Neuro-Wavelet Protection Scheme for PV-Wind Energy Source Integrated 6-Terminal Power Network with IoT-Based Smart Environment
By: Goli, Ravi Kumar
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Contributor(s): Manju Sree, Y.
Publisher: New York Springer 2022Edition: Vol, 103(6), Dec.Description: 2035–2048p.Subject(s): Electrical EngineeringOnline resources: Click here
In:
Journal of the institution of engineers (India): Series BSummary: Microgrids are currently one among the most extensively employed techniques in the power network to lower system losses and raise the reliability of electrical systems. Power project integration typically entails expanding the network of an existing power system with new distributed energy sources, which may have a compensating device and may not have a compensating device. Power project integration often entails connecting new energy resources to an existent power system network, such as wind and PV generating units parallel and series compensating devices. The topology and behaviour of the dynamic system have changed, necessitating the development of a new protective method. To combine various power sources and different loads in a smart grid system, quick fault detection algorithmic approaches are now required. With the aid of new technology, the protective strategy must offer parametric monitoring in addition to physical monitoring. The Internet of Things is a popular technology for monitoring electric protective systems in a variety of environmental settings. The detailed coefficients of the Bior1.5 wavelet are designed to detect defective lines and pinpoint their locations, and the ANN (artificial neural network) technique is used to determine where the fault is located within a power line. This suggested solution offers a neuro-wavelet protection mechanism for a six-terminal transmission system that integrates a hybrid energy source in a smart environment powered by the Internet of Things under different types of faults.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2023-0016 |
Microgrids are currently one among the most extensively employed techniques in the power network to lower system losses and raise the reliability of electrical systems. Power project integration typically entails expanding the network of an existing power system with new distributed energy sources, which may have a compensating device and may not have a compensating device. Power project integration often entails connecting new energy resources to an existent power system network, such as wind and PV generating units parallel and series compensating devices. The topology and behaviour of the dynamic system have changed, necessitating the development of a new protective method. To combine various power sources and different loads in a smart grid system, quick fault detection algorithmic approaches are now required. With the aid of new technology, the protective strategy must offer parametric monitoring in addition to physical monitoring. The Internet of Things is a popular technology for monitoring electric protective systems in a variety of environmental settings. The detailed coefficients of the Bior1.5 wavelet are designed to detect defective lines and pinpoint their locations, and the ANN (artificial neural network) technique is used to determine where the fault is located within a power line. This suggested solution offers a neuro-wavelet protection mechanism for a six-terminal transmission system that integrates a hybrid energy source in a smart environment powered by the Internet of Things under different types of faults.
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