to turning on electrical air conditioner. Also, con-sumption patterns in warm and cold months are different. Analyzing power consumption of the same month for different years had shown high similarity in power consumption patterns. Factors with high impact on power consumption were identified and statistical methods were utilized to prove their impacts. Using SVM, ANN and CBA-ANN-SVM, the model was built. Sine the proposed method (CBA-ANN-SVM) has low MAPE 5 1.474 (4 clusters) and MAPE 5 1.297 (3 clusters) in comparison with SVM (MAPE 5 2.015) and ANN (MAPE 5 1.790), this model was selected as the final model. The final model has the benefits from both models and the benefits of clustering. Clustering algorithm with discovering data structure, divides data into several clusters based on similarities and differences between them. Because data inside each cluster are more similar than entire data, modeling in each cluster will present better results. For future research, we suggest using fuzzy methods and genetic algorithm or a hybrid of both to forecast each cluster. It is also possible to use fuzzy methods or genetic algorithms or a hybrid of both without using clustering. It is issued that such models will produce better and more accurate results. This paper presents a hybrid approach to predict the electric energy usage of weather-sensitive loads. The presented methodutilizes the clustering paradigm along with ANN and SVMapproaches for accurate short-term prediction of electric energyusage, using weather data. Since the methodology beinginvoked in this research is based on CRISP data mining, datapreparation has received a gr eat deal of attention in thisresear ch. Once data pre-processing was done, the underlyingpattern of electric energy consumption was extracted by themeans of machine learning methods to precisely forecast short-term energy consumption. The proposed approach (CBA-ANN-SVM) was applied to real load data and resulting higher accu-racy comparing to the existing models. 2018 American Institute of Chemical Engineers Environ Prog, 2018 https://doi.org/10.1002/ep.12934 KW - Data Mining KW - support vector machine (SVM) KW - Machine Learning KW - forecasting KW - Prediction KW - Electric Energy Consumption KW - clustering KW - artificial neural networks (ANN) Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180907-37550 N1 - This is the pre-peer reviewed version of the following article: https://onlinelibrary.wiley.com/doi/10.1002/ep.12934, which has been published in final form at https://doi.org/10.1002/ep.12934. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. ER - TY - JOUR A1 - Mosavi, Amir A1 - Najafi, Bahman A1 - Faizollahzadeh Ardabili, Sina A1 - Shamshirband, Shahaboddin A1 - Rabczuk, Timon T1 - An Intelligent Artificial Neural Network-Response Surface Methodology Method for Accessing the Optimum Biodiesel and Diesel Fuel Blending Conditions in a Diesel Engine from the Viewpoint of Exergy and Energy Analysis JF - Energies N2 - Biodiesel, as the main alternative fuel to diesel fuel which is produced from renewable and available resources, improves the engine emissions during combustion in diesel engines. In this study, the biodiesel is produced initially from waste cooking oil (WCO). The fuel samples are applied in a diesel engine and the engine performance has been considered from the viewpoint of exergy and energy approaches. Engine tests are performed at a constant 1500 rpm speed with various loads and fuel samples. The obtained experimental data are also applied to develop an artificial neural network (ANN) model. Response surface methodology (RSM) is employed to optimize the exergy and energy efficiencies. Based on the results of the energy analysis, optimal engine performance is obtained at 80% of full load in presence of B10 and B20 fuels. However, based on the exergy analysis results, optimal engine performance is obtained at 80% of full load in presence of B90 and B100 fuels. The optimum values of exergy and energy efficiencies are in the range of 25–30% of full load, which is the same as the calculated range obtained from mathematical modeling. KW - Biodiesel KW - ANN modeling KW - biodiesel KW - Artificial Intelligence KW - diesel engines KW - energy, exergy KW - mathematical modeling KW - OA-Publikationsfonds2018 Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180507-37467 UR - http://www.mdpi.com/1996-1073/11/4/860 VL - 2018 IS - 11, 4 PB - MDPI CY - Basel ER - TY - INPR A1 - Mosavi, Amir A1 - Moeini, Iman A1 - Ahmadpour, Mohammad A1 - Alharbi, Naif A1 - E. Gorji, Nima T1 - Modeling the time-dependent characteristics of perovskite solar cells N2 - We proposed two different time-dependent modeling approaches for variation of device characteristics of perovskite solar cells under stress conditions. The first approach follows Sah-Noyce-Shockley (SNS) model based on Shockley–Read–Hall recombination/generation across the depletion width of pn junction and the second approach is based on thermionic emission model for Schottky diodes. The connecting point of these approaches to time variation is the time-dependent defect generation in depletion width (W) of the junction. We have fitted the two models with experimental data reported in the literature to perovskite solar cell and found out that each model has a superior explanation for degradation of device metrics e.g. current density and efficiency by time under stress conditions. Nevertheless, the Sah-Noyce-Shockley model is more reliable than thermionic emission at least for solar cells. KW - Solarzelle KW - Solar KW - Solar cells KW - Modeling KW - Time-dependent KW - Defect generation KW - Perovskite Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180907-37573 N1 - Published in final form at https://doi.org/10.1016/j.solener.2018.05.082. ER - TY - JOUR A1 - Mosavi, Amir A1 - Hosseini Imani, Mahmood A1 - Zalzar, Shaghayegh A1 - Shamshirband, Shahaboddin T1 - Strategic Behavior of Retailers for Risk Reduction and Profit Increment via Distributed Generators and Demand Response Programs JF - Energies N2 - Following restructuring of power industry, electricity supply to end-use customers has undergone fundamental changes. In the restructured power system, some of the responsibilities of the vertically integrated distribution companies have been assigned to network managers and retailers. Under the new situation, retailers are in charge of providing electrical energy to electricity consumers who have already signed contract with them. Retailers usually provide the required energy at a variable price, from wholesale electricity markets, forward contracts with energy producers, or distributed energy generators, and sell it at a fixed retail price to its clients. Different strategies are implemented by retailers to reduce the potential financial losses and risks associated with the uncertain nature of wholesale spot electricity market prices and electrical load of the consumers. In this paper, the strategic behavior of retailers in implementing forward contracts, distributed energy sources, and demand-response programs with the aim of increasing their profit and reducing their risk, while keeping their retail prices as low as possible, is investigated. For this purpose, risk management problem of the retailer companies collaborating with wholesale electricity markets, is modeled through bi-level programming approach and a comprehensive framework for retail electricity pricing, considering customers’ constraints, is provided in this paper. In the first level of the proposed bi-level optimization problem, the retailer maximizes its expected profit for a given risk level of profit variability, while in the second level, the customers minimize their consumption costs. The proposed programming problem is modeled as Mixed Integer programming (MIP) problem and can be efficiently solved using available commercial solvers. The simulation results on a test case approve the effectiveness of the proposed demand-response program based on dynamic pricing approach on reducing the retailer’s risk and increasing its profit. In this paper, the decision-making problem of the retailers under dynamic pricing approach for demand response integration have been investigated. The retailer was supposed to rely on forward contracts, DGs, and spot electricity market to supply the required active and reactive power of its customers. To verify the effectiveness of the proposed model, four schemes for retailer’s scheduling problem are considered and the resulted profit under each scheme are analyzed and compared. The simulation results on a test case indicate that providing more options for the retailer to buy the required power of its customers and increase its flexibility in buying energy from spot electricity market reduces the retailers’ risk and increases its profit. From the customers’ perspective also the