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International Review of Electrical Engineering Vol. 7 N. 1-- Part A

International Review of Electrical Engineering Vol. 7 N. 1-- Part B

International Review of Electrical Engineering - February 2012 (Vol. 7 N. 1) - Papers Part A

	A Generalized Space Vector Modulation Algorithm for Multilevel Inverters - Induction Motor Fed Design and Implementation of a Single-Stage Low-Frequency Square-Wave-Driven Electronic Ballast for HID Lamps Prediction of Case Temperature for Monitoring IGBT Power Module using Artificial Neural Network Cascade H-Bridge Multilevel Inverter with Low Output Harmonics for Electric/Hybrid Electric Vehicle Applications Modeling and Control of an Integrated Power Electronics Interface for Plug-in Hybrid Electric Vehicles Feature Extraction Method Based on Pulse-Coupled Neural Networks for Ultra High Frequency Partial Discharge in Transformers A Novel Two-Step Minimal-Power-Dissipation Control Method for Magnetically Levitated Planar Motor Defining Design Criteria of an Axial Flux Permanent Magnet Synchronous Generator IPM Synchronous Motor for Traction Applications: Performance Analysis Considering Hysteresis Loop Characteristics Variation Implementation of H∞Multivariable Feedback Control for Permanent Magnet Synchronous Motor Drive System Analytical Design of the Double Rotor Switched Reluctance Motor with Optimal Pole Arc Values Integral Backstepping Control for a PMLSM Using Adaptive RNNUO Robust Nonlinear Receding Horizon Speed Control of Permanent Magnet Synchronous Machine with Armature Current Limitations Modeling and Detection of Inter-turn Fault in Induction Motors Using Wavelet Entropy Estimation Linkage and Inductance Characteristics of a Double-Stator Switched Reluctance Machine Partial Discharge Signal Classification Utilizing Time-Frequency Representation and Two Directional 2DPCA Branch Outage Simulation Based Contingency Screening by Gravitational Search Algorithm Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market Designing and Experimenting an Auto-Adaptive Controller for a Stand-Alone Photovoltaic System with Hybrid Storage Hamilton Energy Theory based Coordinated Control of Generator Excitation and TCSC Effects of Corona Ring Design and its Location on Electric Field and Potential Distribution along 400kV and 1000kV Contaminated Insulator String Firefly Algorithm for Reliable/Emission/Economic Dispatch Multi Objective Problem Dynamic Economic Dispatch Considering Network Power Losses Based on Gravitational Search Algorithm
International Review of Electrical Engineering - February 2012 (Vol. 7 N. 1) - Papers Part B
	Probabilistic LV Distribution Network Design for Aggregated Light Industrial Loads Multi-Objective Environmental Optimal Power Flow Considering Transient Stability Improvement Artificial Intelligence Forecast of PV Plant Production for Integration in Smart Energy Systems A Novel Approach for Optimal Determination of Number of Distributed Generation Units along with their Sizes and Locations Linear Programming for Optimal Sizing of DGs in MicroGrid Considering Loss of Power Supply Probability Technology Probabilistic Approach to Reliability Assessment of Electric Power System Containing Distributed Generation Solution for Multi-Objective Reactive Power Optimization Problem using Fuzzified Particle Swarm Optimization Algorithm Stabilization of Multi-Machine Power Systems Using Craziness based Particle Swarm Optimization and Harmony Search Algorithms Lightning Transient Modeling of Wind Turbine Towers Power System Stability Enhancement Using SSSC Precise Modeling and Detection of High Impedance Faults in Microgrid System Based on Residual Current Harmonic Analysis Single Phase Fault Distance Estimation in Medium Voltage Distribution Network Based on Traveling Waves Blended Crossover Continuous Ant Colony Optimization and Stability Index Tracing for Effective FACTS Devices Installation Using Clonal Selection Algorithm for Optimal Placement and Sizing of Unified Power Flow Controllers in Deregulated Power Systems A Detailed Comparison of Cumulant-based Probabilistic Power Flow Methods Adaptive Least Squares Support Vector Machines Method for Short-term Load Forecasting Based on Mutual Information for Inputs Selection A Fault Direction Discrimination Scheme Based on Transients Generated by Faults in Multi-Branch Power Systems A Honey Bee Foraging Approach to Optimal Capacitor Placement with Harmonic Distortion Consideration Investigation of the Methods for Single Area and Multi Area Optimization of a Power System Dispatch Problem A Study on Scheduling of Primary Frequency Control Reserve BDA Fault Detection in Complex Electric Power Systems Static and Dynamic Security-Augmented Market-Based Generation Scheduling Using Multi-Objective Artificial Bee Colony Algorithm An Efficient Non-Convex Power Dispatch Approach for Modern Thermal Units Environmental/Economic Power Dispatch Using Multi-objective Honey Bee Mating Optimization

International Review of Electrical Engineering - Papers- Part A

A Generalized Space Vector Modulation Algorithm for Multilevel Inverters - Induction Motor Fed
by T. G. Nathenas, G. A. Adamidis

Vol. 7. n. 1, pp. 3218-3229

Abstract - In this paper a new Space Vector Pulse Width Modulation (SVPWM) algorithm is proposed for multilevel voltage source inverters. The proposed algorithm directly identifies the two-level subhexagon in which the reference voltage vector lies. The switching sequence corresponding to a two-level inverter is determined. The proposed method can be extended to any m-level inverter and a generalized algorithm is proposed. Based on the mathematical model presented, a “five-level inverter, induction motor” system is investigated in steady state and transient responses. The induction motor is controlled using Field Oriented Control (F.O.C.). The improvement of the control scheme is achieved using Mamdani’s fuzzy logic controller for both rotor speed and inverter current. The electric drive system is simulated in case of a five-level inverter and the presented results verify the good performance of the proposed SVPWM algorithm.

Keywords: Multilevel Inverter, Space Vector PWM, Induction Motor, Field Oriented Control, Fuzzy Logic Theory.

Design and Implementation of a Single-Stage Low-Frequency Square-Wave-Driven Electronic Ballast for HID Lamps
by Chun-An Cheng, Hung-Liang Cheng, Yung-Chine Wu

Vol. 7. n. 1, pp. 3230-3239

Abstract - This paper presents a single-stage low-frequency square-wave-driven electronic ballast for supplying high-intensity-discharging (HID) lamps with interleaved power-factor-correction (PFC) features. The proposed ballast, which integrates an interleaved PFC converter with a high/low-frequency square-wave-driven full-bridge inverter into a single-stage, not only offers input utility-line current shaping, but also supplies the lamp with low-frequency square-wave sources without accompanying acoustic resonance. The features of the presented ballast are cost-effectiveness, low total-harmonic-distortion (THD), high power factor (>0.99), and high efficiency (>90%) due to the achievement of zero-voltage switching (ZVS) in the high-frequency-operated power switches. This paper demonstrates the theoretical analysis, design guidelines, and experimental results for a prototype ballast supplying a 70-watt HID lamp drawing from a utility-line root-mean-square (rms) voltage of 110 V.

Keywords: Acoustic Resonance, Electronic Ballast, High-Intensity-Discharging Lamp, Power-Factor-Correction.

