Loadability enhancement with FACTS devices using gravitational search algorithm |
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| Affiliation: | 1. Department of Technical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran;2. Centre of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran;1. Department of Electrical and Electronics Engineering, Loyola-ICAM College of Engineering and Technology, Tamil Nadu, India;2. Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Tamil Nadu, India;3. Department of Electrical and Electronics Engineering, Kamaraj College of Engineering and Technology, Tamil Nadu, India;1. Department of Electrical and Electronics Engineering, Faculty of Engineering, Avinasilingam University, Coimbatore 641108, India;2. Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology, Coimbatore 641014, India;3. Department of Instrumentation and Control Engineering, P.S.G. College of Technology, Coimbatore 641004, India;1. The State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China;2. Robert W. Galvin Center for Electricity Innovation at Illinois Institute of Technology, Chicago, IL, 60616, USA;3. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China |
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| Abstract: | In the present work, GSA (gravitational search algorithm) based optimization algorithm is applied for the optimal allocation of FACTS devices in transmission system. IEEE 30 & IEEE 57 test bus systems are taken as standards. Both active and reactive loading of the power system is considered and the effect of FACTS devices on the power transfer capacity of the individual generator is investigated. The proposed approach of planning of reactive power sources with the FACTS devices is compared with other globally accepted techniques like GA (Genetic Algorithm), Differential Evolution (DE), and PSO (Particle Swarm Optimization). From the results obtained, it is observed that incorporating FACTS devices, loadability of the power system increases considerably and each generator present in the system is being able to dispatch significant amount of active power under different increasing loading conditions where the steam flow rate is maintained corresponding to the base active loading condition. The active power loss & operating cost also reduces by significant margin with FACTS devices at each loading condition and GSA based planning approach of reactive power sources with FACTS devices found to be the best among all the methods discussed in terms of reducing active power loss and total operating cost of the system under all active and reactive loading situations. |
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| Keywords: | FACTS devices Active power loss Operating cost Loadability Gravitational search algorithm |
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