retailers’accesstodifferentpowersupplysourcesmayleadtoareductionintheretailelectricityprices. Since the retailer would be able to decrease its electricity selling price to the customers without losing its profitability, with the aim of attracting more customers. Inthiswork,theconditionalvalueatrisk(CVaR)measureisusedforconsideringandquantifying riskinthedecision-makingproblems. Amongallthepossibleoptioninfrontoftheretailertooptimize its profit and risk, demand response programs are the most beneficial option for both retailer and its customers. The simulation results on the case study prove that implementing dynamic pricing approach on retail electricity prices to integrate demand response programs can successfully provoke customers to shift their flexible demand from peak-load hours to mid-load and low-load hours. Comparing the simulation results of the third and fourth schemes evidences the impact of DRPs and customers’ load shifting on the reduction of retailer’s risk, as well as the reduction of retailer’s payment to contract holders, DG owners, and spot electricity market. Furthermore, the numerical results imply on the potential of reducing average retail prices up to 8%, under demand response activation. Consequently, it provides a win–win solution for both retailer and its customers. KW - Risikomanagement KW - demand response programs KW - stochastic programming KW - forward contracts KW - risk management KW - retailer KW - OA-Publikationsfonds2018 Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180628-37546 UR - http://www.mdpi.com/1996-1073/11/6/1602 VL - 2018 IS - 11, 6 PB - MDPI CY - Basel ER - TY - THES A1 - Mischke, Marcel T1 - Keine Ahnung? Landschaft! N2 - ... soll auf den folgenden Seiten eine dritte Richtung angedeutet und vorgezeichnet werden, die ebenso Interesse am Erkenntnisgewinn durch das Thema Landschaft bekundet, dies hingegen aus der Umkehrung heraus erreichen will. Dreht man den Richtungspfeil, stehen wir ihr, der Landschaft, gegenüber. Vom Modus des Aktiven geraten wir in die Passivität. Damit wird eine Korrektur der Fragestellung möglich. Es entsteht eine Perspektive, die die Überlegungen zulässt: Was die Landschaft eigentlich mit uns macht?, welchen Horizont sie uns eröffnet und entstehen lässt, welche Bedeutung und welche Qualität wir dem ›Landschaftlichen‹ zuschreiben können, worin die Notwendigkeit ihres Erhalts und der Nutzen für die gegenwärtige Gesellschaft bestehen kann. KW - Landschaft KW - Fotografie Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20181122-38242 ER - TY - THES A1 - Michel, Ralf T1 - Licht – Farbe – Licht : Zur Integration von Design und Technik in der Designforschung mit Licht und Farbe N2 - Die Thesis untersucht am Beispiel von Farb-Licht Forschungen (Interaktion dynamischen Lichts mit farbigen Oberflächen) und der Designforschungen am Potenzial der organisch Licht emittierenden Dioden (OLED) integrierende Aspekte des Designs im Kontext dieser Technologien. Des weiteren reflektiert die Thesis am Beispiel dieser Designforschungen das Verhältnis von Designforschung und Innovation für die gestalterischen Disziplinen. KW - Design KW - Integrative Gestaltung KW - Designforschung Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180921-37941 ER - TY - THES A1 - Link, Tim T1 - Entwicklung und Untersuchung von alternativen Dicalciumsilicat-Bindern auf der Basis von alpha-C2SH N2 - Um den Klimawandel zu begrenzen, müssen die CO2-Emissionen drastisch gesenkt werden [100]. Bis 2050 soll bei der Herstellung von Zement eine Einsparung um 51–60 % auf 0,425–0,350 tCO2/tZement erfolgen [7]. Um dieses Ziel zu erreichen, sind alternative Bindemittelkonzepte notwendig [70]. Diese Arbeit widmet sich alternativen, hochreaktiven Dicalciumsilicat-Bindemitteln, die durch die thermische Aktivierung von α-Dicalcium-Silicat-Hydrat (α-C2SH) erzeugt werden. Das α-C2SH ist eine kristalline C S H-Phase, die im hydrothermalen Prozess, beispielsweise aus Branntkalk und Quarz, herstellbar ist. Die thermische Aktivierung kann bei sehr niedrigen Temperaturen erfolgen (>420 °C) und führt zu einem Multiphasen-C2S-Binder. Als besonders reaktive Bestandteile können x-C2S und röntgenamorphe Anteile enthalten sein. Weiterhin können β C2S, γ C2S und Dellait (Ca6(SiO4)(Si2O7)(OH)2) entstehen. Im Rahmen der Arbeit wird zunächst der Stand des Wissens zur Polymorphie und Hydratation von C2S zusammengefasst. Es werden bekannte C2S-basierte Bindemittelkonzepte vorgestellt