Prediction of Case Temperature for Monitoring IGBT Power Module using Artificial Neural Network
by Minyou Chen, Shengyou Xu, Li Ran, Dawei Xiang, Peter Wallie

Vol. 7. n. 1, pp. 3240-3247

Abstract - Packaging-related internal failure such as solder fatigue or wire crack has been acknowledged as one of the principal root causes of IGBT power module failures. Condition monitoring is needed by power electronic system operator as a cost-effective means of improving IGBT reliability. In this paper, an approach is presented to monitor internal failure inside a IGBT power module by identifying the increase of external case temperature due to internal failure, In this method, an IGBT power module is regarded as a black box system without considering any internal factors or models associated with the heat sink as well as the power loss module, all electrical factors at certain working points are classified as the inputs, meanwhile the case temperature is considered as the output of the black box system respectively, in which any device power loss model or heat sink model is not established to estimate the internal thermal resistance. Firstly, case temperature is predicted based on the GA-BP artificial neural network, after that, a monitoring method are presented based on the predicted look-up table or model and a threshold for the difference between the measured and the predicted case temperature is set reasonably. It is because that the total loss in the module increases as junction temperature rises generated from internal failure, causing an increase in case temperature rise, the external characteristic of IGBT is the reflection of internal condition, once the measured case temperature is higher than the predicted temperature at a certain working point, taking account of the masking effect of measuring accuracy and errors, then a conclusion can be get that the IGBT condition is abnormal. At last, experiment has validated and demonstrated the concept and characterized the proposed method.

Keywords: Condition Monitoring, Internal Failure, IGBT Reliability, Prediction of Case Temperature, GA-BP.

Cascade H-Bridge Multilevel Inverter with Low Output Harmonics for Electric/Hybrid Electric Vehicle Applications
by Mohsen Ebadpour, Mohammad Bagher Bannae Sharifian

Vol. 7. n. 1, pp. 3248-3256

Abstract - Development of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) will offer many new opportunities and challenges to the power electronics industry, especially in the development of the main traction motor drive. Both HEVs and EVs need a traction motor and a power inverter to drive the vehicle motor. The requirements for the power inverter include high peak power, low output harmonics, inexpensive circuit and low continuous power rating. Cascade H-bridge (CHB) multilevel inverter with minimum output harmonics for electric/hybrid electric vehicle applications is proposed in this paper. Switching angles of switch devices are determined by selective harmonic elimination technique. So, the effect of low order harmonics are reduced, as a result the efficiency of system has improved. Moreover, the number of DC voltage sources that used in the proposed inverter is less than conventional multilevel inverters that leads to reduce the inverter costs. A fundamental frequency switching methods has been used for modulation of inverter and to produce a seven-level phase voltages. The effectiveness of the proposed system has been validated by simulation results on various conditions using PSCAD/EMTDC software.

Keywords: Multilevel Inverter, Fundamental Frequency Switching Method, Triplen Harmonic Compensation, Electric Vehicles (EVs)/Hybrid Electric Vehicles (HEVs).

Modeling and Control of an Integrated Power Electronics Interface for Plug-in Hybrid Electric Vehicles
by Omar Hegazy, Ricardo Barrero, Joeri Van Mierlo, Philippe Lataire

Vol. 7. n. 1, pp. 3254-3269

Abstract - Plug-in Hybrid Electric Vehicles (PHEVs) have been proposed as alternatives that can reduce fuel consumption with low driving costs compared to hybrid electric vehicles. In addition, they can operate like mobile energy storage units when idling to store energy and feed it back to the grid. When the vehicle is parked (at work or at home), the PHEV battery would be recharged from the power grid and would thus allow for a reduction in the overall fuel consumption. This paper proposes a novel integrated power electronics interface for PHEVs, which consists of a novel multi-device interleaved DC/DC converter (MDIC) and Eight-Switch Inverter (ESI), in order to reduce the cost, the mass and the size of the power electronics interface (PEI) used in PHEVs while yielding high performance at any operating mode. In the proposed topology, Eight-Switch Inverter (ESI) is able to function as a bidirectional single-phase AC/DC battery charger/ vehicle to grid (V2G) and to transfer electrical energy between the DC-link (connected to the battery) and the electric traction system as three-phase DC/AC inverter. In addition, a novel multi-device interleaved DC/DC converter is proposed for interfacing the ESI to a low-voltage input source (such as Fuel Cell and battery) in order to minimize the input current/output voltage ripples and to improve the efficiency of the DC system with lower passive components size. The proposed topology is designed and its dynamic performance is validated by using MATLAB/ Simulink. The analytical and simulation results related to this research are presented. Finally, the proposed topology is experimentally verified with results obtained from the prototypes that have been built and tested in our laboratory.

Keywords: Plug-In Hybrid Electric Vehicles, Multi-Device Interleaved Converter (MDIC), Eight-Switch Inverter (ESI), Indirect Field Oriented Control (IFOC), Particle Swarm Optimization (PSO), Dual-Loop Controller, PI Controller.

Feature Extraction Method Based on Pulse-Coupled Neural Networks for Ultra High Frequency Partial Discharge in Transformers
by Ju Tang, Jiabin Zhou, Xiaoxing Zhang, Jiagui Tao

Vol. 7. n. 1, pp. 3270-3279

Abstract - Pattern recognition of transformer partial discharge (PD) is significant in understanding the essence of defects within the transformer and in guiding its maintenance. Based on the characteristics of PD defects, four typical single defects were designed for the present paper. Here, PD three-dimensional (3D) patterns were constructed based on the mass samples gathered using the ultra high frequency and high-speed sampling systems. The pulse-coupled neural network method was used in PD feature extraction, which transformed the PD 3D grayscale images into binary images. Then, we calculated the entropy sequence of binary images and extracted the statistical characteristics of the entropy sequence as the PD feature vectors. Finally, the back propagation neural network was adopted for pattern recognition. The recognition results show that the proposed method can effectively extract entropy sequence as new PD features and improve the accuracy of pattern recognition rate.

Keywords: Partial Discharge (PD), Ultra High Frequency (UHF), Pulse-coupled Neural Networks (PCNN), Transformer, Feature Extraction, Entropy Sequence.

A Novel Two-Step Minimal-Power-Dissipation Control Method for Magnetically Levitated Planar Motor
by Gan Zhou, Rui Bo, Xueliang Huang, Hao Jiang

Vol. 7. n. 1, pp. 3280-3289

Abstract - Magnetically levitated planar motors have wide application prospects in many high-precision industrial apparatus, such as wafer steppers. Based on the dq (d-axis and q-axis) transformation and the Moore-Penrose inverse transformation, a new minimal-power-dissipation (MPD) control method for the linear actuator used in planar motors is systematically presented. Moreover, it is proven that the inverse of Park’s transformation is exactly the MPD transformation when the zero-axis current equals to zero. More importantly, we put forward a novel two-step MPD control method for planar motors for the first time. Compared with previous studies, this method can calculate the force allocation among all actuators in its first step. Therefore, taking the prototype as an example, this two-step method can be used to analyze the relationship between the actuator-force allocation and the power dissipation, and then optimize the mechanical topology of the mover to reduce the power dissipation. The validity of this two-step method is verified with a detailed analytical proof. The same approach can be applied to similar types of planar motors with the structure of symmetrical three-phase windings.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved

Keywords: Linear Actuator, Magnetically Levitated, Minimal Power Dissipation, Planar Motor.

Defining Design Criteria of an Axial Flux Permanent Magnet Synchronous Generator
by Unal Kurt, Guven Onbilgin, Okan Ozgonenel

Vol. 7. n. 1, pp. 3290-3296

Abstract - Axial flux permanent magnet machines using high energy magnets have been increasingly employed for several applications. This work presents a new design procedure for an axial flux permanent magnet synchronous generator (AFPMSG) based on Taguchi experimental design. Interior radius, thickness of the magnet, pole utilization factor and pole number are the analyzed factors. Air-gap magnetic flux density (AGMFD) is chosen as response variable. The aim of the work is to minimize the analyzed factors and maximize the response variable, AGMFD. Simplex algorithm was used to optimize the input variables. According to optimization procedure, interior radius at 39, thickness of the magnet at 8, pole utilization factor at 0.8 and pole number at 8 were chosen as optimized variables. Finite element approach was then used to validate the results.

