Salem M. Elkhodary

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.

Power system voltage stability margin identification using local measurements

Voltage stability margin is essential to be known in advance to avoid voltage collapse and system blackout. This paper presents a new technique for determining the voltage stability margin, so that a corrective decision is taken in the proper time. The proposed algorithm is based on recursive least error square to measure the Thevenins impedance at the bus in question as the busload changes. The proposed technique utilizes the past measurements together with the recent local measurements, bus voltage and load current, to predict Thevenins impedance. The voltage instability occurs at a point where the load impedance equals Thevenins impedance. Prior to this point the voltage margin can be predicted using the proposed technique. The method is tested on the IEEE 30 bus system for a single bus-load change, short-term voltage stability, and when the buses loads change with the same rate, long-term voltage stability study. Unlike the other techniques the proposed algorithm has the ability to estimate digitally the Thevenins impedance at the load bus in question.

Distribution systems reconfiguration using the hyper-cube ant colony optimization algorithm

This paper introduces the Ant Colony Optimization algorithm (ACO) implemented in the Hyper-Cube (HC) framework to solve the distribution network minimum loss reconfiguration problem. The ACO is a relatively new and powerful intelligence evolution method inspired from natural behavior of real ant colonies for solving optimization problems. In contrast to the usual ways of implementing ACO algorithms, the HC framework limits the pheromone values by introducing changes in the pheromone updating rules resulting in a more robust and easier to implement version of the ACO procedure. The optimization problem is formulated taking into account the operational constraints of the distribution systems. Results of numerical tests carried out on two test systems from literature are presented to show the effectiveness of the proposed approach.

Distribution networks reconfiguration for loss reduction using the Hyper Cube Ant Colony Optimization

This paper introduces the Ant Colony Optimization algorithm (ACO) implemented in the Hyper-Cube (HC) framework to solve the distribution network minimum loss reconfiguration problem. The ACO is a relatively new and powerful intelligence evolution method inspired from natural behavior of real ant colonies for solving optimization problems. In contrast to the usual ways of implementing ACO algorithms, the HC framework limits the pheromone values by introducing changes in the pheromone updating rules resulting in a more robust and easier to implement version of the ACO procedure. The optimization problem is formulated taking into account the operational constraints of the distribution systems. Results of numerical tests carried out on two test systems from literature are presented to show the effectiveness of the proposed approach.

Influence of freon on charge density build-up in a solid insulator

The charge generation at the surface of and within an acrylic glass spacer was measured using a capacitive probe in freon as a function of gas pressure and the level, duration and polarity of a dc applied voltage. Typically the rate of charge build up increased with increasing gas pressure from 0.174 /spl mu/C/m/sup 2//s at 0.1 MPa to 0.97 /spl mu/C/m/sup 2//s at 0.4 MPa a fixed applied voltage of 80 kV. At a fixed gas pressure of 0.1 MPa the charge build up increased from 2.6/spl times/10/sup -3/ /spl mu/C/m/sup 2//s at 2 kV to 174/spl times/10/sup -3/ /spl mu/C/m/sup 2//s at 80 kV. The saturated charge density increased linearly with increasing voltage from 1.3 /spl mu/C/m/sup 2/ at 2 kV to 61.2 /spl mu/C/m/sup 2/ at 80 kV, for 0.1 MPa. The charging current was also monitored and found to decrease rapidly with increasing time until saturation is reached. The saturated current increased, at a fixed pressure, with increasing voltage. It also increased with increasing pressure at a fixed applied voltage. The observed charge build up is governed by the total surface and volume resistances of the insulator.<<ETX>>

