Search results for: output parameters
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10116

Search results for: output parameters

10056 Transient Signal Generator For Fault Indicator Testing

Authors: Mohamed Shaban, Ali Alfallah

Abstract:

This paper describes an application for testing of a fault indicator but it could be used for other network protection testing. The application is created in the LabVIEW environment and consists of three parts. The first part of the application is determined for transient phenomenon generation and imitates voltage and current transient signal at ground fault originate. The second part allows to set sequences of trend for each current and voltage output signal, up to six trends for each phase. The last part of the application generates harmonic signal with continuously controllable amplitude of current or voltage output signal and phase shift of each signal can be changed there. Further any sub-harmonics and upper harmonics can be added to selected current output signal

Keywords: signal generator-fault indicator, harmonic signal generator, voltage output

Procedia PDF Downloads 466
10055 Renewable Integration Algorithm to Compensate Photovoltaic Power Using Battery Energy Storage System

Authors: Hyung Joo Lee, Jin Young Choi, Gun Soo Park, Kyo Sun Oh, Dong Jun Won

Abstract:

The fluctuation of the output of the renewable generator caused by weather conditions must be mitigated because it imposes strain on the system and adversely affects power quality. In this paper, we focus on mitigating the output fluctuation of the photovoltaic (PV) using battery energy storage system (BESS). To satisfy tight conditions of system, proposed algorithm is developed. This algorithm focuses on adjusting the integrated output curve considering state of capacity (SOC) of the battery. In this paper, the simulation model is PSCAD / EMTDC software. SOC of the battery and the overall output curve are shown using the simulation results. We also considered losses and battery efficiency.

Keywords: photovoltaic generation, battery energy storage system, renewable integration, power smoothing

Procedia PDF Downloads 246
10054 Dynamic Modeling of Wind Farms in the Jeju Power System

Authors: Dae-Hee Son, Sang-Hee Kang, Soon-Ryul Nam

Abstract:

In this paper, we develop a dynamic modeling of wind farms in the Jeju power system. The dynamic model of wind farms is developed to study their dynamic effects on the Jeju power system. PSS/E is used to develop the dynamic model of a wind farm composed of 1.5-MW doubly fed induction generators. The output of a wind farm is regulated based on pitch angle control, in which the two controllable parameters are speed and power references. The simulation results confirm that the pitch angle is successfully controlled, regardless of the variation in wind speed and output regulation.

Keywords: dynamic model, Jeju power system, online limitation, pitch angle control, wind farm

Procedia PDF Downloads 295
10053 Power Quality Audit Using Fluke Analyzer

Authors: N. Ravikumar, S. Krishnan, B. Yokeshkumar

Abstract:

In present days, the power quality issues are increases due to non-linear loads like fridge, AC, washing machines, induction motor, etc. This power quality issues will affects the output voltages, output current, and output power of the total performance of the generator. This paper explains how to test the generator using the Fluke 435 II series power quality analyser. This Fluke 435 II series power quality analyser is used to measure the voltage, current, power, energy, total harmonic distortion (THD), current harmonics, voltage harmonics, power factor, and frequency. The Fluke 435 II series power quality analyser have several advantages. They are i) it will records output in analog and digital format. ii) the fluke analyzer will records at every 0.25 sec. iii) it will also measure all the electrical parameter at a time.

Keywords: THD, harmonics, power quality, TNEB, Fluke 435

Procedia PDF Downloads 150
10052 Algorithm Development of Individual Lumped Parameter Modelling for Blood Circulatory System: An Optimization Study

Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

Abstract:

Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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10051 Development of PSS/E Dynamic Model for Controlling Battery Output to Improve Frequency Stability in Power Systems

Authors: Dae-Hee Son, Soon-Ryul Nam

Abstract:

The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.

Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)

Procedia PDF Downloads 363
10050 Static Output Feedback Control of a Two-Wheeled Inverted Pendulum Using Sliding Mode Technique

Authors: Yankun Yang, Xinggang Yan, Konstantinos Sirlantzis, Gareth Howells

Abstract:

This paper presents a static output feedback sliding mode control method to regulate a two-wheeled inverted pendulum system with considerations of matched and unmatched uncertainties. A sliding surface is designed and the associated sliding motion stability is analysed based on the reduced-order dynamics. A static output sliding mode control law is synthesised to drive the system to the sliding surface and maintain a sliding motion afterwards. The nonlinear bounds on the uncertainties are employed in the stability analysis and control design to improve the robustness. The simulation results demonstrate the effectiveness of the proposed control.

