Optimized PID Controller for Load Frequency Control in Multi-Source and Dual-Area Power Systems Using PSO and GA Algorithms
This paper presents an optimized load frequency control (LFC) approach for interconnected power systems with conventional and renewable energy sources. A proportional integral derivative (PID) controller, tuned using particle swarm optimization (PSO) and genetic algorithm (GA) techniques, manages fr...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10638091/ |
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| Summary: | This paper presents an optimized load frequency control (LFC) approach for interconnected power systems with conventional and renewable energy sources. A proportional integral derivative (PID) controller, tuned using particle swarm optimization (PSO) and genetic algorithm (GA) techniques, manages frequency in a thermal two-area tie-line IPS and a one-area multi-source power network. The integral time absolute error (ITAE) serves as the fitness function for optimization. Key contributions include developing sustainable power network models with renewable energy fluctuations, applying PSO and GA for robust PID tuning, and comparing controller performance under varying conditions. The PSO-PID controller shows superior frequency stability, achieving deviations of 59.97 Hz, 59.72 Hz, and 59.99 Hz for single-area multi-source, area 1, and area 2 in the two-area IPS. It outperforms the GA-PID controller in reducing undershoot, overshoot, and settling time, offering a more reliable LFC solution for interconnected power systems. |
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| ISSN: | 2169-3536 |