S. F. Mekhamer

A Modified Particle Swarm Optimizer for the Coordination of Directional Overcurrent Relays

The coordination of directional overcurrent relays (DOCR) is treated in this paper using particle swarm optimization (PSO), a recently proposed optimizer that utilizes the swarm behavior in searching for an optimum. PSO gained a lot of interest for its simplicity, robustness, and easy implementation. The problem of setting DOCR is a highly constrained optimization problem that has been stated and solved as a linear programming (LP) problem. To deal with such constraints a modification to the standard PSO algorithm is introduced. Three case studies are presented, and the results are compared to those of LP technique to demonstrate the effectiveness of the proposed methodology.

Economic Dispatch Using an Enhanced Hopfield Neural Network

Abstract This article introduces some modifications to the conventional Hopfield neural network (HNN) to enhance its performance. A comprehensive study of the effect of the HNN parameters on the solution quality of the economic dispatch problem (EDP), as a case study, has been made. By investigating the describing curves, the best values for the HNN parameters are tuned. To further improve the solution quality, an adaptive correction factor is proposed and introduced to the EDP solution obtained by the HNN. To investigate the effect of the modifications on the solution quality of the EDP, three case studies are selected and solved. Comparisons of results are then made with others to prove the validity and effectiveness of the proposed modifications.

A new intelligent optimization technique for distribution systems reconfiguration

The loss minimization problem is one of the most important problems to save the operational cost in distribution systems. Therefore, more efficient approaches are required to handle such a combinatorial problem. This paper presents an efficient meta-heuristic method for reconfiguration of distribution systems. A Tabu Search (TS) algorithm is used to reconfigure distribution systems so that active power losses are globally minimized with turning on / off sectionalizing switches. TS algorithm is introduced with some modifications such as using a tabu list with variable size according to the system size; this should lead to robust algorithm, and prevent cycling. Also, a random multiplicative move is used in the search process to diversify the search toward unexplored regions. A new method to check the radial topology of the system is presented. The proposed method is applied to 32-node and 69-node distribution systems. The obtained results using the proposed TS approach are compared with results obtained using Simulated Annealing (SA) approach and Parallel Tabu Search (PTS) approach in the previous work to examine the performance.

Line outage detection using support Vector Machine (SVM) based on the Phasor Measurement Units (PMUs) technology

Phasor Measurement Units (PMUs) have been increasingly widespread throughout the power network. As a result, several researches have been made to locate the PMUs for complete system observability. Many protection applications are based upon the PMUs locations. This paper introduces an important application in power system protection which is the detection of single line outage. In addition, a detection of the outaged line is achieved depending on the variations of phase angles measured at the system buses where the PMUs are located. Hence, a protection scheme from unexpected overloading in the network that may lead to system collapse can be achieved. Such detections are based upon an artificial intelligence technique which is the support Vector Machine (SVM) classification tool. To demonstrate the effectiveness of the proposed approach, the algorithm is tested using offline simulation for the 14-bus IEEE system.

An Artificial Neural Network Based Protection Approach Using Total Least Square Estimation of Signal Parameters via the Rotational Invariance Technique for Flexible AC Transmission System Compensated Transmission Lines

Abstract This article proposes an approach for the protection of transmission lines with flexible AC transmission systems based on artificial neural networks using the total least square estimation of signal parameters via rotational invariance technique. The required features for the proposed algorithm are extracted from the measured transient currents and voltages waveforms using the total least square estimation of signal parameters via rotational invariance technique. Since these transient waveforms are considered as a summation of damped sinusoids, the total least square estimation of signal parameters via rotational invariance technique is used to estimate different signal parameters, mainly damping factors, frequencies, and amplitudes of different modes contained in the signal. Those features are employed for fault detection and faulted phase selection using artificial neural networks. Two types of flexible AC transmission system compensated transmission lines, namely the thyristor-controlled series capacitor and static synchronous compensator, are considered. System simulation and test results indicate the feasibility of using neural networks with the total least square estimation of signal parameters via rotational invariance technique in the fault detection, classification, and faulted phase selection of flexible AC transmission system compensated transmission lines.