Keywords: two-wheeled inverted pendulum, output feedback sliding mode control, nonlinear systems, robotics

Procedia PDF Downloads 214
10049 Modelling the Effect of Head and Bucket Splitter Angle on the Power Output of a Pelton Turbine

Authors: J. A. Ujam, J. L. Chukwuneke, C. H. Achebe, G. O. R. Ikwu

Abstract:

This work investigates the effect of head and bucket splitter angle on the power output of a pelton turbine (water turbine), so as to boost the efficiency of Hydro-electric power generation systems. A simulation program was developed using MatLab to depict the force generated by the bucket as the water jet strikes the existing splitter angle (100 to 150) and predicted (10 to 250) splitter angles. Result shows that in addition to the existing splitter angle, six more angles have been investigated for the two operating conditions to give maximum power. The angles are 250, 60 and 190 for high head and low flow with increased pressure while low head and high flow with decreased pressure are 230, 210 and 30 in order of the maximum generating power. The Turbine power output for simulation was more than that of the experiment. This was as a result of their head conditions and the bucket splitter angle.

Keywords: bucket splitter angle, force, head, modelling, pelton turbine, power output, shaft output

Procedia PDF Downloads 314
10048 High Efficiency ZPS-PWM Dual-Output Converters with EMI Reduction Method

Authors: Yasunori Kobori, Nobukazu Tsukiji, Nobukazu Takai, Haruo Kobayashi

Abstract:

In this paper, we study a Pulse-WidthModulation (PWM) controlled Zero-Voltage-Switching (ZVS) for single-inductor dual-output (SIDO) converters. This method can meet the industry demands for high efficiency due to ZVS and small size and low cost, thanks to single-inductor per multiple voltages. We show the single inductor single-output (SISO) ZVS buck converter with its operation and simulation and then the experimental results. Next proposed ZVS-PWM controlled SIDO converters are explained in the simulation. Finally we have proposed EMI reduction method with spread spectrum.

Keywords: DC-DC switching converter, zero-oltage switching control, single-inductor dual-output converter, EMI reduction, spread spectrum

Procedia PDF Downloads 462
10047 U-Net Based Multi-Output Network for Lung Disease Segmentation and Classification Using Chest X-Ray Dataset

Authors: Jaiden X. Schraut

Abstract:

Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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10046 ANFIS Approach for Locating Faults in Underground Cables

Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

Abstract:

This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, fault location, underground cable, wavelet transform

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10045 Multi-Objective Optimization and Effect of Surface Conditions on Fatigue Performance of Burnished Components Made of AISI 52100 Steel

Authors: Ouahiba Taamallah, Tarek Litim

Abstract:

The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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10044 Estimation of Residual Stresses in Thick Walled Cylinder by Radial Basis Artificial Neural

Authors: Mohammad Heidari

Abstract:

In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

Procedia PDF Downloads 379
10043 Environmental Sustainability and Energy Consumption: The Role of Financial Development in OPEC-1 Countries

Authors: Isah Wada

Abstract:

The current research investigates the role of financial development in an environmental sustainability-energy consumption nexus for OPEC-1 member countries. The empirical findings suggest that financial development increases environmental sustainability but energy consumption and real output expansion diminishes environmental sustainability, generally. Thus, whilst real output and financial development accelerates energy consumption, environmental sustainability quality diminishes clean energy initiatives. Even more so, energy consumption and financial development stimulates real output growth. The result empirically demonstrates that policy advocates must address broader issues relating to financial development whilst seeking to achieve environmental sustainability due largely to energy consumption.