Keywords: Axial Flux Permanent Magnet Synchronous Generator, Taguchi Design, Optimization, Finite Element.

IPM Synchronous Motor for Traction Applications: Performance Analysis Considering Hysteresis Loop Characteristics Variation
by J. Soleimani, M. Barzegari Bafghi, M. Shojaeepoor

Vol. 7. n. 1, pp. 3297-3303

Abstract - Recently, Inner Permanent Magnet (IPM) Synchronous Motors are known as a good candidate for hybrid electric vehicle traction drive application due to their unique merits like little volume, light weight, high efficiency and power factor and high reliability. However, behavior of this motors is quite depending on hard magnetic material hysteresis loop characteristics, configuration and volume in rotor structure. This paper discusses the effect of hard magnetic material hysteresis loop characteristics on d-q equivalent circuit model, also presents a novel structure of inner PMSM for traction application with double layers of fragmental buried rotor magnets in order to achieve less torque ripple, iron losses and cogging torque, higher power factor and improving the electromagnetic torque per ampere and simulation of this motor. Thus, in order to extract the output values of motor and sensitivity analysis on hysteresis loop characteristics using 3D-Finite element model, then shows the back EMF, power factor, cogging torque, flux density, torque per ampere diagram of the IPM synchronous motor with variation of hard magnetic material hysteresis loop characteristics in rotor structure. This study can help designers in design approach of such motors.

Keywords: Hysteresis Loop, IPM Synchronous Motor, Design; 3D-FEM Model, Dynamic Model, Traction.

Implementation of H∞Multivariable Feedback Control for Permanent Magnet Synchronous Motor Drive System
by S. Hassaine, S. Moreau, B. Mazari

Vol. 7. n. 1, pp. 3304-3313

Abstract - This paper presents a robust speed and current controllers scheme of Permanent Magnet Synchronous Motor (PMSM). It is to achieve accurate control performance in the presence of load torque and plant parameter variation. Application of H∞ technique in the controller creates proper characteristics, which ensures controller robustness. The robustness of the controller is based on consideration motor parameters uncertainty characteristic introduced by H∞ technique. The proposed controller is based in an approach of PMSM model linearization. A methodology of synthesis multivariable robust control is presented. Application of H∞ control with using of weighting functions. The simple and practical control scheme is easily implemented on a PMSM driver using TMS320LF2407 DSP. The effectiveness of the proposed multivariable robust speed control approach is demonstrated by experimental results.

Keywords: PMSM, Multivariable Robust Control, H∞ Approach, Implementation.

Analytical Design of the Double Rotor Switched Reluctance Motor with Optimal Pole Arc Values
by Aravind CV, M. Norhisam, M. R. Zare, I. Aris, M. H. Marhaban, M. Nirei

Vol. 7. n. 1, pp. 3314-3324

Abstract - The paper presents the switched reluctance motor with double rotor structure. Unlike the conventional SRM where the reduction of air-gap introduces mechanical intolerance the proposed structure reduce the air-gap length by using a double rotor structure and thereby increasing the torque generating capability. A detailed analysis on the concept of double rotor structure is introduced. The pole arc constraints are discussed and the values based on the analytical design parameters are derived. A two-dimensional FEA analysis is performed on the proposed structure to verify the design structure. A comparative evaluation on some characteristics of a conventional SRM with that of the double rotor SRM for the same design value is presented towards the end of the paper to demonstrate the effectiveness of the proposed structure in terms of torque generating capability, reduction in ripple, improved THD and ﬂexibility in winding design.

Keywords: Reluctance Motors, Double Rotor, Ripple Minimisation, Pole Arc Design, Feasibility Triangle.

Integral Backstepping Control for a PMLSM Using Adaptive RNNUO
by Chih-Hong Lin

Vol. 7. n. 1, pp. 3325-3333

Abstract - Due to uncertainties exist in the applications of the a permanent magnet linear synchronous motor (PMLSM) servo drive which seriously influence the control performance, thus, an integral backstepping control system using adaptive recurrent neural network uncertainty observer (RNNUO) is proposed to increase the robustness of the PMLSM drive. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM servo drive. Then, an integral backstepping approach is proposed to control the motion of PMLSM drive system. With proposed integral backstepping control system, the mover position of the PMLSM drive possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic reference trajectories. Moreover, to further increase the robustness of the PMLSM drive, an adaptive RNN uncertainty observer is proposed to estimate the required lumped uncertainty. The effectiveness of the proposed control scheme is verified by experimental results.

Keywords: Permanent Magnet Linear Synchronous Motor, Recurrent Neural Network, Integral Backstepping Control.

Robust Nonlinear Receding Horizon Speed Control of Permanent Magnet Synchronous Machine with Armature Current Limitations
by R. Hedjar

Vol. 7. n. 1, pp. 3334-3341

Abstract - This paper deals with robust nonlinear speed control of permanent magnet synchronous machine with currents limitations. The controller is based on the continuous time minimization of the predicted tracking error and no online optimization is required. An integral action is incorporated in the loop to increase the robustness of this control scheme against load torque variations. The proposed nonlinear controller permits to achieve asymptotic speed tracking in presence of unknown load torque, resistance variations and current limitations. Simulations are performed to validate the tracking performance of the proposed controller.

Keywords: Receding-Horizon Control, Robust Speed Control, Current Limitation and PMSM.

Modeling and Detection of Inter-turn Fault in Induction Motors Using Wavelet Entropy Estimation
by Jagadanand G., Lalgy Gopi, Saly George, Jeevamma Jacob

Vol. 7. n. 1, pp. 3342-3351

Abstract - This paper proposes a new method to detect inter-turn faults in an induction motor, which works impeccably even under dynamic load conditions of the motor. A mathematical model for inter-turn faults has been developed using reference frame transformation theory. The model is simulated in MATLAB/ SIMULINK®. A unique characteristic of energy versus entropy obtained from the stator current is identified as a possible feature for the detection of fault. The energy and entropy are extracted by a wavelet based technique. This method will overcome the issues such as averaging problems associated with classical signal processing techniques like short-time Fourier transform. The proposed method is verified in the laboratory set up as well and found to be matching with the simulation results. It can be seen that this scheme for inter-turn fault detection is simple and is capable of providing reliable fault detection even under dynamic operating conditions.

Keywords: Induction Motors, Mathematical Modeling, Inter-turn Faults, Wavelet Transform, Energy And Entropy, Fault Detection.

Linkage and Inductance Characteristics of a Double-Stator Switched Reluctance Machine
by Mohammadali Abbasian, Mohammadhossein Safavipour

Vol. 7. n. 1, pp. 3353-3357

Abstract - Double-stator switched reluctance machine is a novel switched reluctance machine with two stators and one rotor. Compared to conventional switched reluctance machine, in this geometry, much greater percentage of the electromagnetic forces contributes to the motion, thus a great improvement in torque density is achieved. The magneto-motive force orientation of the coils in the double-Stator switched reluctance machine is such that a short flux path is always guaranteed. This paper presents the flux linkage and inductance measurement of a double-stator switched reluctance machine for the first time. Finite element method is performed to calculate the flux linkage and the inductance of a double-stator switched reluctance machine. An experimental prototype of the double-stator switched reluctance machine is then used to evaluate the calculated results. For this purpose, a flux-measurement method based on voltage integration is applied to the double-stator switched reluctance machine. The inductance of stator coils is then calculated using derivation of measured flux linkage. Experimental results verify the results obtained by finite element method.

