Informatics Publishing Limited

S. A. Hosseini ¹, F. Razavi ², M. Karami ¹, A. A. Ghadimi ³, S. S. Karimi Madahi ¹

Affiliations
1 Department of Electrical Engineering, Islamic Azad University, Ashtian Branch, Ashtian, IR
2 Department of Electrical Engineering, University of Tafresh, Tafresh, IR
3 Department of Electrical Engineering, Science and research branch, Islamic Azad University, Arak, IR

Abstract

SiC lightning arresters are a kind of lightning arresters that nowadays are substituted with new type such as ZnO lightning arrester. Nonetheless, many SiC lightning arresters in Iran's electricity networks are operating. For instance, all the medium voltage network lightning arresters of Bakhtar Regional Electrical Company (BREC) are SiC type. The company wants to exchange these lightning arresters, but due to high cost and numbers of these lightning arresters, it is decided to put them in suitable ranks up to a due time. Since all suggested tests for recognition of lightning arresters deficiency are laboratory tests and must be done in lab, it isn't possible for the company to transfer all lightning arresters from substation to lab. Therefore, it has been decided to carry out that in the substation. Accordingly, a project has been suggested and carried out by the writers of this paper and the present paper is the result of this project. Different theories in this paper are surveyed. DC test is introduced as a suitable way for correct recognition deficiency of lightning arresters. The acquired results of DC test on some samples of lightning arresters are in coordination with the standard tests that have been carried out in Pars High Voltage Lab. Finally, three groups of arresters are defined according to their operating condition which includes acting good, delayed acting and not operating arresters. According to this classification, BREC is capable to exchange the arresters with respect to condition of the related arrester and with an appropriate priority which is obtained from its condition.

Keywords

SiC Lightning Arrester, Electricity Network

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R. Eslami ¹, B. Eyvazi ², M. H. Soveyzi ², S. A. Hosseini ³, S. Taherkhani Aghaei ²

Affiliations
1 Department of Electrical Engineering, Sahand University of Technology, New Sahand Town, Tabriz, IR
2 Department of Electrical Engineering, Ekbatan Institute of Higher Education, Qazvin, IR
3 Department of Electrical Engineering, Golpayegan University of Technology, Isfahan, IR

Abstract

Objectives: Objectives of this paper are to achieve decreasing power losses, maintaining permissible voltage profiles in distribution networks and also considering the uncertainties of network Components like loads and wind turbines. Methods/ Statistical Analysis: A new method is proposed for Distribution Feeder Reconfiguration (DFR) and capacitor placement considering Wind Turbine (WT) based on an improved reconfiguration technique. The employed DFR method is based on a single loop reconfiguration method which selects the optimal branch in each loop to achieve maximum loss reduction. Moreover, sequence of loops selection is optimized by using an optimization algorithm. Findings: A joint optimization algorithm has been proposed for combination of the capacitor placement and the improved network reconfiguration. This is due to the inherent coupling relationship between these methods, and therefore, simultaneous implementation of them is more effective than considering them separately. For more practical application of the proposed method, stochastic nature of loads and wind turbine generators of the network have been considered. Teaching-Learning Based Optimization (TLBO) algorithm has been employed for the proposed joint optimization problem and its results have been compared to the PSO and GA. The objective function has been proposed for minimizing the total cost due to capacitor placement and energy losses during 2 years with considering the constraints of bus voltages and the current carrying capacity of conductors. The obtained results confirmed the effectiveness of the proposed method. Application/Improvements: Simultaneous implementation of capacitor placement and reconfiguration method, considering stochastic nature of network and also employing TLBO algorithm for the proposed optimization problem.

Keywords

Load and Technical Improvement, Distribution Network, Uncertainty, Wind Turbine.

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M. H. Jannaty ¹, A. Eghbalzadeh ², S. A. Hosseini ¹

Affiliations
1 Department of Technical and Engineering, Tehran Science and Research Branch, Islamic Azad University, Tehran, IR
2 Civil Engineering Department, Advanced Research Institute for Water and Wastewater, Razi University of Kermanshah, IR

Abstract

During recent years, data mining and machine learning techniques have been developed in various fields for building intelligent information systems. However, few of the presented methods possess online support capabilities or sufficient flexibility to use large and complicated data sets. For this reason, the present study implemented the Particle Swarm Optimization (PSO) technique to predict scour depths by obtaining appropriate parameters for the neural network model and fuzzy inference system. The test was conducted based on samples obtained from 188 pier scour depths presented by the United States Geological Survey (USGS). The empirical results showed that, due to its minimum Root Mean Square Error (RMSE), the presented model was preferable to the ANFIS model. Moreover, the proposed model produced better solutions than FDOT and HEC-18 equations. The momentum method was implemented to accelerate learning by teaching for increasing the accuracy of short-term predictions.

Keywords

Field Data, PSO-ANFIS, Scour Depth, Single Pier.

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