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• W4386119488 abstract "Identifying the weak buses in power system networks is crucial for planning and operation since most generators operate close to their operating limits, resulting in generator failures. This work aims to identify the critical/weak node and reduce the system’s power loss. The line stability index (Lmn) and fast voltage stability index (FVSI) were used to identify the critical node and lines close to instability in the power system networks. Enhanced particle swarm optimization (EPSO) was chosen because of its ability to communicate with better individuals, making it more efficient to obtain a prominent solution. EPSO and other PSO variants minimized the system’s actual/real losses. Nodes 8 and 14 were identified as the critical nodes of the IEEE 9 and 14 bus systems, respectively. The power loss of the IEEE 9 bus system was reduced from 9.842 MW to 7.543 MW, and for the IEEE 14 bus system, the loss was reduced from 13.775 MW of the base case to 12.253 MW for EPSO. EPSO gives a better active power loss reduction and improves the node’s voltage profile than other PSO variants and algorithms in the literature. This suggests the feasibility and suitability of EPSO to improve the grid voltage quality." @default.
• W4386119488 created "2023-08-25" @default.
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• W4386119488 date "2023-08-24" @default.
• W4386119488 modified "2023-09-28" @default.
• W4386119488 title "Minimization of Active Power Loss Using Enhanced Particle Swarm Optimization" @default.
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• W4386119488 doi "https://doi.org/10.3390/math11173660" @default.
• W4386119488 hasPublicationYear "2023" @default.
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