Research Article
A Data-Driven Approach for Reactive Power Optimization Incorporating Interval Values for Renewable Power Generation
| Algorithms | Settings |
| GA | Population size = 50, iterations = 200, crossover probability = 0.6, mutation probability = 0.01, and selection method: tournament selection | I-GWO | Population Size = 50, iterations = 200, and was linearly decreased from 2 to 0 | Improved PSO | Population Size = 50, iterations = 200, inertia weight = [0.4, 0.9], , , , , and |
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