The Experts below are selected from a list of 84306 Experts worldwide ranked by ideXlab platform
Zhu Qun-xiong - One of the best experts on this subject based on the ideXlab platform.
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Spatial Data Mining Model Based on MapX and Its Application
Computer Engineering, 2004Co-Authors: Zhu Qun-xiongAbstract:MapX having strong ability to manipulate the GIS Data, this paper applies MapX to spatial Data Mining, and constructs a spatial Data Mining Model based on MapX. It is convenient to manipulate spatial and non-spatial Data, as well as judge the topological relationships and distance information between spatial objects, according to solving the problem of the Data conformity and pretreatment in spatial Data Mining through the Model. Generalization techniques are employed to construct the concept hierarchies. Finally the association rules algorithm is used to get useful knowledge in spatial Data Mining.
Dadash M Zadeh - One of the best experts on this subject based on the ideXlab platform.
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Data Mining Model based intelligent differential microgrid protection scheme
IEEE Systems Journal, 2017Co-Authors: Susmita Kar, S R Samantaray, Dadash M ZadehAbstract:This paper presents a Data-Mining-based intelligent differential protection scheme for the microgrid. The proposed scheme preprocesses the faulted current and voltage signals using discrete Fourier transform and estimates the most affected sensitive features at both ends of the respective feeder. Furthermore, differential features are computed from the corresponding features at both ends of the feeder and are used to build the decision tree-based Data-Mining Model for registering the final relaying decision. The proposed scheme is extensively validated for fault situations in the standard IEC microgrid Model with wide variations in operating parameters for radial and mesh topology in grid-connected and islanded modes of operation. The extensive test results indicate that the proposed intelligent differential relaying scheme can be highly reliable in providing an effective protection measure for safe and secured microgrid operation.
Vijendran G. Venkoparao - One of the best experts on this subject based on the ideXlab platform.
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Data-Mining Model based adaptive protection scheme to enhance distance relay performance during power swing
International Journal of Electrical Power and Energy Systems, 2016Co-Authors: Rahul Dubey, Binaya Kumar Panigrahi, Bijay Ketan Panigrahi, Subhransu Ranjan Samantaray, Vijendran G. VenkoparaoAbstract:The paper presents a Data-Mining Model based adaptive protection scheme enhancing distance relay performance during power swing for both compensated and uncompensated power transmission networks. In the power transmission network, the distance relays are sensitive to certain system event such as power swings, which drive the apparent impedance trajectories into the protection zones of the distance relay (zone-3) causing mal-operation of the distance relay, leading to subsequent blackouts. Further, three-phase balanced symmetrical fault detection during power swing is one of the serious concerns for the distance relay operation. This paper proposed a new adaptive protection scheme method based on Data-Mining Models such as DT (decision tree) and RF (random forests) for providing supervisory control to the operation of the conventional distance relays. The proposed scheme is able to distinguish power swings and faults during power swing including fault zone identification for series compensated power transmission network during stress condition like power swing. The proposed scheme has been validated on a 39-bus New England system which is developed on Dig-Silent power factory commercial software (PF4C) platform and the performance indicate that the proposed scheme can reliably enhance the distance relay operation during power swing.
Susmita Kar - One of the best experts on this subject based on the ideXlab platform.
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Data Mining Model based intelligent differential microgrid protection scheme
IEEE Systems Journal, 2017Co-Authors: Susmita Kar, S R Samantaray, Dadash M ZadehAbstract:This paper presents a Data-Mining-based intelligent differential protection scheme for the microgrid. The proposed scheme preprocesses the faulted current and voltage signals using discrete Fourier transform and estimates the most affected sensitive features at both ends of the respective feeder. Furthermore, differential features are computed from the corresponding features at both ends of the feeder and are used to build the decision tree-based Data-Mining Model for registering the final relaying decision. The proposed scheme is extensively validated for fault situations in the standard IEC microgrid Model with wide variations in operating parameters for radial and mesh topology in grid-connected and islanded modes of operation. The extensive test results indicate that the proposed intelligent differential relaying scheme can be highly reliable in providing an effective protection measure for safe and secured microgrid operation.
Rahul Dubey - One of the best experts on this subject based on the ideXlab platform.
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Data-Mining Model based adaptive protection scheme to enhance distance relay performance during power swing
International Journal of Electrical Power and Energy Systems, 2016Co-Authors: Rahul Dubey, Binaya Kumar Panigrahi, Bijay Ketan Panigrahi, Subhransu Ranjan Samantaray, Vijendran G. VenkoparaoAbstract:The paper presents a Data-Mining Model based adaptive protection scheme enhancing distance relay performance during power swing for both compensated and uncompensated power transmission networks. In the power transmission network, the distance relays are sensitive to certain system event such as power swings, which drive the apparent impedance trajectories into the protection zones of the distance relay (zone-3) causing mal-operation of the distance relay, leading to subsequent blackouts. Further, three-phase balanced symmetrical fault detection during power swing is one of the serious concerns for the distance relay operation. This paper proposed a new adaptive protection scheme method based on Data-Mining Models such as DT (decision tree) and RF (random forests) for providing supervisory control to the operation of the conventional distance relays. The proposed scheme is able to distinguish power swings and faults during power swing including fault zone identification for series compensated power transmission network during stress condition like power swing. The proposed scheme has been validated on a 39-bus New England system which is developed on Dig-Silent power factory commercial software (PF4C) platform and the performance indicate that the proposed scheme can reliably enhance the distance relay operation during power swing.