und bewertet. Die Herstellung von C2S-Bindern wird experimentell im Labormaßstab untersucht. Dabei kommen unterschiedliche Autoklaven und ein Muffelofen zum Einsatz. Die Herstellungsparameter werden hinsichtlich Phasenbestand und Reaktivität optimiert. Die Bindemittel werden durch quantitative Röntgen-Phasenanalyse (QXRD), Rasterelektronenmikroskopie (REM), N2-Adsorption (BET-Methode), Heliumpycnometer, Thermoanalyse (TGA/DSC) und 29Si-MAS- sowie 29Si-1H-CP/MAS-NMR-Spektroskopie charakterisiert. Das Hydratationsverhalten der Bindemittel wird vorrangig mithilfe von Wärmeflusskalorimetrie untersucht. Weiterhin werden in situ und ex situ XRD-, TGA/DSC- und REM-Untersuchungen durchgeführt. Anhand von zwei Bindemitteln wird die Fähigkeit zur Erzielung hoher Festigkeiten demonstriert. Abschließend erfolgt eine Abschätzung zu Energiebedarf und CO2-Emissionen für die Herstellung der untersuchten C2S-Binder. Die Ergebnisse zeigen, dass für eine hohe Reaktivität der Binder eine niedrige Brenntemperatur und ein geringer Wasserdampfpartialdruck während der thermischen Aktivierung entscheidend sind. Weiterhin muss das hydrothermal hergestellte α-C2SH eine möglichst hohe spezifische Oberfläche aufweisen. Diese Parameter beeinflussen den Phasenbestand und die phasenspezifische Reaktivität. Brenntemperaturen von ca. 420–500 °C führen zu hochreaktiven Bindern, die im Rahmen dieser Arbeit als Niedertemperatur-C2S-Binder bezeichnet werden. Temperaturen von ca. 600–800 °C führen zu Bindern mit geringerer Reaktivität, die im Rahmen dieser Arbeit als Hochtemperatur-C2S bezeichnet werden. Höhere Brenntemperaturen (1000 °C) führen zu Bindemitteln, die innerhalb der ersten drei Tage keine hydraulische Aktivität zeigen. Die untersuchten Bindemittel können sehr hohe Reaktionsgeschwindigkeiten erreichen. Die Wärmeflusskalorimetrie deutet bei einigen Bindemitteln einen nahezu vollständigen Umsatz innerhalb von drei Tagen an. Durch XRD wurde für einen Binder der vollständige Verbrauch von x-C2S innerhalb von drei Tagen nachgewiesen. Für einen mittels in-situ-XRD und Wärmeflusskalorimetrie untersuchten Binder wurde gezeigt, dass die Phasen vorrangig in der Reihenfolge röntgenamorph > x-C2S > β-C2S > γ-C2S hydratisieren. Hydratationsprodukte sind nadelige C S H-Phasen und Portlandit. Die Herstellung durch thermische Aktivierung von α-C2SH führt zu tafeligen Bindemittelpartikeln, die teilweise Zwickelräume und Poren zwischen den einzelnen Partikeln einschließen. Um eine verarbeitbare Bindemittelpaste zu erzeugen, sind daher sehr hohe Wasser/Bindemittel-Werte (z. B. 1,4) erforderlich. Der Wasseranspruch kann durch Mahlung etwa auf das Niveau von Zement gesenkt werden. Die Druckfestigkeitsentwicklung wurde an zwei Niedertemperatur-C2S-Kompositbindern mit 40 % Kalksteinmehl bzw. 40 % Hüttensand untersucht. Aufgrund von theoretischen Betrachtungen zur Porosität in Abhängigkeit des w/b-Wertes wurde dieser auf 0,3 festgelegt. Durch Zugabe von PCE-Fließmittel wurde ein verarbeitbarer Mörtel erhalten. Die Festigkeitsentwicklung ist sehr schnell. Der Kalksteinmehl-Binder erreichte nach zwei Tagen 46 N/mm². Bis Tag 28 trat keine weitere Festigkeitssteigerung ein. Der Hüttensand-Binder erreichte nach zwei Tagen 62 N/mm². Durch die Hüttensandreaktion stieg die Festigkeit bis auf 85 N/mm² nach 28 Tagen an. Für den Herstellungsprozess von Niedertemperatur-C2S-Binder wurden Energieverbräuche und CO2-Emissionen abgeschätzt. Es deutet sich an, dass, bezogen auf die Bindemittelmenge, keine wesentlichen Einsparungen im Vergleich zur Portlandzementherstellung möglich sind. Für die tatsächlichen Emissionen muss jedoch zusätzlich die Leistungsfähigkeit der Bindemittel berücksichtigt werden. Die Leistungsfähigkeit kann als erforderliche Bindemittelmenge betrachtet werden, die je m³ Beton eingesetzt werden muss, um bestimmte Festigkeits-, Dauerhaftigkeits- und Verarbeitungseigenschaften zu erreichen. Aus verschiedenen Veröffentlichungen [94, 201, 206] wurde die These abgeleitet, dass die Leistungsfähigkeit eines Bindemittels maßgeblich von der C-S-H-Menge bestimmt wird, die während der Hydratation gebildet wird. Daher wird für NT-C2S-Binder eine außergewöhnlich hohe Leistungsfähigkeit erwartet. Auf Basis der Leistungsfähigkeitsthese verringern sich die abgeschätzten CO2-Emissionen von NT-C2S-Bindern, sodass gegenüber Portlandzement ein mögliches Einsparpotenzial von 42 % ermittelt wurde. KW - Belit KW - Zement KW - Hydratation KW - Calcinieren