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Islanding detection and classification and load shedding scheme for dispersed generation integrated radial distribution systems

Aziah , Khamis (2014) Islanding detection and classification and load shedding scheme for dispersed generation integrated radial distribution systems. PhD thesis, UTeM.

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Islanding Detection And Classification And Load Shedding Scheme For Dispersed Generation Integrated Radial Dsitribution Systems 24pages.pdf

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Abstract

The high penetration level of distributed generation (DG) provides numerous potential environmental benefits, such as high reliability, efficiency, and low carbon emissions. However, the effective detection of islanding and rapid DG disconnection is essential to prevent safety problems and equipment damage caused by the island mode operations of DGs. The common islanding protection technology is based on passive techniques that do not perturb the system but have large nondetection zones. Therefore, the first part of this thesis attempts to develop a simple and effective passive islanding detection method with reference to a probabilistic neural networkbased classifier, as well as utilizes the features extracted from three-phase voltages seen at the DG terminal. This approach enables initial features to be obtained using the phase-space technique. This technique analyzes the time series in a higher dimensional space, revealing several hidden features of the original signal. Meanwhile, the second part of the thesis focuses on the development of an optimal load shedding scheme after the system experiences an unintentional islanding state to prevent system collapse due to load-generation mismatch and voltage instability encountered in the islanded part of the system. To handle this optimization problem, a constraint multiobjective function that considers the linear static voltage stability margin and amount of load curtailment was formulated. A novel heuristic optimization technique based on the backtracking search algorithm (BSA) was subsequently proposed as an optimization tool for determining the optimum load shedding based on the proposed objective function. Several test systems, including a radial distribution system with two DG units and the Institute of Electrical and Electronics Engineers (IEEE) 33-bus radial distribution system with four DG units, were utilized to evaluate the effectiveness of the proposed islanding detection method and the optimal load shedding scheme. The effectiveness of the proposed islanding detection method was verified by comparing its results with the conventional wavelet transform (WT)-based technique through intensive simulations conducted with the DIgSILENT Power Factory® software. The assessment indices, namely, the mean absolute percentage error (MAPE), mean absolute error (MAE), and root mean square error (RMSE), obtained a 0% error rate for the proposed method when applied to the IEEE 33-bus radial distribution system with four DG units. Meanwhile, the MAPE, MAE, and RMSE obtained error rates of 0.1482%, 0.2752%, and 5.055%, respectively, for the WT-based technique when applied to the IEEE 33-bus radial distribution system with four DG units. These indices show that the proposed islanding detection method is robust and capable of sensing the difference between the islanding condition and other system disturbances. Meanwhile, the performance of the proposed load shedding scheme was evaluated through an extensive test conducted on the IEEE 33-bus system considering several scenarios such as load shedding under various operating points and at various islands using the MATLAB® software. Moreover, the effectiveness of the proposed scheme was validated by comparing its results with those obtained using the genetic algorithm (GA). The optimization results indicate that the proposed BSA technique is more effective in determining the optimal amount of load to be shed in any islanded system compared with GA.

Item Type: Thesis (PhD)
Uncontrolled Keywords: Distributed generation of electric power
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Library > Tesis > FKE
Depositing User: Norziyana Hanipah
Date Deposited: 04 Sep 2015 07:22
Last Modified: 04 Sep 2015 07:22
URI: http://eprints.utem.edu.my/id/eprint/14881

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