Power Quality Conditioners-Based Fractional-Order PID Controllers Using Hybrid Jellyfish Search and Particle Swarm Algorithm for Power Quality Enhancement
Abstract
:1. Introduction
1.1. Related Works in the Literature
1.2. Contributions and Organization
- A hybrid RES-based grid with a load model, where UPQC is connected to manage PQ.
- The FOPID controller is utilized to generate pulse signals for the switches of the UPQC compensator by comparing the actual and reference values.
- The parameters of the FOPID controller are regulated by utilizing the employed HJSPSO optimization algorithm.
- The performing of the proposed model is evaluated under numerous PQ conditions, including sags, harmonics, interruptions, and swells.
- A comparative analysis between other controllers and optimization techniques is implemented.
2. System Investigation
2.1. PV Plant
2.2. Wind System
3. Unified Power Quality Conditioner
3.1. Configuration of UPQC
- (a)
- Reactive power mode: The UPQC functions as a reactive power compensator.
- (b)
- Energy absorption mode: The UPQC absorbs energy through the series converter to balance the additional power.
- (c)
- Energy supply mode: The UPQC uses the series converter to supply energy and restore lost power.
3.2. Control Strategy of UPQC
4. Optimization Problem: Formulation and Algorithm
4.1. Objective Function
4.2. Constraints
4.3. Hybrid Jellyfish Search Optimizer and Particle Swarm Optimizer (HJSPSO)
5. Results and Discussions
5.1. Power Quality Issues
5.1.1. Event #1: Balanced Sag
5.1.2. Event #2: Balanced Swell
5.1.3. Event #3: Three-Phase Faults
5.1.4. Event #4: Double Line to Ground
5.2. Comparative Investigation
5.2.1. Comparison of HJSPSO and Other Optimization Methods
5.2.2. Comparative Evaluation of Two Different Controllers
6. Conclusions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Operating Conditions | FOPID Control Strategy | Time (s) | Objective fn. | ||||
---|---|---|---|---|---|---|---|
Kp | Ki | Kd | λ | μ | |||
Sag event | 3.541 | 1.468 | 0.307 | 1.6783 | 0.1523 | 127.474 | 1.423 |
Swell event | 3.348 | 0.476 | 0.231 | 1.8441 | 0.3061 | 128.846 | 1.890 |
3-phase fault | 3.304 | 0.586 | 0.515 | 1.6891 | 0.5704 | 129.476 | 1.168 |
Double line to ground fault | 4.051 | 2.045 | 0.087 | 1.6801 | 0.5690 | 125.476 | 1.378 |
Optimization Methods | GOA | SSA | HJSPSO |
---|---|---|---|
Max. iteration | 250 | 250 | 250 |
Number of search agents | 100 | 100 | 100 |
Computing time (s) | 159.544 | 212.405 | 127.474 |
Objective function | 1.747 | 1.987 | 1.423 |
Kp | 2.261 | 3.766 | 3.541 |
Ki | 1.991 | 1.898 | 1.468 |
Kd | 0.541 | 0.468 | 0.307 |
λ | 1.4786 | 1.7894 | 1.6783 |
μ | 0.2487 | 0.1479 | 0.1523 |
Scenarios | Computing Time (s) | Comparative Index (J) | ||
---|---|---|---|---|
UPQC-FLC | UPQC-FOPID | UPQC-FLC | UPQC-FOPID | |
Event #1: Balanced sag | 187.474 | 127.474 | 2.831 | 1.423 |
Event #2: Balanced swell | 188.011 | 128.846 | 2.092 | 1.890 |
Event #3: 3-phase fault | 158.505 | 129.476 | 2.038 | 1.168 |
Event #4: Double line to ground fault | 204.112 | 125.476 | 2.478 | 1.378 |
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Aldosary, A. Power Quality Conditioners-Based Fractional-Order PID Controllers Using Hybrid Jellyfish Search and Particle Swarm Algorithm for Power Quality Enhancement. Fractal Fract. 2024, 8, 140. https://doi.org/10.3390/fractalfract8030140
Aldosary A. Power Quality Conditioners-Based Fractional-Order PID Controllers Using Hybrid Jellyfish Search and Particle Swarm Algorithm for Power Quality Enhancement. Fractal and Fractional. 2024; 8(3):140. https://doi.org/10.3390/fractalfract8030140
Chicago/Turabian StyleAldosary, Abdallah. 2024. "Power Quality Conditioners-Based Fractional-Order PID Controllers Using Hybrid Jellyfish Search and Particle Swarm Algorithm for Power Quality Enhancement" Fractal and Fractional 8, no. 3: 140. https://doi.org/10.3390/fractalfract8030140