A Nature Inspired Optimization Algorithm for Reactive Power Control in a Power System
S. Sakthivel1, M. Gayathri2, V. Manimozhi3
1S. Sakthivel, Associate Professor, Department of Electrical and Electronics Engineering, V. R. S. College of Engineering and Technology, Villupuram (Tamil Nadu), India.
2M. Gayathri, UG Student, Department of Electrical and Electronics Engineering, V. R. S. College of Engineering and Technology, Villupuram (Tamil Nadu), India.
3V. Manimozhi, UG Student, Department of Electrical and Electronics Engineering, V. R. S. College of Engineering and Technology, Villupuram (Tamil Nadu), India.
Manuscript received on 21 March 2013 | Revised Manuscript received on 28 March 2013 | Manuscript published on 30 March 2013 | PP: 29-33 | Volume-2 Issue-1, March 2013 | Retrieval Number: A0470032113/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In power system operation, minimizing the real power loss in transmission lines and the voltage deviation at the load buses by controlling the reactive power flow is an important task. This ensures for secured operation of power systems with regard to voltage stability and economics of operation owing to loss minimization. In this paper, the nature inspired Big Bang – Big Crunch (BB-BC) algorithm is implemented to solve the multi constrained optimal reactive power flow problem in a power system. The algorithm is free from large number of operators and can be easily coded in any programming language. Generator bus voltages, transformer tap positions and settings of switched shunt var compensators are used as decision variables to control the reactive power flow. BB-BC algorithm is tested on the standard IEEE-30 bus test system and the results are compared with other methods to prove the effectiveness of the new algorithm. The results are quite encouraging and the algorithm is found to be efficient
Keywords: Big Bang–Big Crunch Algorithm, Optimal Reactive Power Flow, Loss Minimization, Optimal Reactive Power Flow Control.
Scope of the Article: Discrete Optimization