Keywords: Switched Reluctance Machines, Double Stator, Finite Element Method, Measurement, Flux Linkage, Inductance.

Partial Discharge Signal Classification Utilizing Time-Frequency Representation and Two Directional 2DPCA
by Ruijin Liao, Ke Wang, Lijun Yang, Lei Yuan, Jian Li

Vol. 7. n. 1, pp. 3358-3369

Abstract - In this paper, a new feature extraction algorithm is presented, based on a time-frequency representation technique S transform (ST) and two-directional two-dimensional principal component analysis ((2D)²PCA), which enables the classification of partial discharge (PD) UHF signals generated by different artificial defects utilizing a support vector machine (SVM) classifier. S transform (ST) is firstly employed to obtain a time-frequency representation of the recorded UHF signals. Then, (2D)²PCA is applied to compress the ST amplitude (STA) matrices to extract various feature vectors with different (d₁, d₂) combinations, i.e. (5, 5), (5, 10), (10, 5) and (10, 10). In the training phase, LIBSVM toolbox is used to construct the SVM classifier, and the two parameters of SVM are selected by particle swarm optimization (PSO) algorithm. After that the PSO-SVM classifier is trained using the selected parameters. During testing, the PD classes are recognized by means of the trained PSO-SVM. Besides, a comparison with the traditional three-layer back propagation neural network (BPNN) is given in this study. Experimental results show that the classification accuracies by PSO-SVM are all higher than that by BPNN under four circumstances of (d₁, d₂) combinations. The success rates of the PSO-SVM with the four feature vectors are above 94% in all cases, and the highest classification accuracy 97.67% is obtained with the (10, 5) combination. Furthermore, by applying (2D)²PCA, the feature dimension can be dramatically decreased compared with that of the obtained STA matrices, and the most important information of original data is also preserved. It can be found that the proposed feature extraction and classification algorithm can be effectively applied to PD pattern recognition.

Keywords: Partial Discharge, Pattern Recognition, S Transform, (2D)²PCA, Support Vector Machine, Particle Swarm Optimization.

Branch Outage Simulation Based Contingency Screening by Gravitational Search Algorithm
by O. Ceylan, A. Ozdemir, H. Dag

Vol. 7. n. 1, pp. 3370-3379

Abstract - Power systems contingency analysis is an important issue for electric power system operators. This paper performs branch outage simulation based contingency screening using a bounded network approach. Local constrained optimization problem representing the branch outage phenomena is solved by the gravitational search algorithm. The proposed method is applied to IEEE 14, 30, 57, and 118 Bus Test systems and its performance from the point of capturing violations is evaluated. In addition, false alarms and the computational accuracy of the proposed method are also analyzed by using scattering diagrams. Finally, the proposed gravitational search based contingency screening is compared with full AC load flow solutions from the point of computational speed.

Keywords: Branch Outage, Contingency Studies, Gravitational Search Algorithm, Optimization.

Stochastic Optimal Wind Power Bidding Strategy in Short-Term Electricity Market
by Weihao Hu, Zhe Chen, Birgitte Bak-Jensen

Vol. 7. n. 1, pp. 3380-3390

Abstract - Due to the fluctuating nature and non-perfect forecast of the wind power, the wind power owners are penalized for the imbalance costs of the regulation, when they trade wind power in the short-term liberalized electricity market. Therefore, in this paper a formulation of an imbalance cost minimization problem for trading wind power in the short-term electricity market is described, to help the wind power owners optimize their bidding strategy. Stochastic optimization and a Monte Carlo method are adopted to find the optimal bidding strategy for trading wind power in the short-term electricity market in order to deal with the uncertainty of the regulation price, the activated regulation of the power system and the forecasted wind power generation. The Danish short-term electricity market and a wind farm in western Denmark are chosen as study cases due to the high wind power penetration here. Simulation results show that the stochastic optimal bidding strategy for trading wind power in the Danish short-term electricity market is an effective measure to maximize the revenue of the wind power owners.

Keywords: Optimal Bidding Strategy, Short-Term Electricity Market, Stochastic Optimization, Wind Power Generation, Monte Carlo Method.

Designing and Experimenting an Auto-Adaptive Controller for a Stand-Alone Photovoltaic System with Hybrid Storage
by T. A. Singo, A. Martinez, S. Saadate

Vol. 7. n. 1, pp. 3391-3400

Abstract - An auto-adaptive controller has been successfully designed and implemented in a stand-alone PV system with a hybrid storage that combines batteries and ultracapacitors. Our controller, based on a Perturb and Observe (P&O) algorithm, gives better results and enhances considerably the efficiency, by making Maximum Power Point Tracking (MPPT) more stable and faster. Moreover, it is demonstrated that ultracapacitors are useful to face peak power demand and allow batteries to operate under better conditions because deep discharges are strongly reduced. The algorithm has been successfully implemented via a digital controller based on a dSPACE card. Results are validated experimentally on a benchmark prototype under real climatic conditions, particularly for low irradiation. Finally, performances and advantages of the global system are discussed in the paper.

Keywords: PV Panels, Hybrid Storage, Auto-Adaptive Controller, P&O Algorithm, Benchmark Prototype.

Hamilton Energy Theory based Coordinated Control of Generator Excitation and TCSC
by Fang Shi, Jie Wang

Vol. 7. n. 1, pp. 3401-3407

Abstract - A coordinated control design algorithm based on Hamilton energy theory, which has a simple physical meaning and is easily understandable to operators, is presented in this paper. The conditions how can the Hamilton function qualify as a real Lyapunov function are discussed and a stabilized control strategy is proposed via a concept of energy balancing and damping injection. A kind of long distance transmission power system, which can be equivalently seen as single machine infinite bus (SMIB) system, is represented into pseudo-generalized Hamilton system and the coordination of generator excitation and TCSC controllers is realized immediately with the proposed algorithm. The incorporation of decentralized input control signals will lead to a better stabilized performance. To illustrate the proposed approach, a simulation experiment has been performed for a practical power system. The results of the proposed coordinated control strategy are compared with previous decentralized one, which demonstrate the effectiveness and practicability of the coordinated controller proposed in this paper.

Keywords: Pseudo-Generalized Dissipative Hamilton System, Lyapunov Function, Asymptotically Stability, Coordinated Control, TCSC.

Effects of Corona Ring Design and its Location on Electric Field and Potential Distribution along 400kV and 1000kV Contaminated Insulator String
by S. M. Hassan Hosseini, H. Samadzadeh

Vol. 7. n. 1, pp. 3408-3413

Abstract - This paper demonstrates the study of three-dimensional (3D) electric field and potential distribution along the surface of rubber insulators under contamination condition with water droplets. Of particular interest to this investigation is the effect of corona ring and its number and location on the electric field distribution along the insulator. A number of 400 kV as well as 1000 kV insulator configurations are designed and modeled. It is supposed that the insulator surface has been covered and contaminated with water droplets. Simulations are carried out using Maxwell.13 software which provides a 3D solving of electromagnetic problems using finite element method (FEM). Simulation results exhibits that when two corona rings are used concurrently, the potential and electric field distribution would be more uniform around and on the surface of contaminated insulator.

Keywords: Three Dimensional Simulation, Contaminated Insulator, Water Drops, Corona Ring.