Special features of energy forecast methodology in fast growing countries

An accurate load-forecast is essential for developing a power supply strategy, and system development plan, especially for developing countries where the demand is increased with high growth rate. Forecasting demand and energy for power systems in fast developing countries is however a difficult task; the difficulty arises from the limited historical data, and/or its uncertainty as well as the high growth rate of electric demand. This paper, thus presents a unified forecasting methodology with special features based on the decomposition of loads into several sectorial components for a fast-growing power system. The model has been applied to a typical fast growing system, the Saudi power system, as compared with the conventional method of forecasting the total energy. Further, this paper applies energy forecast models using artificial neural networks (ANN) with multilayer perceptron (MLP) and back propagation (BP) learning algorithm on such a fast growing system. ANN is implemented to support the choice of the most suitable load-forecasting model for long term power system planning. This technique demonstrates the accuracy of the proposed method among the three forecast models and shows that the suggested forecast model based on the ANN technique is simplest with high accuracy. To carry out this task with the various methods, it was necessary to perform data mining for the available historical data. Hence, it could be possible to forecast the peak load forecast assuming the historical data for the load factor.

The Use of Experimental and Artificial Neural Network Technique to Estimate Age against Surface Leakage Current for Non-ceramic Insulators

Solid insulators breakdown mechanism is always associated with surface leakage current. Surface leakage current causes surface tracking. Surface tracking in non-ceramic insulators is an unwanted phenomenon, which cannot be accurately predicted. This paper introduces an experimental and analytical technique to predict the insulator life time, and presents an experimental measurements of the surface leakage current against time of nonceramic insulators on naturally aged insulators and artificially contaminated material. A comparison of surface leakage current for fourteen different type of non-ceramic materials under the same conditions is also introduced in this paper (the mentioned nonceramic materials are mainly silicon rubber (SR) and poly propylene (PP), with different filler percentage). The study of the leakage current dependence on the insulators contamination level is also presented in this paper. Different prototype of artificial neural networks-based system that can estimate the insulator age under different contamination level at the surface of polymer insulators by employing the experimentally measured leakage current was constructed in this paper. The proposed prototype is trained for different filler level for different insulator type in the neural network. The proposed technique in this paper predicts the best non-ceramic insulator with the exact filler percentage that withstands higher voltage with longer life time under contaminated weather and polluted condition. The proposed technique is considered to be helpful tool in the area of quality control

Effects of ac voltage on charge density in a spacer

The charging of acrylic glass rod under the influence of ac voltage is reported. A linear dependence of the accumulated charge density on the peak ac applied voltage is observed. A comparison between the accumulated charge density with ac and dc applied voltages is reported. The charge densities that accumulate under the effect of ac voltage are smaller than under dc voltage for the same peak voltage level. A switchable dc power supply to simulate an ac voltage application is also employed. Results show that there is an accumulation of both positive and negative charges on the insulator using ac depending on the polarity of the voltage wave.

Surface charge decay under the influence of prior applied voltage in freon

The application of high voltage to an insulating spacer causes a generation of charges within and on the insulator. These charges distort the electric field and may result in a significant modification of the withstand voltage. The decay of the charge density subsequent to removal of the applied voltage is reported. At a fixed pressure the rate of charge decay increased with increasing pre-applied voltage. At a fixed pre-applied voltage, the rate of charge decay increased with increasing gas pressure.

Generation of surface charges on an insulator in SF/sub 6/ gas

The build up with time of the accumulated charge density on an acrylic glass rod insulator having a fixed length and fixed diameter of 30 mm was measured in SF/sub 6/. The charge density is found to increase linearly with increasing voltage at a fixed pressure, to increase linearly with increasing gas pressure in the range 0.1-0.13 MPa, to be almost constant in the range 0.13-0.5 MPa at a fixed applied voltage, and to increase with increasing voltage at a fixed E/p. The rate of charge build-up depends on time; it initially increases rapidly, and then increase slowly until saturation is reached. The charge polarity corresponds to that of the adjacent electrode. These results suggest that the role of the ionized species within the volume of the gas in charging the insulator is less significant than the charging of the insulator by injection of current from the electrodes, which is governed by the total surface and volume resistances of the insulator.<<ETX>>