Optimization strategy of power regulation performance of the hydropower station monitoring control system considering vibration avoidance operation of units

With the large-scale integration of new energy sources into the grid, hydropower units are required to undertake increasing regulation tasks. However, due to the nonlinear characteristics of hydroturbines, turbine vibration, and the hydraulic inertia of the waterway system, power regulation performance is often inadequate, and prolonged operation within vibration zones occurs. These issues collectively threaten operational stability of the units. Multi-objective optimized control for power regulation has thus become a cutting-edge research area in hydroturbine control systems. Nevertheless, few studies have focused on the simultaneous optimization of power regulation performance and vibration avoidance operation for hydropower units under multi-unit joint operation. To address this gap, this study establishes a power regulation simulation model of the parallel-operated hydropower units, which incorporates the waterway system, hydro-turbine, and control system. The influences of key factors such as the hydropower station monitoring control system, governor system, and load distribution coefficients are examined. Objective functions are formulated to evaluate the effectiveness of both power regulation performance and vibration avoidance. An improved multi-objective optimization algorithm is employed to optimize the control parameters of the hydropower units, and the Technique for Order Preference by Similarity to Ideal Solution decision-making method is applied for solution evaluation and selection. The proposed optimization strategy significantly enhances the power regulation performance and vibration avoidance operformance, which is evidenced by a reduction in regulation time of at least 195.32s and a decrease in vibration zones dwell time by over 93.3%. The developed power regulation simulation model and the multi-objective parameter optimization approach can effectively inform the operational optimization of actual hydropower units.