scholarly journals Stability and Sensitivity Analysis and Optimization Control of the Hydro-turbine Generator Unit

Author(s):  
Yousong Shi ◽  
Jianzhong Zhou

Abstract The hydro-turbine governing system (HTGS) and shafting system are mutually coupled. However, the interaction between them has always been neglected. This paper aims to explore the stability and sensitivity of the governor control parameters to the HTGS and shafting system and make the optimal control of the stable operation for the hydro-turbine generator unit(HTGU). First, a novel HTGU motion equation is proposed, which can make connections between the HTGS and the shafting system of the HTGU. And on this basis, the nonlinear coupling mathematical model of the HTGS and the shafting system is established. According to the nonlinear mathematical model, the sensitivity of the governor control parameters on the operating stability of the HTGU is obtained. Then, a multi-objective governor control parameters optimization strategy is proposed. Furthermore, the chaotic-dominated sorting genetic algorithm II(NSGA-II) and multi-objective evolutionary algorithm based on decomposition(MOEAD) were introduced to obtain the optimal control parameter and mutually verify the effectiveness of the optimization effect. Finally, the nonlinear dynamic characteristics of HTGU under optimal control were revealed. The simulation results show that the rotation speed deviation and shafting system vibrations are sensitive on the PID parameters in some ranges and the stable region will be decreased when considering the shafting system vibrations. The multi-objective PID parameter optimization strategy shows good control performance on the nonlinear dynamic characteristics of the HTGU. The shafting system vibrations excited by the coupled vibration sources are quasi-period in 3D space. In addition to this, these results and the optimization strategy can provide some bases for the design and stable operation of the HTGU.

2018 ◽  
Vol 10 (7) ◽  
pp. 168781401878483 ◽  
Author(s):  
Rong Yuan ◽  
Haiqing Li ◽  
Qingyuan Wang

In this study, an enhanced genetic algorithm is proposed to solve multi-objective design and optimization problems in practical engineering. In the given approach, designers choose available design results from the given samples first. These samples are re-ordered according to their mutual relationships. After that, designers choose an exact ratio of conformity as available field. Furthermore, more weight information can be obtained through finding the minimum value of the norm of unconformity and satisfactory samples. These samples can be used to reflect the preference chosen for Pareto design solutions. A structure design problem of speed increaser used in wind turbine generator systems is solved to show the application of the given design strategy.


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