Artificial Neural Network Approach for Short Term Load Forecasting for Illam Region
In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems.
Decoder Design for a New Single Error Correcting/Double Error Detecting Code
This paper presents the decoder design for the single error correcting and double error detecting code proposed by the authors in an earlier paper. The speed of error detection and correction of a code is largely dependent upon the associated encoder and decoder circuits. The complexity and the speed of such circuits are determined by the number of 1?s in the parity check matrix (PCM). The number of 1?s in the parity check matrix for the code proposed by the authors are fewer than in any currently known single error correcting/double error detecting code. This results in simplified encoding and decoding circuitry for error detection and correction.
High Impedance Faults Detection Technique Based on Wavelet Transform
The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.
A Novel Technique for Ferroresonance Identification in Distribution Networks
Happening of Ferroresonance phenomenon is one of the reasons of consuming and ruining transformers, so recognition of Ferroresonance phenomenon has a special importance. A novel method for classification of Ferroresonance presented in this paper. Using this method Ferroresonance can be discriminate from other transients such as capacitor switching, load switching, transformer switching. Wavelet transform is used for decomposition of signals and Competitive Neural Network used for classification. Ferroresonance data and other transients was obtained by simulation using EMTP program. Using Daubechies wavelet transform signals has been decomposed till six levels. The energy of six detailed signals that obtained by wavelet transform are used for training and trailing Competitive Neural Network. Results show that the proposed procedure is efficient in identifying Ferroresonance from other events.
An Online Evaluation of Operating Reserve for System Security
Utilities use operating reserve for frequency regulation.To ensure that the operating frequency and system security are well maintained, the operating grid codes always specify that the reserve quantity and response rate should meet some prescribed levels. This paper proposes a methodology to evaluate system's contingency reserve for an isolated power network. With the presented algorithm to estimate system's frequency response characteristic, an online allocation of contingency reserve would be feasible to meet the grid codes for contingency operation. Test results from the simulated conditions, and from the actual operating data verify the merits of the proposed methodology to system's frequency control, and security.
A New Design of Temperature-Controlled Chamber for OLED Panels
This paper presents an inexpensive and effective temperature-controlled chamber for temperature environment tests of Organic Light Emitting Diode (OLED) panels. The proposed chamber is a compact warmer and cooler with an exact temperature control system. In the temperature-controlled space of the chamber, thermoelectric modules (TEMs) are utilized to cool or to heat OLED panels, novel fixtures are designed to flexibly clamp the OLED panels of different size, and special connectors for wiring between the OLED panels and the test instrument are supplied. The proposed chamber has the following features. (1) The TEMs are solid semi-conductive devices, so they operate without noise and without pollution. (2) The volume of the temperature-controlled space of the chamber about 160mm*160mm*120mm, so the chamber are compact and easy to move. (3) The range of the controlled temperatures is from -10 oC to +80 oC, and the precision is ?0.5 oC. (4) The test instrument can conveniently and easily measure the OLED panels via the novel fixtures and special connectors. In addition to a constant temperature being maintained in the chamber, a temperature shock experiments can run for a long time. Therefore, the chamber will be convenient and useful for temperature environment tests of OLED panels.
Voltage Sag Effect on Three Phase Five Leg Transformers
The behavior of three phase five leg transformer under voltage sag is studied in this paper. This paper proposes a simple, practical model of a three phase-five leg, saturated transformer with accurate performance. Transformer saturation is produced when the voltage sag is recovered and it causes inrush current in transformer. Effects of voltage sag depth, duration and initial point on wave have been analyzed in this paper. Initial point on wave can produce maximum inrush current in five leg transformers while comparing with three leg transformers. The magnetic circuit symmetry of five leg transformer produces the more symmetrical shape of inrush current curves versus initial point on wave and sag duration than three leg transformer. The simulations show that current peak has a periodical dependence on sag duration and linear dependence on sag depth. Inrush current that is produced in three phase five leg transformer is higher than three phase three leg transformer.
The Effect of Harmonic Power Fluctuation for Estimating Flicker
Voltage flicker problems have long existed in several
of the distribution areas served by the Taiwan Power Company. In
the past, those research results indicating that the estimated ΔV10
value based on the conventional method is significantly smaller than
the survey value. This paper is used to study the relationship between
the voltage flicker problems and harmonic power variation for the
power system with electric arc furnaces. This investigation discussed
thought the effect of harmonic power fluctuation with flicker
estimate value. The method of field measurement, statistics and
simulation is used. The survey results demonstrate that 10 ΔV
estimate must account for the effect of harmonic power variation.
Development of a Comprehensive Electricity Generation Simulation Model Using a Mixed Integer Programming Approach
This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.
