VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene
The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is emplo...
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2023-07-01
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| Series: | EAI Endorsed Transactions on Energy Web |
| Subjects: | |
| Online Access: | https://publications.eai.eu/index.php/ew/article/view/3378 |
| _version_ | 1797768499605536768 |
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| author | Ali Abderrazak Tadjeddine Mohammed Sofiane Bendelhoum Ridha Ilyas Bendjillali Hichem Hamiani Soumia Djelaila |
| author_facet | Ali Abderrazak Tadjeddine Mohammed Sofiane Bendelhoum Ridha Ilyas Bendjillali Hichem Hamiani Soumia Djelaila |
| author_sort | Ali Abderrazak Tadjeddine |
| collection | DOAJ |
| description | The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.
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| first_indexed | 2024-03-12T20:55:20Z |
| format | Article |
| id | doaj.art-a140739d5c3f456a96e91cd1f4db6210 |
| institution | Directory Open Access Journal |
| issn | 2032-944X |
| language | English |
| last_indexed | 2024-03-12T20:55:20Z |
| publishDate | 2023-07-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Energy Web |
| spelling | doaj.art-a140739d5c3f456a96e91cd1f4db62102023-07-31T18:10:15ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Energy Web2032-944X2023-07-011010.4108/ew.3378VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study KaberteneAli Abderrazak Tadjeddine0Mohammed Sofiane Bendelhoum1Ridha Ilyas Bendjillali2Hichem Hamiani3Soumia Djelaila4École Nationale Polytechnique d'OranCentre Universitaire Nour Bachir El BayadhCentre Universitaire Nour Bachir El BayadhCentre Universitaire Nour Bachir El Bayadh Centre Universitaire Nour Bachir El Bayadh The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system. https://publications.eai.eu/index.php/ew/article/view/3378Integration VREZIP dynamic models loadsAutomatic Frequency Restoration Reserve (aFRR)Power System Stabilizers (PSS)Maximum Power Point Tracking (MPPT)Particle Swarm Optimization (PSO) |
| spellingShingle | Ali Abderrazak Tadjeddine Mohammed Sofiane Bendelhoum Ridha Ilyas Bendjillali Hichem Hamiani Soumia Djelaila VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene EAI Endorsed Transactions on Energy Web Integration VRE ZIP dynamic models loads Automatic Frequency Restoration Reserve (aFRR) Power System Stabilizers (PSS) Maximum Power Point Tracking (MPPT) Particle Swarm Optimization (PSO) |
| title | VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene |
| title_full | VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene |
| title_fullStr | VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene |
| title_full_unstemmed | VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene |
| title_short | VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene |
| title_sort | vre integrating in piat grid with afrr using pss mppt and pso based techniques a case study kabertene |
| topic | Integration VRE ZIP dynamic models loads Automatic Frequency Restoration Reserve (aFRR) Power System Stabilizers (PSS) Maximum Power Point Tracking (MPPT) Particle Swarm Optimization (PSO) |
| url | https://publications.eai.eu/index.php/ew/article/view/3378 |
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