Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices
Abstract This paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1 + PI) controller for Automatic generation control (AGC) of a power system with Flexible AC Transmission system (FACTS) devices. Three differently rated reheat turbine operated thermal units with appropriate gen...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-03-01
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| Series: | Protection and Control of Modern Power Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s41601-021-00187-x |
| _version_ | 1818610654870765568 |
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| author | Pratap Chabdra Nayak Ramesh Chandra Prusty Sidhartha Panda |
| author_facet | Pratap Chabdra Nayak Ramesh Chandra Prusty Sidhartha Panda |
| author_sort | Pratap Chabdra Nayak |
| collection | DOAJ |
| description | Abstract This paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1 + PI) controller for Automatic generation control (AGC) of a power system with Flexible AC Transmission system (FACTS) devices. Three differently rated reheat turbine operated thermal units with appropriate generation rate constraint (GRC) are considered along with different FACTS devices. A new multistage controller design structure of a PDF plus (1 + PI) is introduced in the FACTS empowered power system for AGC while the controller gains are tuned by the GOA. The superiority of the proposed algorithm over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms is demonstrated. The dynamic responses of GOA optimized PDF plus (1 + PI) are compared with PIDF, PID and PI controllers on the same system. It is demonstrated that GOA optimized PDF plus (1 + PI) controller provides optimum responses in terms of settling time and peak deviations compared to other controllers. In addition, a GOA-tuned PDF plus (1 + PI) controller with Interline Power Flow Controller (IPFC) exhibits optimal results compared to other FACTS devices. The sturdiness of the projected controller is validated using sensitivity analysis with numerous load patterns and a wide variation of parameterization. To further validate the real-time feasibility of the proposed method, experiments using OPAL-RT OP5700 RCP/HIL and FPGA based real-time simulations are carried out. |
| first_indexed | 2024-12-16T15:17:53Z |
| format | Article |
| id | doaj.art-2a5762b4c1ad496f8e312c24d9c4a005 |
| institution | Directory Open Access Journal |
| issn | 2367-2617 2367-0983 |
| language | English |
| last_indexed | 2024-12-16T15:17:53Z |
| publishDate | 2021-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Protection and Control of Modern Power Systems |
| spelling | doaj.art-2a5762b4c1ad496f8e312c24d9c4a0052022-12-21T22:26:44ZengSpringerOpenProtection and Control of Modern Power Systems2367-26172367-09832021-03-016111510.1186/s41601-021-00187-xGrasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devicesPratap Chabdra Nayak0Ramesh Chandra Prusty1Sidhartha Panda2Department of Electrical Engineering, VSSUTDepartment of Electrical Engineering, VSSUTDepartment of Electrical Engineering, VSSUTAbstract This paper uses a Grasshopper Optimization Algorithm (GOA) optimized PDF plus (1 + PI) controller for Automatic generation control (AGC) of a power system with Flexible AC Transmission system (FACTS) devices. Three differently rated reheat turbine operated thermal units with appropriate generation rate constraint (GRC) are considered along with different FACTS devices. A new multistage controller design structure of a PDF plus (1 + PI) is introduced in the FACTS empowered power system for AGC while the controller gains are tuned by the GOA. The superiority of the proposed algorithm over the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms is demonstrated. The dynamic responses of GOA optimized PDF plus (1 + PI) are compared with PIDF, PID and PI controllers on the same system. It is demonstrated that GOA optimized PDF plus (1 + PI) controller provides optimum responses in terms of settling time and peak deviations compared to other controllers. In addition, a GOA-tuned PDF plus (1 + PI) controller with Interline Power Flow Controller (IPFC) exhibits optimal results compared to other FACTS devices. The sturdiness of the projected controller is validated using sensitivity analysis with numerous load patterns and a wide variation of parameterization. To further validate the real-time feasibility of the proposed method, experiments using OPAL-RT OP5700 RCP/HIL and FPGA based real-time simulations are carried out.https://doi.org/10.1186/s41601-021-00187-xAutomatic generation controlFACTS devicesMultistage controllerGrasshopper optimization algorithm |
| spellingShingle | Pratap Chabdra Nayak Ramesh Chandra Prusty Sidhartha Panda Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices Protection and Control of Modern Power Systems Automatic generation control FACTS devices Multistage controller Grasshopper optimization algorithm |
| title | Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices |
| title_full | Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices |
| title_fullStr | Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices |
| title_full_unstemmed | Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices |
| title_short | Grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with FACTS devices |
| title_sort | grasshopper optimization algorithm optimized multistage controller for automatic generation control of a power system with facts devices |
| topic | Automatic generation control FACTS devices Multistage controller Grasshopper optimization algorithm |
| url | https://doi.org/10.1186/s41601-021-00187-x |
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