Analysis of Lightning Surge Condition Effect on Surge Arrester in Electrical Power System by using ATP/EMTP Program
The condition of lightning surge causes the traveling waves and the temporary increase in voltage in the transmission line system. Lightning is the most harmful for destroying the transmission line and setting devices so it is necessary to study and analyze the temporary increase in voltage for designing and setting the surge arrester. This analysis describes the figure of the lightning wave in transmission line with 115 kV voltage level in Thailand by using ATP/EMTP program to create the model of the transmission line and lightning surge. Because of the limit of this program, it must be calculated for the geometry of the transmission line and surge parameter and calculation in the manual book for the closest value of the parameter. On the other hand, for the effects on surge protector when the lightning comes, the surge arrester model must be right and standardized as metropolitan electrical authority's standard. The candidate compared the real information to the result from calculation, also. The results of the analysis show that the temporary increase in voltage value will be rise to 326.59 kV at the line which is done by lightning when the surge arrester is not set in the system. On the other hand, the temporary increase in voltage value will be 182.83 kV at the line which is done by lightning when the surge arrester is set in the system and the period of the traveling wave is reduced, also. The distance for setting the surge arrester must be as near to the transformer as possible. Moreover, it is necessary to know the right distance for setting the surge arrester and the size of the surge arrester for preventing the temporary increase in voltage, effectively.
Development of Blower for Air Management System of Fuel Cell Modules
This study presents a blower for air management system of fuel cell modules. A blower is composed of BLDC motor and impeller. Magnetic equivalent circuit model and finite element analysis are used to design the motor, and an improved structure is considered to reduce a mechanical loss induced from bearing units. Finally, air blower system combined with the motor and an impeller is manufactured and output properties, such as an air pressure and an amount of flowing air, are measured. Through the experimental results, a validity of the simulated one is confirmed.
Application of Artificial Neural Networks for Temperature Forecasting
In this paper, the application of neural networks to study the design of short-term temperature forecasting (STTF) Systems for Kermanshah city, west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STTF systems is used. Our study based on MLP was trained and tested using ten years (1996-2006) meteorological data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STTF systems.
A Fuzzy System to Analyze SIVD Diseases Using the Transcranial Magnetic Stimulation
The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia (SIVD) and to measure the effect of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Relative Mapping Errors of Linear Time Invariant Systems Caused By Particle Swarm Optimized Reduced Order Model
The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.
High Impedance Fault Detection using LVQ Neural Networks
This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.
Design of AC Electronics Load Surge Protection
This study examines the design and construction of AC Electronics load surge protection in order to carry electric surge load arisen from faults in low voltage electricity system (single phase/220V) by using the principle of electronics load clamping voltage during induction period so that electric voltage could go through to safe load and continue to work. The qualification of the designed device could prevent both transient over voltage and voltage swell. Both will work in cooperation, resulting in the ability to improve and modify the quality of electrical power in Thailand electricity distribution system more effective than the past and help increase the lifetime of electric appliances, electric devices, and electricity protection equipments.
Highly Efficient Low Power Consumption Tracking Solar Cells for White LED-Based Lighting System
Although White LED lighting systems powered by solar cells have presented for many years, they are not widely used in today application because of their cost and low energy conversion efficiency. The proposed system use the dc power generated by fixed solar cells module to energize White LED light sources that are operated by directly connected White LED with current limitation resistors, resulting in much more power consumption. This paper presents the use of white LED as a general lighting application powered by tracking solar cells module and using pulse to apply the electrical power to the White LED. These systems resulted in high efficiency power conversion, low power consumption, and long light of the white LED.
A Hybrid GMM/SVM System for Text Independent Speaker Identification
This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.
A New Method of Combined Classifier Design Based on Fuzzy Neural Network
To make the modulation classification system more suitable for signals in a wide range of signal to noise rate (SNR), a novel method of designing combined classifier based on fuzzy neural network (FNN) is presented in this paper. The method employs fuzzy neural network classifiers and interclass distance (ICD) to improve recognition reliability. Experimental results show that the proposed combined classifier has high recognition rate with large variation range of SNR (success rates are over 99.9% when SNR is not lower than 5dB).
Balanced and Unbalanced Voltage Sag Mitigation Using DSTATCOM with Linear and Nonlinear Loads
DSTATCOM is one of the equipments for voltage sag mitigation in power systems. In this paper a new control method for balanced and unbalanced voltage sag mitigation using DSTATCOM is proposed. The control system has two loops in order to regulate compensator current and load voltage. Delayed signal cancellation has been used for sequence separation. The compensator should protect sensitive loads against different types of voltage sag. Performance of the proposed method is investigated under different types of voltage sags for linear and nonlinear loads. Simulation results show appropriate operation of the proposed control system.
Coordinated Design of TCSC Controller and PSS Employing Particle Swarm Optimization Technique
This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.