Firefly Algorithm for Reliable/Emission/Economic Dispatch Multi Objective Problem
by K. Chandrasekaran, Sishaj P Simon

Vol. 7. n. 1, pp. 3414-3425

Abstract - The economic dispatch (ED) problem plays vital role in the power system optimization problem. Recently the power system stresses the need for economic, non-polluting and reliable operation. This paper solves the multi-objective ED problem with three conflicting functions such as fuel cost, emission and reliability level of the system. The problem is formulated as a non-smooth and non convex problem when the valve-point effects of thermal units are considered in the proposed reliable, emission, economic dispatch (REED) problem. This paper presents a multi objective optimization methodology for solving the newly developed REED problem using a fuzzy adapted firefly algorithm (FAFF). The firefly algorithm (FF) is used to schedule the optimal dispatch and fuzzy membership approach is used to find a best compromise solution from the Pareto optimal set. The methodology is validated on 6, 10 unit system and IEEE RTS 24 bus system and the results are compared with the existing literature. The results clearly show that the proposed method is able to produce well distributed Pareto-optimal solutions when compared with other methods reported in the literature.

Keywords: Firefly Algorithm, Reliable, Emission And Economic Dispatch Problem, Fuzzy Membership Approach.

Dynamic Economic Dispatch Considering Network Power Losses Based on Gravitational Search Algorithm
by H. Maskani, M. Yazdani, S. Alishahi, H. Falaghi

Vol. 7. n. 1, pp. 3426-3434

Abstract - Economic dispatch at minimum production cost is one of the most important subjects in the power system operation, which is a complicated nonlinear constrained optimization problem. In addition, dynamic economic dispatch is one of the important optimization problems in power system operation, which is used to determine the optimal combination of power outputs of all generating units to minimize the total fuel cost while satisfying various constraints over the entire dispatch periods. To solve the dynamic economic dispatch problem, it is assumed that a thermal unit commitment has been previously determined. In this paper, a new method is proposed to solve the dynamic economic dispatch problem using gravitational search algorithm based on swarm-based optimization. This algorithm is applied to a complex dynamic economic dispatch problem for 6-unit and 15-unit power systems with a 24-h load demand at each 1-h time intervals. Comparing gravitational search algorithm results with other methods' results that reported in literature shows the ability of gravitational search algorithm to reach better solutions.

Keywords: Dynamic Economic Dispatch, Gravitational Search Algorithm, Power Loss, Swarm-Based Optimization, Total Fuel Cost.

International Review of Electrical Engineering - Papers- Part B

Probabilistic LV Distribution Network Design for Aggregated Light Industrial Loads
by P. van Rhyn, J.H.C. Pretorius, R Herman

Vol. 7. n. 1, pp. 3435-3442

Abstract - This paper studies the statistical load modeling of a selected group of light industrial consumers as typically found within modern light industrial development nodes such as industrial parks. A statistical model using beta-distributed constant current load at daily instants of maximum demand was presented by Van Rhyn, Pretorius and Herman [1]. It has been established that light industrial consumer loads are stochastic of nature, similar to previously reported residential load, and that load uncertainty can be described mathematically at a specific interval in time using a beta probability density function (pdf) [2].This paper shows how groups of different light industrial consumers as found in modern industrial parks or industrially zoned areas can be summated statistically to obtain a system maximum demand of the composite load. A simple algorithm can be used to calculate the beta parameters of individual or composite light industrial loads at daily instances of maximum demand as reported by Van Rhyn [3]. These parameters can be applied to an existing statistical voltage regulation model to design and specify low voltage (LV) distribution components for a grouped loading case study.

Keywords: Load Modeling, Statistical Methods, Beta Distribution, Light Industrial Electrification.

Multi-Objective Environmental Optimal Power Flow Considering Transient Stability Improvement
by Ramin Moslemi, Masoud Esmaili, Heidar Ali Shayanfar, Lingfeng Wang, Robert C. Green

Vol. 7. n. 1, pp. 3443-3453

Abstract - In recent years, global concerns about environmental issues and pollutant emissions have been incorporated into the optimal power flow frameworks used in electricity power markets. Therefore, the generation of participant generators in the power market is changed to fulfill new environmental requirements. While reducing emissions, these requirements may exacerbate the transient stability margin due to increasing the generation of critical generators. This leaves the system vulnerable against serious faults like short-circuit in transmission lines. In this paper, by employing multi-objective optimization based on epsilon-constraint, a transient stability index termed corrected transient energy margin is imposed on the environmental optimal power flow to prevent transient stability deterioration. In the proposed multi-objective framework, the total op-eration cost is minimized as the main objective function while emissions as the second objective function are minimized and the transient stability margin as the third objective function are max-imized at the same time. Pareto solutions are obtained and a fuzzy decision maker picks up the best Pareto solution. To verify the efficiency of the proposed method, it is tested on the New-England test system. Results indicate that the optimal point obtained by the proposed approach satisfies power system economic, environmental, and security needs simultaneously.

Keywords: Multi-Objective Optimal Power Flow, Corrected Transient Stability Function, Emissions, Multi-Objective Mathematical Programming.

Artificial Intelligence Forecast of PV Plant Production for Integration in Smart Energy Systems
by Mikhail Simonov, Marco Mussetta, Francesco Grimaccia, Sonia Leva, Riccardo E. Zich

Vol. 7. n. 1, pp. 3454-3460

Abstract - Computation techniques play an important role in most engineering problems in which optimization problems have to be faced. Energy management operations represent one of these cases where real-time energy production, transfer, storage and consumption need to be optimized. In this context renewable energy sources can be managed using evolutionary computation and other tools. In this light artificial neural network solution based on weather forecast can estimate energy flows combined with the event-driven variability encouraging photovoltaic integration with the electric power system.
This article discusses the role of these computational tools and some issues related to the variability and uncertainty in the operations where PV plants are potentially fully connected to the power grid in a future scenario.

Keywords: PV Forecasting, Renewable Energy, Smart Grids, Artificial Intelligence.

A Novel Approach for Optimal Determination of Number of Distributed Generation Units along with their Sizes and Locations
by M.R. Alemi, M. Fallahnejad, M. Sedighizadeh

Vol. 7. n. 1, pp. 3461-3469

Abstract - The optimal allocation of Distributed Generation (DG) has attracted many researchers’ attention recently due to its ability to obviate defects caused by improper installation of this equipment. This paper presents an advanced two-layer method for optimal determination of number, capacity and location of DG units in power systems. The interior layer which concerns with improvement of voltage profile and minimization of power losses and costs, determines the optimal locations and sizes; whilst, the exterior layer sets optimal number of DG units. Particle Swarm Optimization (PSO) and Clonal Selection Algorithm (CLONALG) are two methods which have been applied to either minimize or maximize different objective functions in previous studies. In this study, the Combination of Particle Swarm Optimization and Clonal Selection Algorithm (PCLONALG) is utilized as a solving tool in both layers to acquire superior solutions. The approach method has the preferences of both previous techniques. Finally, the application of the proposed technique is demonstrated in two typical networks. The experimental results illustrate that the two-layer method, without any simplifying assumptions, has an impressive ability to find the best number of DG units along with their best sizes and locations.

Keywords: Distributed Generation, Optimal Placement, Two-Layer Method, Power Losses, Voltage Profile.

Linear Programming for Optimal Sizing of DGs in MicroGrid Considering Loss of Power Supply Probability Technology
by H. A. Zamani, S. M. Ezzati, M. D. Farashah, E. Dahri, S. M. M. Tafreshi

Vol. 7. n. 1, pp. 3470-3477

Abstract - In this research, a methodology to execute the best unit sizing for Distributed Energy Resources (DER) in MicroGird (MG), has been improved. On the basis of Linear Programming (LP), a renovated optimal unit sizing technique was improved to estimate the optimum system formation that can obtain the customers needed Loss of Power Supply Probability (LPSP) with a minimum Cost of Energy (COE). The suggested method consequences are confirmed for single source DG and hybrid DG with results obtained from HOMER and Genetic Algorithm (GA) for the similar test systems.