Keywords: energy consumption, environmental sustainability, financial development, OPEC, real output

Procedia PDF Downloads 147
10042 Design, Analysis and Construction of a 250vac 8amps Arc Welding Machine

Authors: Anthony Okechukwu Ifediniru, Austin Ikechukwu Gbasouzor, Isidore Uche Uju

Abstract:

This article is centered on the design, analysis, construction, and test of a locally made arc welding machine that operates on 250vac with 8 amp output taps ranging from 60vac to 250vac at a fixed frequency, which is of benefit to urban areas; while considering its cost-effectiveness, strength, portability, and mobility. The welding machine uses a power supply to create an electric arc between an electrode and the metal at the welding point. A current selector coil needed for current selection is connected to the primary winding. Electric power is supplied to the primary winding of its transformer and is transferred to the secondary winding by induction. The voltage and current output of the secondary winding are connected to the output terminal, which is used to carry out welding work. The output current of the machine ranges from 110amps for low current welding to 250amps for high current welding. The machine uses a step-down transformer configuration for stepping down the voltage in order to obtain a high current level for effective welding. The welder can adjust the output current within a certain range. This allows the welder to properly set the output current for the type of welding that is being performed. The constructed arc welding machine was tested by connecting the work piece to it. Since there was no shock or spark from the transformer’s laminated core and was successfully used to join metals, it confirmed and validated the design.

Keywords: AC current, arc welding machine, DC current, transformer, welds

Procedia PDF Downloads 150
10041 Fuzzy Logic Modeling of Evaluation the Urban Skylines by the Entropy Approach

Authors: Murat Oral, Seda Bostancı, Sadık Ata, Kevser Dincer

Abstract:

When evaluating the aesthetics of cities, an analysis of the urban form development depending on design properties with a variety of factors is performed together with a study of the effects of this appearance on human beings. Different methods are used while making an aesthetical evaluation related to a city. Entropy, in its preliminary meaning, is the mathematical representation of thermodynamic results. Measuring the entropy is related to the distribution of positional figures of a message or information from the probabilities standpoint. In this study, analysis of evaluation the urban skylines by the entropy approach was modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Input-output parameters were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between application data and RBMTF is done by using absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of evaluation the urban skylines by the entropy approach. As a result, RBMTF model has shown satisfying relation with experimental results, which suggests an alternative method to evaluation of the urban skylines by the entropy approach.

Keywords: urban skylines, entropy, rule-based Mamdani type, fuzzy logic

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10040 Design of a Fuzzy Expert System for the Impact of Diabetes Mellitus on Cardiac and Renal Impediments

Authors: E. Rama Devi Jothilingam

Abstract:

Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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10039 Modular Harmonic Cancellation in a Multiplier High Voltage Direct Current Generator

Authors: Ahmad Zahran, Ahmed Herzallah, Ahmad Ahmad, Mahran Quraan

Abstract:

Generation of high DC voltages is necessary for testing the insulation material of high voltage AC transmission lines with long lengths. The harmonic and ripple contents of the output DC voltage supplied by high voltage DC circuits require the use of costly capacitors to smooth the output voltage after rectification. This paper proposes a new modular multiplier high voltage DC generator with embedded Cockcroft-Walton circuits that achieve a negligible harmonic and ripple contents of the output DC voltage without the need for costly filters to produce a nearly constant output voltage. In this new topology, Cockcroft-Walton modules are connected in series to produce a high DC output voltage. The modules are supplied by low input AC voltage sources that have the same magnitude and frequency and shifted from each other by a certain angle to eliminate the harmonics from the output voltage. The small ripple factor is provided by the smoothing column capacitors and the phase shifted input voltages of the cascaded modules. The constituent harmonics within each module are determined using Fourier analysis. The viability of the proposed DC generator for testing purposes and the effectiveness of the cascaded connection are confirmed by numerical simulations using MATLAB/Simulink.

Keywords: Cockcroft-Walton circuit, harmonics, ripple factor, HVDC generator

Procedia PDF Downloads 333
10038 Determining Efficiency of Frequency Control System of Karkheh Power Plant in Main Network

Authors: Ferydon Salehifar, Hassan Safarikia, Hossein Boromandfar

Abstract:

Karkheh plant in Iran's Khuzestan province and is located in the city Andimeshk. The plant has a production capacity of 400 MW units with water and three hours. One of the important parameters of each country's power grid stability is the stability of the power grid is affected by the voltage and frequency In plants, the amount of active power frequency control is done so that when the unit is placed in the frequency control their productivity is a function of frequency and output power varies with frequency. Produced by hydroelectric power plants with the water level behind the dam has a direct relationship And to decrease and increase the water level behind the dam in order to reduce the power output increases But these changes have a different interval is due to some mechanical problems such as turbine cavitation and vibration are limited. In this study, the range of the frequency control can be Karkheh manufacturing plants have been identified and their effectiveness has been determined.

