A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems
The current research investigates a new and unique Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) algorithm for solving large-scale Optimal Power Flow (OPF) problems of complex power systems, including renewable energy sources and Flexible AC Transmission Systems (FACTS). A re...
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MDPI AG
2022-11-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/22/3825 |
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| author | Sundaram B. Pandya James Visumathi Miroslav Mahdal Tapan K. Mahanta Pradeep Jangir |
| author_facet | Sundaram B. Pandya James Visumathi Miroslav Mahdal Tapan K. Mahanta Pradeep Jangir |
| author_sort | Sundaram B. Pandya |
| collection | DOAJ |
| description | The current research investigates a new and unique Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) algorithm for solving large-scale Optimal Power Flow (OPF) problems of complex power systems, including renewable energy sources and Flexible AC Transmission Systems (FACTS). A recently reported single-objective generalized normal distribution optimization algorithm is transformed into the MOGNDO algorithm using the nondominated sorting and crowding distancing mechanisms. The OPF problem gets even more challenging when sources of renewable energy are integrated into the grid system, which are unreliable and fluctuating. FACTS devices are also being used more frequently in contemporary power networks to assist in reducing network demand and congestion. In this study, a stochastic wind power source was used with different FACTS devices, including a static VAR compensator, a thyristor- driven series compensator, and a thyristor—driven phase shifter, together with an IEEE-30 bus system. Positions and ratings of the FACTS devices can be intended to reduce the system’s overall fuel cost. Weibull probability density curves were used to highlight the stochastic character of the wind energy source. The best compromise solutions were obtained using a fuzzy decision-making approach. The results obtained on a modified IEEE-30 bus system were compared with other well-known optimization algorithms, and the obtained results proved that MOGNDO has improved convergence, diversity, and spread behavior across PFs. |
| first_indexed | 2024-03-09T18:22:36Z |
| format | Article |
| id | doaj.art-8c56b0dd2a134d13a99658c780f8ae28 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T18:22:36Z |
| publishDate | 2022-11-01 |
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| series | Electronics |
| spelling | doaj.art-8c56b0dd2a134d13a99658c780f8ae282023-11-24T08:11:06ZengMDPI AGElectronics2079-92922022-11-011122382510.3390/electronics11223825A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow ProblemsSundaram B. Pandya0James Visumathi1Miroslav Mahdal2Tapan K. Mahanta3Pradeep Jangir4Department of Electrical Engineering, Shri K.J. Polytechnic, Bharuch 392 001, IndiaDepartment of Computer Science and Engineering, Vel Tech Rangarajan Dr Sangunthala R&D Institute of Science and Technology, Chennai 600 062, IndiaDepartment of Control Systems and Instrumentation, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 708 00 Ostrava, Czech RepublicSchool of Mechanical Engineering, Vellore Institute of Technology, Chennai 600 127, IndiaRajasthan Rajya Vidyut Prasaran Nigam, Losal, Sikar 332 025, IndiaThe current research investigates a new and unique Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) algorithm for solving large-scale Optimal Power Flow (OPF) problems of complex power systems, including renewable energy sources and Flexible AC Transmission Systems (FACTS). A recently reported single-objective generalized normal distribution optimization algorithm is transformed into the MOGNDO algorithm using the nondominated sorting and crowding distancing mechanisms. The OPF problem gets even more challenging when sources of renewable energy are integrated into the grid system, which are unreliable and fluctuating. FACTS devices are also being used more frequently in contemporary power networks to assist in reducing network demand and congestion. In this study, a stochastic wind power source was used with different FACTS devices, including a static VAR compensator, a thyristor- driven series compensator, and a thyristor—driven phase shifter, together with an IEEE-30 bus system. Positions and ratings of the FACTS devices can be intended to reduce the system’s overall fuel cost. Weibull probability density curves were used to highlight the stochastic character of the wind energy source. The best compromise solutions were obtained using a fuzzy decision-making approach. The results obtained on a modified IEEE-30 bus system were compared with other well-known optimization algorithms, and the obtained results proved that MOGNDO has improved convergence, diversity, and spread behavior across PFs.https://www.mdpi.com/2079-9292/11/22/3825FACTS controllerMO-OPFmeta-heuristicsprobability density functionstochasticWTGS |
| spellingShingle | Sundaram B. Pandya James Visumathi Miroslav Mahdal Tapan K. Mahanta Pradeep Jangir A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems Electronics FACTS controller MO-OPF meta-heuristics probability density function stochastic WTGS |
| title | A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems |
| title_full | A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems |
| title_fullStr | A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems |
| title_full_unstemmed | A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems |
| title_short | A Novel MOGNDO Algorithm for Security-Constrained Optimal Power Flow Problems |
| title_sort | novel mogndo algorithm for security constrained optimal power flow problems |
| topic | FACTS controller MO-OPF meta-heuristics probability density function stochastic WTGS |
| url | https://www.mdpi.com/2079-9292/11/22/3825 |
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