Dynamic Economic Dispatch Using a Hybrid Hopfield Neural Network Quadratic Programming Based Technique

Abstract This article introduces a solution for the dynamic economic dispatch problem using a hybrid technique of the Hopfield neural network and quadratic programming. This hybrid algorithm is based on using the enhanced Hopfield neural network to solve the static part of the problem and the quadratic programming algorithm for solving the dynamic part of the dynamic economic dispatch. This technique guarantees the global optimality of the solution due to its look-ahead capability. The proposed technique is applied to and tested on an example from the literature, and the solution is then compared with that obtained by some other techniques to prove the validity and effectiveness of the proposed algorithm.

Fault Location of Uncompensated/Series-compensated Lines Using Two-end Synchronized Measurements

Abstract Phasor measurement units have gained great popularity in the field of control and wide-area protection during the last decade. One of the major protection applications based on phasor measurement unit technology is to determine the fault location in a transmission line. Therefore, research has been developed in the field of fault location. This article introduces a generalized model of fault-location algorithm for both uncompensated and series-compensated transmission lines. The proposed algorithm is based on the distributed parameters of the transmission line in the determination of fault location. Moreover, the proposed algorithm utilizes the synchronized measurements of voltages and currents at both ends of the line. The proposed algorithm is general for any allocation of series-compensation elements. The proposed algorithm is tested through the PSCAD offline simulation program (Manitoba Research Center, Manitoba, Canada) and mathematical analysis with the aid of MATLAB (The MathWorks, Natick, Massachusetts, USA).

A hybrid Hopfield neural network-quadratic programming approach for dynamic economic dispatch problem

This paper introduces a solution of the dynamic economic dispatch (DED) problem using a hybrid approach of Hopfield neural network (HNN) and quadratic programming (QP). The hybrid algorithm is based on using enhanced HNN; to solve the static part of the problem; and the QP algorithm for solving the dynamic part of the DED. This technique guarantees the global optimality of the solution due to its look-ahead capability. The new algorithm is applied and tested to an example from the literature and the solution is then compared with that obtained by some other techniques to prove the superiority and effectiveness of the proposed algorithm.

Gene expression programming for static security assessment of power systems

In this paper, a novel gene expression programming (GEP) algorithm is introduced for power system static security assessment. The GEP algorithms as evolutionary algorithms for pattern classification have recently received attention for classification problems because they can perform global searches. The proposed methodology introduces the GEP for the first time in static security assessment problems. The proposed algorithm is examined using different IEEE standard test systems. Different contingency case studies have been used to test the proposed methodology. The GEP based algorithm formulates the problem as a multi-class classification problem using the one-against-all binarization method. The algorithm classifies the security of the power system into three classes, normal, alert and emergency. Performance of the algorithm is compared with other neural network based algorithm classifiers to show its superiority in static security assessment.

Fault Location in Long Transmission Lines Using Synchronized Phasor Measurements from Both Ends

Abstract Phasor measurement unit based fault location techniques are proposed in this article. Several methods for fault location using synchronized phasor measurements have been listed in the literature review. Some of the listed methods use voltage and current measurements at one end or use two end measurements. Other methods use synchronized voltage measurements only to eliminate the errors of current transformers. This article regenerates the method using only voltage measurements and suggests a new algorithm using both voltage and current measurements with a higher degree of accuracy. To show the superiority of the new proposed algorithm, a comparison between the two algorithms in terms of accuracy and reliability has been conducted. This article also clarifies the validity of the proposed approach for different fault resistances, even the most severe condition of zero-fault resistance is considered. The robustness of the proposed approach is introduced by considering a noise on the tested signal and inaccurate model parameters. The methods have been tested using results of the off-line simulation program (Power Systems Computer Aided Design, Nayak Corporation, Princeton, New Jersey, USA) and the mathematical analysis with the aid of MATLAB (The MathWorks, Natick, Massachusetts, USA). A comparison between the proposed phasor measurement unit based fault location algorithms and one of the other methodologies is also presented.