Almoataz Y. Abdelaziz

An adaptive protection scheme for optimal coordination of overcurrent relays

Abstract This paper presents an adaptive protection scheme for optimal coordination of overcurrent relays (OCR) in interconnected power networks with an improved formulation. The scheme adapts to system changes; new relays settings are implemented as load, generation-level or system-topology changes. The software developed for this application is described. The developed scheme is applied to the IEEE 30-bus test system. Results showed the importance and necessity of this scheme in maintaining the optimal performance of the relays under all conditions.

A Classification Technique for Recloser-Fuse Coordination in Distribution Systems With Distributed Generation

In this paper, a novel approach is presented to study the impact of distributed-generation penetration on recloser-fuse coordination. The main core of this approach is based on an assessment process using a classification technique to classify the recloser-fuse coordination status at fault conditions to either coordination holds or coordination lost. Accordingly, the distribution system operator can take the proper decision. Then, two complementary actions are recommended in the proposed approach as a solution to decrease the number of cases where coordination is lost. The first one is to search for the best DG locations, where such locations are characterized by the minimum number of cases classified as coordination lost. The second one is based on changing the recloser setting in such a way to minimize the cases where coordination is lost. This new approach has been implemented on the IEEE 37-node test feeder using MATLAB-based developed software and the obtained results are presented and discussed.

Optimal Placement and Sizing of Distributed Generators in Unbalanced Distribution Systems Using Supervised Big Bang-Big Crunch Method

This paper presents an efficient and fast-converging optimization technique based on a modification of the traditional big bang-big crunch method for optimal placement and sizing of voltage controlled distributed generators. The proposed algorithm deals with the optimization problems incorporating multiple distributed generators for the sake of power as well as energy loss minimization in balanced/unbalanced distribution systems. The proposed algorithm is implemented in MATLAB environment and tested on the 33-bus feeder system and the IEEE 37-node feeder. Validation of the proposed method is done via comparing the results with published results obtained from other competitive methods.

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.

Distribution Systems Reconfiguration Using Ant Colony Optimization and Harmony Search Algorithms

Abstract One objective of the feeder reconfiguration problem in distribution systems is to minimize the distribution network total power loss for a specific load. For this problem, mathematical modeling is a non-linear mixed integer problem that is generally hard to solve. This article proposes two heuristic algorithms inspired from natural phenomena to solve the network reconfiguration problem: (1) “real ant-behavior-inspired” ant colony optimization implemented in the hyper cube framework and (2) the “musician behavior-inspired” harmony search algorithm. The optimization problem is formulated taking into account the operational constraints of distribution systems. A 32-bus system and a 118-bus distribution were selected for optimizing the configuration to minimize the losses. The results of reconfiguration using the proposed algorithms show that both of them yield the optimum configuration with minimum power loss for each case study; however, the harmony search required shorter simulation time but more practice of the iterative process than the hyper cube–ant colony optimization. Implementing the ant colony optimization in the hyper cube framework resulted in a more robust and easier handling of pheromone trails than the standard ant colony optimization.

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.

Static VAR Compensator Damping Controller Design Based on Flower Pollination Algorithm for a Multi-machine Power System

Abstract A new optimization technique known as the flower pollination algorithm is suggested in this article for robust tuning of a static VAR compensator to mitigate power system oscillations. The flower pollination algorithm is based on the properties of flowering plants. The tuning of a static VAR compensator controller is established as an optimization process. The flower pollination algorithm is applied to find out the optimal parameters of a static VAR compensator by diminishing certain performance index. The behavior of the suggested algorithm has been appreciated with the behavior of the genetic algorithm and bacteria foraging to certify the notability of the suggested flower pollination algorithm in designing a static VAR compensator. Simulation results of the flower pollination algorithm based static VAR compensator provide greater attenuation for various loading conditions than the optimized static VAR compensator by genetic algorithm and the optimized static VAR compensator by bacteria foraging. The results of the developed flower pollination algorithm based static VAR compensator are observed via time-domain analysis, eigenvalues, and various indices. Also, the economic value of this work is confirmed.

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.

Optimal Location of Thyristor-controlled Series Compensators in Power Systems for Increasing Loadability by Genetic Algorithm

Abstract This article presents an approach to find the optimal location of thyristor-controlled series compensators in a power system to improve the loadability of its lines and minimize its total loss. Also the proposed approach aims to find the optimal number of devices and their optimal compensation levels by using a genetic algorithm taking into consideration the thermal and voltage limits. Examination of the proposed approach is carried out on a modified IEEE 30-bus system.

Optimal Planning of Distributed Generators in Distribution Networks Using Modified Firefly Method

Abstract—This article presents a novel algorithm for optimal planning of a dispatchable distributed generator connected to the distribution networks. The proposed algorithm modifies the traditional firefly method to be able to deal with the practically constrained optimization problems by proposing formulas for tuning the algorithm parameters and updating equations. The proposed algorithm rigidly determines the optimal location and size of the distributed generation units in order to minimize the system power loss without violating the system practical constraints. Moreover, the optimal distributed generator location and minimum size for achieving a certain specified power loss are determined using the proposed method and compared to the results of a proposed heuristic technique. The distributed generation units in the proposed algorithms are modeled as voltage controlled nodes with the flexibility to be converted to constant power nodes in the case of reactive power limit violation. The proposed algorithms are implemented in MATLAB and tested on the IEEE 33-bus and the IEEE 37-nodes feeder. The results that are via comparison with published results obtained from other competing methods show the effectiveness, accuracy, and speed of the proposed method.