KW - Autoklav KW - alpha-C2SH KW - Hydrothermalsynthese KW - alternative Bindemittel KW - CO2 Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180205-37228 ER - TY - THES A1 - Lang, Kevin T1 - Argument Search with Voice Assistants N2 - The need for finding persuasive arguments can arise in a variety of domains such as politics, finance, marketing or personal entertainment. In these domains, there is a demand to make decisions by oneself or to convince somebody about a specific topic. To obtain a conclusion, one has to search thoroughly different sources in literature and on the web to compare various arguments. Voice interfaces, in form of smartphone applications or smart speakers, present the user with natural conversations in a comfortable way to make search requests in contrast to a traditional search interface with keyboard and display. Benefits and obstacles of such a new interface are analyzed by conducting two studies. The first one consists of a survey for analyzing the target group with questions about situations, motivations, and possible demanding features. The latter one is a wizard-of-oz experiment to investigate possible queries on how a user formulates requests to such a novel system. The results indicate that a search interface with conversational abilities can build a helpful assistant, but to satisfy the demands of a broader audience some additional information retrieval and visualization features need to be implemented. KW - Amazon Alexa KW - Argument KW - Suche KW - Stimme KW - Assistent KW - alexa KW - voice KW - assistant KW - arguments KW - search Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20190617-39353 ER - TY - JOUR A1 - Laak, Dirk van T1 - Freiräume. Historische Hinweise zur Füllung einer Leerstelle N2 - Vortrag, gehalten am 22.11.2017 anlässlich des Wissenschaftstages an der Bauhaus-Universität Weimar T3 - Neue Bauhausvorträge - 4 KW - Freiraum Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20180724-37716 ER - TY - INPR A1 - Kavrakov, Igor A1 - Morgenthal, Guido T1 - A synergistic study of a CFD and semi-analytical models for aeroelastic analysis of bridges in turbulent wind conditions N2 - Long-span bridges are prone to wind-induced vibrations. Therefore, a reliable representation of the aerodynamic forces acting on a bridge deck is of a major significance for the design of such structures. This paper presents a systematic study of the two-dimensional (2D) fluid-structure interaction of a bridge deck under smooth and turbulent wind conditions. Aerodynamic forces are modeled by two approaches: a computational fluid dynamics (CFD) model and six semi-analytical models. The vortex particle method is utilized for the CFD model and the free-stream turbulence is introduced by seeding vortex particles upstream of the deck with prescribed spectral characteristics. The employed semi-analytical models are based on the quasi-steady and linear unsteady assumptions and aerodynamic coefficients obtained from CFD analyses. The underlying assumptions of the semi-analytical aerodynamic models are used to interpret the results of buffeting forces and aeroelastic response due to a free-stream turbulence in comparison with the CFD model. Extensive discussions are provided to analyze the effect of linear fluid memory and quasi-steady nonlinearity from a CFD perspective. The outcome of the analyses indicates that the fluid memory is a governing effect in the buffeting forces and aeroelastic response, while the effect of the nonlinearity is overestimated by the quasi-steady models. Finally, flutter analyses are performed and the obtained critical velocities are further compared with wind tunnel results, followed by a brief examination of the post-flutter behavior. The results of this study provide a deeper understanding of the extent of which the applied models are able to replicate the physical processes for fluid-structure interaction phenomena in bridge aerodynamics and aeroelasticity. KW - Ingenieurwissenschaften KW - Aerodynamik KW - Bridge KW - Aerodynamic nonlinearity KW - Fluid memory KW - Vortex particle method KW - Buffeting KW - Flutter Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200206-40873 N1 - This is the pre-peer reviewed version of the following article: https://www.sciencedirect.com/science/article/abs/pii/S0889974617308423?via%3Dihub, which has been published in final form at https://doi.org/10.1016/j.jfluidstructs.2018.06.013 ER -