Short-term Load Forecasting in Power System by Hybrid Neural Network and Improved Gravitational Search Algorithm

Abstract

This paper presents a design of fuzzy power system stabilizer (FPSS) using Harmony Search Algorithm (HSA) to damp low frequency oscillation in multi-machine power system where the parameters of proposed controller are optimized offline automatically by the proposed techniques. This newly proposed controller is more efficient because it cope with oscillations and different operating points. In this strategy the controller is tuned on line from the knowledge base and fuzzy interference. Two eigenvalue-based objective functions to enhance system damping of electromechanical modes are considered. This newly developed control strategy mixed the advantage of HSA and Fuzzy controller with simple structure while is easy to implement. The New England 10-unit 39-bus standard power system and 9 buses IEEE power system, under various system configurations and loading conditions, is employed to illustrate the performance of the proposed method. The effectiveness of proposed controller is compared with other techniques. Eigenvalue analysis and nonlinear simulation results show the effectiveness of the proposed controller.

Keywords

References

 
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Journal of Modeling in Engineering
Volume 13, Issue 40
April 2015
Pages 69-77

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History

  • Receive Date: 28 January 2017
  • Revise Date: 18 September 2017
  • Accept Date: 28 January 2017

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