Keywords: Optimal Unit Sizing, Cost of Energy, Loss of Power Supply Probability, Linear Programming.

Probabilistic Approach to Reliability Assessment of Electric Power System Containing Distributed Generation
by Shengyou Xu, Minyou Chen, Li Ran

Vol. 7. n. 1, pp. 3478-3485

Abstract - The application of renewable energy in electric power system is growing rapidly due to enhanced public concerns for adverse environmental impacts and escalation in energy costs associated with the use of conventional energy sources, distributed generation (DG) such as wind is being recognized as an encouraging and cost effective generation source both in large grid connected systems and small isolated applications. Power output from DG is not readily controllable. High distributed generation penetration can lead to high-risk levels in power system reliability and stability. In order to maintain the system stability, considerable effort has been devoted to the economic evaluation of power systems utilizing renewable energy, comparatively less emphasis has been given to the related reliability analyses of such systems particularly considering the appreciate volume and location of possible distributed generation. This paper presents a probabilistic evaluation approach that can incorporate the impacts on reliability of new energy utilization in electric power systems, the basic concepts, indices, and special issues in the probabilistic system reliability assessment are discussed, several steps designated as equivalent simplification and the islanded reliability calculating method are proposed and discussed. Firstly the equivalent failure rate and failure duration time for a given system is determined using system equivalent simplification, then, the islanded probability at a load point for a given system containing distributed generation is calculated using probabilistic approach, at last, different operating strategies were compared and the resulting benefits were evaluated. The analysis results of example show that the system reliability has been improved significantly when DG is connected to the power system, furthermore, the system reliability can be enhanced more if the DG with more capability is located at the feeder line which bears more loads. Therefore, the probabilistic evaluation approach is feasible for the operator to decide the appreciate capability and detailed location of possible DG in electric power systems so that a desired reliability level is obtained.

Keywords: Renewable Energy, Distributed Generation, System Reliability, Probabilistic Approach.

Solution for Multi-Objective Reactive Power Optimization Problem using Fuzzified Particle Swarm Optimization Algorithm
by D. Silas Stephen, M. Devesh Raj, P.Somasundaram

Vol. 7. n. 1, pp. 3486-3494

Abstract - This paper presents a more efficient method for solving the Multi-Objective Reactive Power Optimization (MORPO) problem. The MORPO problem is formulated as a non-linear constrained true multi-objective optimization problem with competing objectives the transmission loss, voltage deviation and the voltage stability index. The solution methodology is a combined application of Fuzzy Logic strategy incorporated in Particle Swarm Optimization (PSO) algorithm, termed as Fuzzified PSO (FPSO). The performance of the proposed approach was tested on a standard IEEE 30-bus system and is compared with Strength Pareto Evolutionary Algorithm (SPEA), Tabu search (TS), and Fuzzy Guided Tabu Search (FGTS) algorithm. The result shows that the proposed method has greater potential in the evolutionary computation for solving the MORPO problem.

Keywords: Multi-Objective Reactive Power Optimization (MORPO), Particle Swarm Optimization (PSO), Fuzzy Logic, Voltage Stability.

Stabilization of Multi-Machine Power Systems Using Craziness based Particle Swarm Optimization and Harmony Search Algorithms
by M. R. Banaei, S.Abbasi, E. Salary

Vol. 7. n. 1, pp. 3465-3504

Abstract - Inter-area oscillations are critical to optimal power flow and stability in a power system. PSSs are effective damping devices, as they provide auxiliary control signals to the excitation systems of generators. The proper selection of PSS parameters to accommodate variations in the power system dynamics is important and a challenging task particularly when several PSSs are involved. This paper demonstrates using of both CRPSO and HS algorithms for the simultaneous stabilization of multi-machine power system via single-setting power system stabilizers. The proposed approach employs algorithms to search for optimal setting of PSS parameters that shift the system eigenvalues associated with the electromechanical modes to the left in the s-plane. In this paper for multi-machine power systems, the participation factors (PFs) are used to design of PSS optimum location, and then the eigenvalue analysis is applied. Simulation results carried out by MATLAB/SIMULINK show the effectiveness and robustness of the proposed PSSs to damp out the local modes of oscillations.

Keywords: PSS, PF, CRPSO, HS.

Lightning Transient Modeling of Wind Turbine Towers
by Xiaoqing Zhang, Chenhua Liu

Vol. 7. n. 1, pp. 3505-3511

Abstract - This paper proposes a circuit model for lightning transient analysis of wind turbine (WT) towers. The model represents the WT tower as a discrete multiconductor gird. An efficient procedure is given to determine the circuit parameters of the multiconductor grid, in which the electromagnetic couplings between the grid branches in different spatial positions can be taken into account. Based on the circuit parameters, the discretization π-type circuit units are employed to build the equivalent circuit of the multiconductor grid and then the lightning transient responses are obtained by solving the circuit equations. An experiment with a laboratory-scale WT tower has been made for checking the validity of the circuit model. Also, the circuit model has been applied to lightning transient analysis of an actual WT tower.

Keywords: Lightning Strike, Wind Turbine Tower, Circuit Parameter, Multiconductor Grid, Transient Simulation.

Power System Stability Enhancement Using SSSC
by M. R. Banaei, E. Salary

Vol. 7. n. 1, pp. 3512-3522

Abstract - In this paper the ability of the STATCOM and SSSC supplementary controllers to en¬hance the dynamic stability of a single-machine infinite-bus power system using linearized Phil¬lips-Heffron model is compared. These controllers are tuned to simultaneously shift the undamped electromechani¬cal modes to a prescribed zone in the s-plane according to the eigenvalue-based multi-objective function comprising the damping factor and the damp¬ing ratio using particle swarm optimization technique that has a strong abil¬ity to find the most optimistic results. Simula-tion results have been carried out using MAT¬LAB/SIMULINK show that the SSSC performance is better than STATCOM and it provides higher damping than that of the STATCOM.

Keywords: Single-Machine İnfinite-Bus, SSSC, Dynamical Stability.

Precise Modeling and Detection of High Impedance Faults in Microgrid System Based on Residual Current Harmonic Analysis
by L. Eslami, R. Keivanian

Vol. 7. n. 1, pp.3523-3531

Abstract - In all distribution systems, usually it is possible for energized conductors to come into contact with the outside substances like trees, building walls and also surfaces below them. This situation, known as High Impedance Fault (HIF), is very perilous for human life and may result in electricity congestion, burning or ignition by the arc or the substance heat. Moreover, a part of the energy produced by the power company is lost and this loss causes some damage in power supply plants. Common relaying in distribution systems only detects short circuit conditions and thus very considerable amount of generated electric power flows through the earth without achieving by the load. Because the occurrence of the HIF is accompanied by very slight increase in load current, it is very difficult for protection equipment to detect it. So it can be misinterpreted as a usual increase in the value of load current. Although various approaches for detecting high impedance faults have been presented until now, most of them are complicated or difficult in implementation or have been tested on power distribution networks which don’t use renewable energies as a primary source. In this paper, we have proposed a novel approach for high impedance fault detection using harmonic analysis of current in a microgrid system. Diverse simulations in EMTPWorks environment confirms that our proposed approach has a great accuracy while keeping simplicity in implementation.

