Sajad Bagheri ¹, Reza Effatnejad ², Abolfazl Salami ³

Affiliations
1 Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Arak, IR
2 Electrical Engineering Department, Karaj Branch, Islamic Azad University, Karaj, IR
3 Faculty of Electrical Engineering, Arak Technology University, Arak, IR

Abstract

Frequency response analysis method is used for certain evaluating and monitoring of the winding displacement and deformation of transformer core to detect incipient faults. Frequency response analysis is based on the graphical analysis and comparison of the current measured transfer function with a base current. In this paper we use compound of haar wavelet transform and intelligent Simulated Anealing Algorithms (SA) and finally we compare the achieved parameters with Genetic Algorithm (GA).

Keywords

Frequency Response Analysis, Haar Wavelet Transform, Genetic Algorithm, Simulated Annealing, Transformers Winding Parameter Identification, Traveling Wave Model

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Mohammad Mohammadinodoushan ¹, Ali Asghar Ghadimi ², Abolfazl Salami ³, Hamid Reza Alirezaei ¹, Alireza Mohammadi-Nodooshan ⁴

Affiliations
1 Electrical Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, IR
2 Electrical Engineering Department, Arak University, Arak, IR
3 Electrical Engineering Department, Arak University of Technology, Arak, IR
4 Department of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran, IR

Abstract

Background/Objectives: Several advantages of Distributed Generation (DG) have created incentives to increase DG penetration in distribution networks. In order to meet this requirement, Coordinated Reconfiguration and Voltage Control (CRVC) is used in this paper. Methods: To do so, simulations are done in two parts. In the first part, the power loss of a distribution system is decreased through CRVC, and in the second part, DG allowable capacity is increased through CRVC. In order to decrease the computational time for finding the best network configuration and voltage control devices values, modified Binary Particle Swarm Optimization (BPSO) is used. The method has been tested on a 33-bus radial distribution system. Findings and Improvements: Simulation results in both two parts show the efficiency of the method. In the first part, CRVC method could decrease power loss 33%. In the second part, the DG allowable penetration is increased 140% thorough CRVC. This shows that this method is more robust than various techniques that have been proposed to increase DG allowable capacity in the past. Moreover, without using complex voltage control methods, CRVC improved the voltage of all busses considerably. Furthermore, simulations verified the decrease in computational time for reconfiguration which is an important challenge in using reconfiguration.

Keywords

Binary Partcile Swarm Optimization, Distributed Generation, Loss Reduction, Reconfiguration, Voltage Control

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