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Energies 2018, 11(9), 2367; https://doi.org/10.3390/en11092367

A Mixed-Strategy-Based Whale Optimization Algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect

School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Received: 25 July 2018 / Revised: 30 August 2018 / Accepted: 4 September 2018 / Published: 7 September 2018
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Abstract

For solving the parameter optimization problem of a hydraulic turbine governing system (HTGS) with a delayed water hammer (DWH) effect, a Mixed-Strategy-based Whale Optimization Algorithm (MSWOA) is proposed in this paper, in which three improved strategies are designed and integrated to promote the optimization ability. Firstly, the movement strategies of WOA have been improved to balance the exploration and exploitation. In the improved movement strategies, a dynamic ratio based on improved JAYA algorithm is applied on the strategy of searching for prey and a chaotic dynamic weight is designed for improving the strategies of bubble-net attacking and encircling prey. Secondly, a guidance of the elite’s memory inspired by Particle swarm optimization (PSO) is proposed to lead the movement of the population to accelerate the convergence speed. Thirdly, the mutation strategy based on the sinusoidal chaotic map is employed to avoid prematurity and local optimum points. The proposed MSWOA are compared with six popular meta-heuristic optimization algorithms on 23 benchmark functions in numerical experiments and the results show that the MSWOA has achieved significantly better performance than others. Finally, the MSWOA is applied on parameter identification problem of HTGS with a DWH effect, and the comparative results confirm the effectiveness and identification accuracy of the proposed method. View Full-Text
Keywords: whale optimization algorithm; meta-heuristic; improved JAYA algorithm; chaotic mutation; HTGS; parameter identification whale optimization algorithm; meta-heuristic; improved JAYA algorithm; chaotic mutation; HTGS; parameter identification
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Ding, T.; Chang, L.; Li, C.; Feng, C.; Zhang, N. A Mixed-Strategy-Based Whale Optimization Algorithm for Parameter Identification of Hydraulic Turbine Governing Systems with a Delayed Water Hammer Effect. Energies 2018, 11, 2367.

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