Keywords: High Impedance Fault, Fault Detection, Microgrid System, EMTPWorks.

Single Phase Fault Distance Estimation in Medium Voltage Distribution Network Based on Traveling Waves
by Šeila Gruhonjić Ferhatbegović, Ante Marušić, Ivica Pavić

Vol. 7. n. 1, pp. 3532-3541

Abstract - The subject of this research is the location of single phase fault in the medium voltage distribution network which is independent of the neutral point treatment. Observed transient methods use currents and voltages in transient conditions during process of discharging and charging capacity of the network at the moment of fault occurrence. Transient conditions in medium-voltage distribution network are limited duration, up to several cycles from the moment of fault occurrence. High-frequency transients are related to traveling waves. The implementation of these methods, require a minimum sampling frequency of 1 MHz. In the application of low ]frequency transients, the problem is transient attenuation for higher values of fault resistance, so these methods are not reliable for single phase fault with fault resistance of greater than 250 ohms. The advantage of method based on traveling waves is independence of fault resistance which may have significant values in the case of single phase faults in the distribution network.

Keywords: Single Phase Fault, Medium Voltage Distribution Network, Transients, Fault Location.

Blended Crossover Continuous Ant Colony Optimization and Stability Index Tracing for Effective FACTS Devices Installation
by Z. Hamid, I. Musirin, M. N. A. Rahim

Vol. 7. n. 1, pp. 3542-3553

Abstract - Recently, the two commonly implemented techniques for installing Flexible AC Transmission System (FACTS) devices are optimization approach and sensitivity analysis, although there are lots of other methods available for the same purpose. Alternatively, there are also various power tracing methods developed by researchers, unfortunately, the application is rather limited as they are only applied for transmission service pricing, especially in deregulated power system. By incorporating the tracing algorithm, this paper intends to present a novel method for determining the exact locations for FACTS devices placement, that is, Fast Voltage Stability Index Load Tracing (FVSI-LT). After experimentation on IEEE 57-bus reliability test system (RTS) considering normal and multi-contingencies condition, it is revealed that the proposed method provides a sense of reliability in terms of voltage stability enhancement while at the same time proves its capability to be applied into real system. Moreover, a new hybrid algorithm, Blended Crossover Continuous Ant Colony Optimization (BX-CACO) has also been proposed and it is observed that this algorithm reflects an impressive performance in terms of computation time and solution optimality after comparing with other Artificial Intelligence (AI) algorithms.

Keywords: BX-CACO, FACTS Devices, FVSI-LT, Power Tracing.

Using Clonal Selection Algorithm for Optimal Placement and Sizing of Unified Power Flow Controllers in Deregulated Power Systems
by A. Ramezani, Y. Ramezani, A. A. Ramezani, M. Ramezani

Vol. 7. n. 1, pp. 3554-3561

Abstract - This paper presents Clonal Selection Algorithm (CSA) to obtain the optimal location and parameters of Unified Power Flow Controller (UPFC) in deregulated electric power system. UPFC has great flexibility that can control the active and reactive power flow and bus voltages, simultaneously. UPFC is applied to maximize the system loadability subject to the transmission line capacity limits. The results of the proposed optimization problem are compared to Harmony Search algorithm (HSA) that they were evaluated in our prior work. These results are compared with those obtained from CSA to show the effectiveness of the proposed method in finding the best solution for the optimization problem. The proposed approach is conducted and tested on IEEE 9-bus and IEEE 14-bus test systems. The results show that the loadability of the power transmission system can be effectively enhanced through the optimal location and proper parameters selection of the UPFC.

Keywords: Power System Loadability, Unified Power Flow Controller (UPFC), Harmony Search Algorithm (HSA).

A Detailed Comparison of Cumulant-based Probabilistic Power Flow Methods
by Duong D. Le, C. Bovo, A. Berizzi, E. Ciapessoni, D. Cirio, A. Pitto

Vol. 7. n. 1, pp. 3562-3573

Abstract - The probabilistic power flow methodology deals with the uncertainties in power systems. Compared to the traditional deterministic power flow, this approach provides the overall spectrum of all probable values of the desired output variables. In this paper, the methods based on the properties of cumulants of random variables are considered. An in-depth analysis of such cumulant-based probabilistic power flow calculations is presented. A comparison of their features is given in detail through both a theoretical analysis and some case studies. Results on IEEE 14-bus and IEEE 300-bus Test Systems are presented and compared taking as benchmark the results obtained by the Monte Carlo methodology. Moreover, suitable suggestions to the exploit their features in the different power system applications are given. Further researches on these methods are also being developed to increase the accuracy and the computational efficiency.

Keywords: Probabilistic Power Flow, Cumulants, Gram-Charlier Series Expansion, Von Mises Function.

Adaptive Least Squares Support Vector Machines Method for Short-term Load Forecasting Based on Mutual Information for Inputs Selection
by Miloš B. Stojanović, Miloš M. Božić, Milena M. Stanković, Zoran P. Stajić

Vol. 7. n. 1, pp. 3574-3585

Abstract - The accuracy of load forecasts has a significant effect on many aspects of power systems nowadays, such as power systems operations, economy management and control of power systems. Therefore, the electric utility corporation’s savings highly depend on their ability to provide precise load forecasts. In the past few years least squares support vector machines (LS-SVMs) have been successfully employed in electric load forecasting. However, the accuracy of LS-SVMs is highly related to the selection of inputs which forms the training data set. Recently, mutual information (MI) has been employed as a criterion in the regression tasks, mostly for feature selection and for the identification of real inputs in noisy data sets. This paper proposes a new methodology for adaptive training set inputs selection, based on MI computation between training set inputs and current forecasting input, aiming to, primarily, improve the quality of load forecasting. In this way for each prediction step a new training set is formed, one that fits the current forecasting scenario better. Accordingly, several LS-SVM forecasting models have been built, based on inputs selection according to the MI criterion, for hourly forecasting of electric load for one day ahead. As the experimental results show, this approach can lead to significant improvements in the accuracy of load forecasts being achieved, as well as a great reduction in the number of inputs in the training set.

Keywords: Inputs Selection, Mutual Information, Short - term Load Forecasting, Least Squares Support Vector Machines.

A Fault Direction Discrimination Scheme Based on Transients Generated by Faults in Multi-Branch Power Systems
by S. Milad Tayebi, Ahad Kazemi, Roshanak Rezaeipour

Vol. 7. n. 1, pp. 3586-3591

Abstract - This paper presents a transient based protection scheme to identify a faulted section in power systems. The proposed scheme based on wavelet coefficients of the transients generated by the fault is able to discriminate the direction of the fault using voltage signals only and avoids the need for installing current transformers (CTs). Therefore, the proposed scheme ensures complete immunity to saturation of CTs. In this paper, the fault direction identification can be achieved by two-ended measurements of voltages so that high-frequency transients generated by a fault are measured from two ends of a line. The proposed algorithm has the advantage of working properly in the case of all types of faults, different fault inceptions, different fault locations and fault resistances. The simulations have been carried out by ATP/EMTP program under various fault conditions and the results have been processed in MATLAB so that the validity of this method has been verified.

Keywords: Wavelet Transform (WT), Wavelet Coefficients (WTCs), Fault Direction, Traveling Waves.

