A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem
This paper presents an improved Teaching-Learning-Based Optimization (TLBO) for optimal tuning of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. The original TLBO is characterized by easy implementation and is mainly free of control parameters. Unfortunately, TLB...
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2021
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oai:doaj.org-article:f0798c7a30154fbb951a25842c09cce02021-11-11T16:02:53ZA New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem10.3390/en142173121996-1073https://doaj.org/article/f0798c7a30154fbb951a25842c09cce02021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/7312https://doaj.org/toc/1996-1073This paper presents an improved Teaching-Learning-Based Optimization (TLBO) for optimal tuning of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. The original TLBO is characterized by easy implementation and is mainly free of control parameters. Unfortunately, TLBO may suffer from population diversity losses in some cases, leading to local optimum and premature convergence. In this study, three approaches are considered for improving the original TLBO (i) randomness improvement, (ii) three new mutation strategies (iii) hyperchaotic perturbation strategy. In the first approach, all random numbers in the original TLBO are substituted by the hyperchaotic map sequence to boost exploration capability. In the second approach, three mutations are carried out to explore a new promising search space. The obtained solution is further improved in the third strategy by implementing a new perturbation equation. The proposed HTLBO was evaluated with 26 test functions. The obtained results show that HTLBO outperforms the TBLO algorithm and some state-of-the-art algorithms in robustness and accuracy in almost all experiments. Moreover, the efficacy of the proposed HTLBO is justified by involving it in the power system stability problem. The results consist of the Integral of Absolute Error (ITAE) and eigenvalue analysis of electromechanical modes demonstrate the superiority and the potential of the proposed HTLBO based PSSs and SVC controllers over a wide range of operating conditions. Besides, the advantage of the proposed coordination design controllers was confirmed by comparing them to PSSs and SVC tuned individually.Anouar FarahAkram BelaziKhalid AlqununAbdulaziz AlmalaqBadr M. AlshammariMohamed Bechir Ben HamidaRabeh AbbassiMDPI AGarticlepower system stabilityelectromechanical oscillationsPSSSVCTLBOhyperchaotic TLBOTechnologyTENEnergies, Vol 14, Iss 7312, p 7312 (2021) |
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power system stability electromechanical oscillations PSS SVC TLBO hyperchaotic TLBO Technology T |
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power system stability electromechanical oscillations PSS SVC TLBO hyperchaotic TLBO Technology T Anouar Farah Akram Belazi Khalid Alqunun Abdulaziz Almalaq Badr M. Alshammari Mohamed Bechir Ben Hamida Rabeh Abbassi A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem |
| description |
This paper presents an improved Teaching-Learning-Based Optimization (TLBO) for optimal tuning of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. The original TLBO is characterized by easy implementation and is mainly free of control parameters. Unfortunately, TLBO may suffer from population diversity losses in some cases, leading to local optimum and premature convergence. In this study, three approaches are considered for improving the original TLBO (i) randomness improvement, (ii) three new mutation strategies (iii) hyperchaotic perturbation strategy. In the first approach, all random numbers in the original TLBO are substituted by the hyperchaotic map sequence to boost exploration capability. In the second approach, three mutations are carried out to explore a new promising search space. The obtained solution is further improved in the third strategy by implementing a new perturbation equation. The proposed HTLBO was evaluated with 26 test functions. The obtained results show that HTLBO outperforms the TBLO algorithm and some state-of-the-art algorithms in robustness and accuracy in almost all experiments. Moreover, the efficacy of the proposed HTLBO is justified by involving it in the power system stability problem. The results consist of the Integral of Absolute Error (ITAE) and eigenvalue analysis of electromechanical modes demonstrate the superiority and the potential of the proposed HTLBO based PSSs and SVC controllers over a wide range of operating conditions. Besides, the advantage of the proposed coordination design controllers was confirmed by comparing them to PSSs and SVC tuned individually. |
| format |
article |
| author |
Anouar Farah Akram Belazi Khalid Alqunun Abdulaziz Almalaq Badr M. Alshammari Mohamed Bechir Ben Hamida Rabeh Abbassi |
| author_facet |
Anouar Farah Akram Belazi Khalid Alqunun Abdulaziz Almalaq Badr M. Alshammari Mohamed Bechir Ben Hamida Rabeh Abbassi |
| author_sort |
Anouar Farah |
| title |
A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem |
| title_short |
A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem |
| title_full |
A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem |
| title_fullStr |
A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem |
| title_full_unstemmed |
A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem |
| title_sort |
new design method for optimal parameters setting of psss and svc damping controllers to alleviate power system stability problem |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/f0798c7a30154fbb951a25842c09cce0 |
| work_keys_str_mv |
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