Keywords: Karkheh power, frequency control system, active power, efficiency

Procedia PDF Downloads 587
10037 Approach to Formulate Intuitionistic Fuzzy Regression Models

Authors: Liang-Hsuan Chen, Sheng-Shing Nien

Abstract:

This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

Procedia PDF Downloads 108
10036 Modeling, Analysis, and Optimization of Process Parameters of Metal Spinning

Authors: B. Ravi Kumar, S. Gajanana, K. Hemachandra Reddy, K. Udayani

Abstract:

Physically into various derived shapes and sizes under the effect of externally applied forces. The spinning process is an advanced plastic working technology and is frequently used for manufacturing axisymmetric shapes. Over the last few decades, Sheet metal spinning has developed significantly and spun products have widely used in various industries. Nowadays the process has been expanded to new horizons in industries, since tendency to use minimum tool and equipment costs and also using lower forces with the output of excellent surface quality and good mechanical properties. The automation of the process is of greater importance, due to its wider applications like decorative household goods, rocket nose cones, gas cylinders, etc. This paper aims to gain insight into the conventional spinning process by employing experimental and numerical methods. The present work proposes an approach for optimizing process parameters are mandrel speed (rpm), roller nose radius (mm), thickness of the sheet (mm). Forming force, surface roughness and strain are the responses.in spinning of Aluminum (2024-T3) using DOE-Response Surface Methodology (RSM) and Analysis of variance (ANOVA). The FEA software is used for modeling and analysis. The process parameters considered in the experimentation.

Keywords: FEA, RSM, process parameters, sheet metal spinning

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10035 Classification of Barley Varieties by Artificial Neural Networks

Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

Abstract:

In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

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10034 Broadcasting Stabilization for Dynamical Multi-Agent Systems

Authors: Myung-Gon Yoon, Jung-Ho Moon, Tae Kwon Ha

Abstract:

This paper deals with a stabilization problem for multi-agent systems, when all agents in a multi-agent system receive the same broadcasting control signal and the controller can measure not each agent output but the sum of all agent outputs. It is analytically shown that when the sum of all agent outputs is bounded with a certain broadcasting controller for a given reference, each agent output is separately bounded:stabilization of the sum of agent outputs always results in the stability of every agent output. A numerical example is presented to illustrate our theoretic findings in this paper.

Keywords: broadcasting control, multi-agent system, transfer function, stabilization

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10033 Working Title: Estimating the Power Output of Photovoltaics in Kuwait Using a Monte Carlo Approach

Authors: Mohammad Alshawaf, Rahmat Poudineh, Nawaf Alhajeri

Abstract:

The power generated from photovoltaic (PV) modules is non-dispatchable on demand due to the stochastic nature of solar radiation. The random variations in the measured intensity of solar irradiance are due to clouds and, in the case of arid regions, dust storms which decrease the intensity of intensity of solar irradiance. Therefore, modeling PV power output using average, maximum, or minimum solar irradiance values is inefficient to predict power generation reliably. The overall objective of this paper is to predict the power output of PV modules using Monte Carlo approach based the weather and solar conditions measured in Kuwait. Given the 250 Wp PV module used in study, the average daily power output is 1021 Wh/day. The maximum power was generated in April and the minimum power was generated in January 1187 Wh/day and 823 Wh/day respectively. The certainty of the daily predictions varies seasonally and according to the weather conditions. The output predictions were far more certain in the summer months, for example, the 80% certainty range for August is 89 Wh/day, whereas the 80% certainty range for April is 250 Wh/day.

Keywords: Monte Carlo, solar energy, variable renewable energy, Kuwait

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10032 Design and Simulation of Coupled-Line Coupler with Different Values of Coupling Efficiency

Authors: Suleiman Babani, Jazuli Sanusi Kazaure

Abstract:

In this paper, two coupled-line couplers are designed and simulated using stripline technology. The coupled-line couplers (A and B) are designed with different values of coupling coefficient 6dB and 10dB respectively. Both of circuits have a coupled output port, a through output port and an isolated output port. Moreover, both circuits are tuned to function around 2.45 GHz. The design results are presented by simulation results obtained using ADS 2012.08 (Advanced Design System) software.

