Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System
Introduction. The Grid Connected Photovoltaic System comprises two fundamental control loops: an external loop responsible for overseeing the DC link voltage, and an internal control loop that regulates the inverter current. The primary element of any control loop is the proportional-integral contro...
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National Research Mordova State University; MRSU
2025-01-01
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| Series: | Инженерные технологии и системы |
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| Online Access: | https://journals.rcsi.science/2658-4123/article/viewFile/264106/273632 |
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| author | Amit Verma Prabhakar Tiwari Desh Deepak Sharma |
| author_facet | Amit Verma Prabhakar Tiwari Desh Deepak Sharma |
| author_sort | Amit Verma |
| collection | DOAJ |
| description | Introduction. The Grid Connected Photovoltaic System comprises two fundamental control loops: an external loop responsible for overseeing the DC link voltage, and an internal control loop that regulates the inverter current. The primary element of any control loop is the proportional-integral controller and determining the appropriate gains for this controller is a difficult issue.
Aim of the Study. The study aimed to adjust the gains of the PI controllers in both static and dynamic irradiance scenarios for improving DC-link voltage by novel hybrid optimization method named Genetic Algorithm- Simulated Annealing and Genetic Algorithm- Pattern search.
Material and Methods. In this paper we use two hybrid optimizations techniques called Genetic Algorithm- simulated Annealing and Genetic Algorithm- Pattern Search to adjust the gains of the PI controllers in both static and dynamic irradiance scenarios for improving DC-link voltage.
Results. Finally, this study presents comparison of DC-link voltage with six cases with manual tuning of PI controller, as well as PI controller by Genetic Algorithm- simulated Annealing, Genetic Algorithm- Pattern Search, Genetic Algorithm, Simulated Annealing and Pattern Search. The comparison showed by using Genetic Algorithm-Simulated Annealing, peak overshoot in DC-link voltage is 829.3 V while peak overshoot in DC-link voltage is 1 052 V when DC-link voltage is controlled by manual tuning of PI as well as significant reduction in peak time and settling time in DC-link voltage.
Discussion and Conclusion. The results achieved to strengthen the DC-link voltage under both static and dynamic irradiance conditions enable the sustaining of a constant DC-link voltage, which is essential for grid-connected photovoltaic systems. The comparison showed by using Genetic Algorithm- Simulated Annealing, peak overshoot in DC-link voltage is 829.3 V while peak overshoot in DC-link voltage is 1 052 V when DC-link voltage is controlled by manual tuning of PI as well as significant reduction in peak time and settling time in DC-link voltage. |
| format | Article |
| id | doaj-art-db0aa3c558ba4dd3a41c95ca01b89be6 |
| institution | Matheson Library |
| issn | 2658-4123 2658-6525 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | National Research Mordova State University; MRSU |
| record_format | Article |
| series | Инженерные технологии и системы |
| spelling | doaj-art-db0aa3c558ba4dd3a41c95ca01b89be62025-06-25T07:54:05ZengNational Research Mordova State University; MRSUИнженерные технологии и системы2658-41232658-65252025-01-0135233335410.15507/2658-4123.035.202502.333-35458Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power SystemAmit Verma0https://orcid.org/0000-0002-1591-1523Prabhakar Tiwari1https://orcid.org/0000-0003-3923-9126Desh Deepak Sharma2https://orcid.org/0000-0003-4512-4878Madan Mohan Malaviya University of TechnologyMadan Mohan Malaviya University of TechnologyMahatma Jyotiba Phule Rohilkhand UniversityIntroduction. The Grid Connected Photovoltaic System comprises two fundamental control loops: an external loop responsible for overseeing the DC link voltage, and an internal control loop that regulates the inverter current. The primary element of any control loop is the proportional-integral controller and determining the appropriate gains for this controller is a difficult issue. Aim of the Study. The study aimed to adjust the gains of the PI controllers in both static and dynamic irradiance scenarios for improving DC-link voltage by novel hybrid optimization method named Genetic Algorithm- Simulated Annealing and Genetic Algorithm- Pattern search. Material and Methods. In this paper we use two hybrid optimizations techniques called Genetic Algorithm- simulated Annealing and Genetic Algorithm- Pattern Search to adjust the gains of the PI controllers in both static and dynamic irradiance scenarios for improving DC-link voltage. Results. Finally, this study presents comparison of DC-link voltage with six cases with manual tuning of PI controller, as well as PI controller by Genetic Algorithm- simulated Annealing, Genetic Algorithm- Pattern Search, Genetic Algorithm, Simulated Annealing and Pattern Search. The comparison showed by using Genetic Algorithm-Simulated Annealing, peak overshoot in DC-link voltage is 829.3 V while peak overshoot in DC-link voltage is 1 052 V when DC-link voltage is controlled by manual tuning of PI as well as significant reduction in peak time and settling time in DC-link voltage. Discussion and Conclusion. The results achieved to strengthen the DC-link voltage under both static and dynamic irradiance conditions enable the sustaining of a constant DC-link voltage, which is essential for grid-connected photovoltaic systems. The comparison showed by using Genetic Algorithm- Simulated Annealing, peak overshoot in DC-link voltage is 829.3 V while peak overshoot in DC-link voltage is 1 052 V when DC-link voltage is controlled by manual tuning of PI as well as significant reduction in peak time and settling time in DC-link voltage.https://journals.rcsi.science/2658-4123/article/viewFile/264106/273632genetic algorithmsimulated annealingpattern searchhybridized genetic algorithm and simulated annealing |
| spellingShingle | Amit Verma Prabhakar Tiwari Desh Deepak Sharma Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System Инженерные технологии и системы genetic algorithm simulated annealing pattern search hybridized genetic algorithm and simulated annealing |
| title | Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System |
| title_full | Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System |
| title_fullStr | Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System |
| title_full_unstemmed | Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System |
| title_short | Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System |
| title_sort | combination of evolutionary algorithms and direct search approaches for improving the dynamic performance of grid connected solar power system |
| topic | genetic algorithm simulated annealing pattern search hybridized genetic algorithm and simulated annealing |
| url | https://journals.rcsi.science/2658-4123/article/viewFile/264106/273632 |
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