Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems
Abstract Today, reliable power delivery and increasing demand are important issues in modern power systems. Flexible Alternating Current Transmission Systems (FACTS) devices are used to control transmission line parameters to increase power transfer and stability. Nevertheless, the problem of determ...
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2025-01-01
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| Series: | International Journal of Computational Intelligence Systems |
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| Online Access: | https://doi.org/10.1007/s44196-024-00727-x |
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| author | Mohammad Aljaidi Pradeep Jangir Sunilkumar P. Agrawal Sundaram B. Pandya Anil Parmar Ali Fayez Alkoradees Arpita Aseel Smerat |
| author_facet | Mohammad Aljaidi Pradeep Jangir Sunilkumar P. Agrawal Sundaram B. Pandya Anil Parmar Ali Fayez Alkoradees Arpita Aseel Smerat |
| author_sort | Mohammad Aljaidi |
| collection | DOAJ |
| description | Abstract Today, reliable power delivery and increasing demand are important issues in modern power systems. Flexible Alternating Current Transmission Systems (FACTS) devices are used to control transmission line parameters to increase power transfer and stability. Nevertheless, the problem of determining the optimal placement and sizing of these devices is still challenging, as the placement and sizing of the devices affects generation costs, power losses, voltage stability, and system reliability. This study proposes the Fata Morgana Algorithm (FATA), an optimization algorithm inspired by the natural process of mirage formation to optimize placement and sizing of FACTS devices in an IEEE 30 bus system with wind turbine integration. The FATA algorithm is evaluated against recently developed and improved optimization techniques, such as rime-ice formation phenomenon based Improved RIME (IRIME) Algorithm, Newton–Raphson-Based Optimization (NRBO), Resistance Capacitance Algorithm (RCA), Krill Optimization Algorithm (KOA), and Grey Wolf Optimizer (GWO), across multiple optimization objectives: reduction in generation cost, reduction in power loss and combined generation cost plus power loss, termed as Gross cost function. Results obtained show that FATA consistently outperforms the other algorithms in terms of convergence and solution quality, offering a robust approach to solving single objective optimization problems. FATA theoretically provides a good balance between exploration and exploitation, and produces better global solutions. It practically increases power system efficiency by lowering operational costs and losses and improving stability. Results indicate that the FATA algorithm produced minimum generation cost of 807.0405 $/h, which is 0.088–0.426% less than the competing algorithms. It also reduced power losses to 5.5917 MW, which is 1.095–6.781% less than other methods. For gross cost minimization, the FATA algorithm achieved a minimum gross cost of 1366.3727 $/h, which is 0.4799% better than the next best algorithm and 3.2261% better than the worst. The results also show that FATA is robust in solving complex optimization problems in power systems, and it provides significant improvements in run time and convergence efficiency. The main advantage for readers is that FATA provides a reliable and efficient way to optimize power systems. Future work could also investigate the application of FATA in real time, as well as in larger power networks with more renewable energy sources. |
| format | Article |
| id | doaj-art-92141499a50d4c5691e8fe6a95a6e783 |
| institution | Kabale University |
| issn | 1875-6883 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
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| series | International Journal of Computational Intelligence Systems |
| spelling | doaj-art-92141499a50d4c5691e8fe6a95a6e7832025-01-26T12:51:43ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832025-01-0118113810.1007/s44196-024-00727-xOptimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based SystemsMohammad Aljaidi0Pradeep Jangir1Sunilkumar P. Agrawal2Sundaram B. Pandya3Anil Parmar4Ali Fayez Alkoradees5Arpita6Aseel Smerat7Department of Computer Science, Faculty of Information Technology, Zarqa UniversityUniversity Centre for Research and Development, Chandigarh UniversityDepartment of Electrical Engineering, Government Engineering CollegeDepartment of Electrical Engineering, Shri K. J. PolytechnicDepartment of Electrical Engineering, Shri K. J. PolytechnicUnit of Scientific Research, Applied College, Qassim UniversityDepartment of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical SciencesCentre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara UniversityAbstract Today, reliable power delivery and increasing demand are important issues in modern power systems. Flexible Alternating Current Transmission Systems (FACTS) devices are used to control transmission line parameters to increase power transfer and stability. Nevertheless, the problem of determining the optimal placement and sizing of these devices is still challenging, as the placement and sizing of the devices affects generation costs, power losses, voltage stability, and system reliability. This study proposes the Fata Morgana Algorithm (FATA), an optimization algorithm inspired by the natural process of mirage formation to optimize placement and sizing of FACTS devices in an IEEE 30 bus system with wind turbine integration. The FATA algorithm is evaluated against recently developed and improved optimization techniques, such as rime-ice formation phenomenon based Improved RIME (IRIME) Algorithm, Newton–Raphson-Based Optimization (NRBO), Resistance Capacitance Algorithm (RCA), Krill Optimization Algorithm (KOA), and Grey Wolf Optimizer (GWO), across multiple optimization objectives: reduction in generation cost, reduction in power loss and combined generation cost plus power loss, termed as Gross cost function. Results obtained show that FATA consistently outperforms the other algorithms in terms of convergence and solution quality, offering a robust approach to solving single objective optimization problems. FATA theoretically provides a good balance between exploration and exploitation, and produces better global solutions. It practically increases power system efficiency by lowering operational costs and losses and improving stability. Results indicate that the FATA algorithm produced minimum generation cost of 807.0405 $/h, which is 0.088–0.426% less than the competing algorithms. It also reduced power losses to 5.5917 MW, which is 1.095–6.781% less than other methods. For gross cost minimization, the FATA algorithm achieved a minimum gross cost of 1366.3727 $/h, which is 0.4799% better than the next best algorithm and 3.2261% better than the worst. The results also show that FATA is robust in solving complex optimization problems in power systems, and it provides significant improvements in run time and convergence efficiency. The main advantage for readers is that FATA provides a reliable and efficient way to optimize power systems. Future work could also investigate the application of FATA in real time, as well as in larger power networks with more renewable energy sources.https://doi.org/10.1007/s44196-024-00727-xOptimal power flow (OPF)Flexible alternating current transmission systems (FACTS)Fata Morgana Algorithm (FATA)Renewable energy integration |
| spellingShingle | Mohammad Aljaidi Pradeep Jangir Sunilkumar P. Agrawal Sundaram B. Pandya Anil Parmar Ali Fayez Alkoradees Arpita Aseel Smerat Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems International Journal of Computational Intelligence Systems Optimal power flow (OPF) Flexible alternating current transmission systems (FACTS) Fata Morgana Algorithm (FATA) Renewable energy integration |
| title | Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems |
| title_full | Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems |
| title_fullStr | Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems |
| title_full_unstemmed | Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems |
| title_short | Optimizing FACTS Device Placement Using the Fata Morgana Algorithm: A Cost and Power Loss Minimization Approach in Uncertain Load Scenario-Based Systems |
| title_sort | optimizing facts device placement using the fata morgana algorithm a cost and power loss minimization approach in uncertain load scenario based systems |
| topic | Optimal power flow (OPF) Flexible alternating current transmission systems (FACTS) Fata Morgana Algorithm (FATA) Renewable energy integration |
| url | https://doi.org/10.1007/s44196-024-00727-x |
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