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- Title
Optimal detection and classification of grid connected system using MSVM-FSO technique.
- Authors
Stallon, Samuel Raj Daison; Anand, Ramanpillai; Kannan, Ramasamy; Rajasekaran, Seenakesavan
- Abstract
This paper, a hybrid method, is proposed for protecting the hybrid photovoltaic (PV) and wind turbine (WT) system. The proposed protecting method is the hybrid wrapper of both the multiple support vector machine (MSVM) and firebug swarm optimization (FSO), commonly named as MSVM-FSO method. The proposed technique is diagnosing the appropriate fault occurring in the hybrid system. The main purpose of the proposed system is to assure the system with lower complexity for the fault diagnosis and detection (FDD) for improving the power quality (PQ) of hybrid method. Here, the MSVM approach is used to detect the fault conditions of grid-tied system. To evaluate the events of voltages, fault and the currents of hybrid systems are analyzed at the feeder of buses. The FSO categorizes the types of fault, which is occurred in grid-connected system. By then, the proposed method's performance is done in the MATLAB software and it is contrasted with different existing methods. From this, the proposed method provides accuracy as 99.7% and efficiency as 98%, which is high compared to existing methods.
- Subjects
GRIDS (Cartography); HYBRID systems; SUPPORT vector machines; FAULT diagnosis; FAULT currents
- Publication
Environmental Science & Pollution Research, 2024, Vol 31, Issue 21, p31064
- ISSN
0944-1344
- Publication type
Article
- DOI
10.1007/s11356-024-32921-x