Keywords: ADS, coupled-line coupler, directional coupler, stripline

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10031 Optimization of Machining Parametric Study on Electrical Discharge Machining

Authors: Rakesh Prajapati, Purvik Patel, Hardik Patel

Abstract:

Productivity and quality are two important aspects that have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process, as well as the product developed. The electrical discharge machining (EDM) process, even now it is an experience process, wherein the selected parameters are still often far from the maximum, and at the same time selecting optimization parameters is costly and time consuming. Material Removal Rate (MRR) during the process has been considered as a productivity estimate with the aim to maximize it, with an intention of minimizing surface roughness taken as most important output parameter. These two opposites in nature requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Regression Analysis and Analysis of Variance. Then objective function is optimized using Genetic Algorithm technique. The model is shown to be effective; MRR and Surface Roughness improved using optimized machining parameters.

Keywords: MMR, TWR, OC, DOE, ANOVA, minitab

Procedia PDF Downloads 295
10030 Epistemic Uncertainty Analysis of Queue with Vacations

Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

Abstract:

The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

Procedia PDF Downloads 392
10029 The Realization of a System’s State Space Based on Markov Parameters by Using Flexible Neural Networks

Authors: Ali Isapour, Ramin Nateghi

Abstract:

— Markov parameters are unique parameters of the system and remain unchanged under similarity transformations. Markov parameters from a power series that is convergent only if the system matrix’s eigenvalues are inside the unity circle. Therefore, Markov parameters of a stable discrete-time system are convergent. In this study, we aim to realize the system based on Markov parameters by using Artificial Neural Networks (ANN), and this end, we use Flexible Neural Networks. Realization means determining the elements of matrices A, B, C, and D.

Keywords: Markov parameters, realization, activation function, flexible neural network

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10028 Role of Process Parameters on Pocket Milling with Abrasive Water Jet Machining Technique

Authors: T. V. K. Gupta, J. Ramkumar, Puneet Tandon, N. S. Vyas

Abstract:

Abrasive Water Jet Machining (AWJM) is an unconventional machining process well known for machining hard to cut materials. The primary research focus on the process was for through cutting and a very limited literature is available on pocket milling using AWJM. The present work is an attempt to use this process for milling applications considering a set of various process parameters. Four different input parameters, which were considered by researchers for part separation, are selected for the above application i.e. abrasive size, flow rate, standoff distance, and traverse speed. Pockets of definite size are machined to investigate surface roughness, material removal rate, and pocket depth. Based on the data available through experiments on SS304 material, it is observed that higher traverse speeds gives a better finish because of reduction in the particle energy density and lower depth is also observed. Increase in the standoff distance and abrasive flow rate reduces the rate of material removal as the jet loses its focus and occurrence of collisions within the particles. ANOVA for individual output parameter has been studied to know the significant process parameters.

Keywords: abrasive flow rate, surface finish, abrasive size, standoff distance, traverse speed

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10027 Battery State of Charge Management Algorithm for Photovoltaic Ramp Rate Control

Authors: Nam Kyu Kim, Hee Jun Cha, Jae Jin Seo, Dong Jun Won

Abstract:

Output power of a photovoltaic (PV) generator depends on incident solar irradiance. If the clouds pass or the climate condition is bad, the PV output fluctuates frequently. When PV generator is connected to the grid, these fluctuations adversely affect power quality. Thus, ramp rate control with battery energy storage system (BESS) is needed to reduce PV output fluctuations. At the same time, for effective BESS operation and sizing the optimal BESS capacity, managing state of charge (SOC) is the most important part. In addition, managing SOC helps to avoid violating the SOC operating range of BESS when performing renewable integration (RI) continuously. As PV and BESS increase, the SOC management of BESS will become more important in the future. This paper presents the SOC management algorithm which helps to operate effectively BESS, and has focused on method to manage SOC while reducing PV output fluctuations. A simulation model is developed in PSCAD/EMTDC software. The simulation results show that the SOC is maintained within the operating range by adjusting the output distribution according to the SOC of the BESS.

Keywords: battery energy storage system, ramp rate control, renewable integration, SOC management

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