A Honey Bee Foraging Approach to Optimal Capacitor Placement with Harmonic Distortion Consideration
by M. Sedighizadeh, F. Kalimdast

Vol. 7. n. 1, pp. 3592-3599

Abstract - This paper presents a particle swarm (Binary Honey Bee Foraging, BHBF) approach to achieve optimal capacitor placement in radial distribution systems. Harmonic distortion effects, discrete nature of capacitors, and different load levels are all taken into consideration in the problem formulation. Mathematically, the capacitor placement problem is a non-linear and non-differentiable mixed integer optimization problem with a set of equality and inequality operating constraints. Most conventional optimization techniques are incapable to solve this hard combinatorial problem, whereas BHBF algorithm is very suitable. The proposed solution method employs BHBF to search for optimal locations, types, and sizes of capacitors to be placed and optimal numbers of switched capacitor banks at different load levels. Computation procedures of applying the method to the capacitor placement problem are given in detail. The proposed approach has been implemented and tested on a distorted IEEE 9-bus test system with promising results. Results are compared with other evolutionary optimization algorithms such as Binary Particle Swarm Optimization (BPSO), and Genetic Algorithms (GA).

Keywords: Capacitor Placement, Harmonic Distortion, Harmonic Power Flow, Binary Honey Bee Foraging, (BHBF), Binary Particle Swarm Optimization (BPSO), Genetic Algorithms (GA).

Investigation of the Methods for Single Area and Multi Area Optimization of a Power System Dispatch Problem
by Senthil Krishnamurthy, Raynitchka Tzoneva

Vol. 7. n. 1, pp. 3600-3627

Abstract - The objective of the economic dispatch problem of electrical power generation is to schedule the committed generating units output so as to meet the required load demand while satisfying the system equality and inequality constraints. Most of the earlier reviews concentrated on the single area power system dispatch problem. The aim of this paper is to review the single area and multi area optimization of a power system dispatch problem considering the single criteria and multi-criteria methods and algorithms.

Keywords: Single Area Power System, Multi Area Power System, Power System Optimization, Economic Dispatch, Emission Dispatch, Multi-criteria Optimization, and Multi Area Economic Emission Dispatch.

A Study on Scheduling of Primary Frequency Control Reserve
by M. Rouholamini, M. Rashidinejad

Vol. 7. n. 1, pp. 3628-3637

Abstract - This paper presents the simultaneous scheduling of energy and primary frequency control reserve in transmission lines considering congestion constraint. A daily unit commitment problem subject to primary regulation reserve constraints is proposed in this paper. Here, a novel method is suggested to formulate the aforementioned problem. The proposed model has been structured as a Mixed Integer Non Linear Programming (MINLP) problem. Furthermore, the congestion constraint is considered via DC power flow which has been omitted in the previous researches. The proposed model is applied to determine the conceivability of primary frequency control provision. In this study, the market clearing structure is assumed as pay as bid. Finally, a four units case study and the conventional 39-bus New England test system are employed to demonstrate the effectiveness of the proposed methodology.

Keywords: Congestion, Frequency Deviation, Load Ramp Rate, MINLP, Primary Reserve, Simultaneous Scheduling.

BDA Fault Detection in Complex Electric Power Systems
by Yagang Zhang, Zengping Wang, Shuqiang Zhao

Vol. 7. n. 1, pp. 3638-3645

Abstract - The appearance of wide area measurement system provides a new idea for the design of power system protection. For the wide area adaptive backup protection, the fault element location and fault section definition in power grid are the preconditions of fixed value modification of relative backup protection. In this paper, the research mainly serves the wide area adaptive backup protection system, using the PMU real-time measurement information in wide area measurement system, considering the influence of random disturbance caused by the access of new energy sources to the power system and information missing, we will provide accurate and reliable BDA fault detection scheme in complex power systems.
Copyright © 2012 Praise Worthy Prize S.r.l. - All rights reserved

Keywords: Fault Detection, BDA, Phasor Measurement Unit, Lyapunov Theorem, Random Disturbance.

Static and Dynamic Security-Augmented Market-Based Generation Scheduling Using Multi-Objective Artificial Bee Colony Algorithm
by M. Gitizadeh, J. Aghaei

Vol. 7. n. 1, pp. 3646-3656

Abstract - After some destructive blackouts, voltage stability and collapse have become worldwide concerned problems for electricity energy networks. Also, with increased loading and utilization of power transmission systems, voltage stability has become a rising concern in electric power utilities. Static aspects of power system security, such as voltage security margin, cannot guarantee the secure operation of the power system. Besides, dynamic modeling and evaluation of power system security is a complex and time consuming task. In this regard, to cope with such problems, a multi-objective framework is proposed which concurrently considers static and dynamic aspects of power system security in the scheduling problem of electricity energy markets. This paper presents a new approach based on the Multi-Objective Artificial Bee Colony (MOABC) algorithm to solve a security augmented market-based generation scheduling. In the proposed multi-objective framework, generation offer cost, Voltage Security Margin (VSM) (as static security index) and linearized Corrected Transient Energy Margin (CTEM) (as dynamic security index) of system are considered as objective functions of market-based generation scheduling. The New England test system is used as an example to illustrate the practical application of this security-augmented energy market clearing mechanism.

Keywords: Market-Based Generation Scheduling, Multi-Objective Artificial Bee Colony (MOABC), Corrected Transient Energy Margin (CTEM), Voltage Security Margin (VSM).

An Efficient Non-Convex Power Dispatch Approach for Modern Thermal Units
by Po-Hung Chen, Deng-Fa Lin, Cheng-Chien Kuo

Vol. 7. n. 1, pp. 3657-3666

Abstract - This paper presents an efficient solution technique for solving the practical non-convex power dispatch problem of modern thermal units. The proposed approach, which combines a novel particle structure with an efficient encoding/decoding technique, can easily coordinate with various evolutionary algorithms such as genetic algorithm and particle swarm optimization. In this work, all constraints are incorporated and satisfied using the proposed encoding/decoding technique to prevent finding an infeasible solution and speed up convergence. Therefore, both solution quality and searching efficiency can be increased dramatically. Moreover, most nonlinear characteristics and constraints of modern thermal units, including generation limits, ramp rate limits, prohibited operation zones, transmission loss, and non-convex cost functions are all considered for practical applications. The proposed approach is applied with great success to four test systems including the actual Taipower 40-unit system. Test results of the proposed approach are compared with those of published methods. Experimental results reveal the attractive properties of the proposed approach in practical applications, namely, a highly optimal solution and robust convergence behavior.

Keywords: Non-Convex Power Dispatch, Particle Structure, Evolutionary Algorithms, Ramp Rate Limits, Prohibited Operation Zones.

Environmental/Economic Power Dispatch Using Multi-objective Honey Bee Mating Optimization
by Javad Javidan, Ali Ghasemi

Vol. 7. n. 1, pp. 3667-3675

Abstract - This paper presents a Multi-Objective Honey Bee Mating Optimization (MOHBMO) algorithm to solve the Economic Environmental Dispatch (EED) problem. The EED problem can be formulated as a nonlinear constrained multi-objective optimization problem. The three competing and non-commensurable fuel cost, pollutant emission and system loss objectives should be minimized simultaneously while fulfilling certain system constraints. For dealing with different solutions in multi-objective optimization problem, Pareto dominance concept is used to generate and sort the dominated and non-dominated solutions. The IEEE 6-generator 30-bus and IEEE 14-generator 118-bus test system are used to investigate the capabilities of the MOHBMO approach in finding optimal solution. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multi-objective optimization algorithms such as NSGA, NPGA, SPEA, MOPSO and MODE. The comparison with reported results of other multi-objective optimization algorithms reveals the superiority of the proposed MOHBMO algorithm and confirms its great potential in handling the multi-objective problems in power systems.

Keywords: Environmental/Economic Load Dispatch, MOHBMO Algorithm, Generation Unit Constraints, Multi-Objective Optimization.