In the practical production environment, the complexity and variability of hydroelectric units often result in a need for more fault data, leading to inadequate accuracy in fault identification for data-driven intelligent diagnostic models. To address this issue, this paper introduces a novel fault diagnosis method tailored for unbalanced small-sample states in hydroelectric units based on the Wasserstein generative adversarial network (W-GAN). Firstly, the fast Fourier transform is used to convert the signal from the time domain to the frequency domain to obtain the spectral data, and the W-GAN is trained to generate false spectral data with the same probability distribution as the real fault data, which are combined with the actual data and inputted into the 1D-CNN for feature extraction and fault diagnosis. In order to assess the effectiveness of the proposed model, a case study was conducted using actual data from a domestic hydropower plant, and the experimental results show that the sample features can be effectively enriched via data enhancement performed on small-sample data to improve the accuracy of fault diagnosis, which verifies the effectiveness of the method proposed in this paper.

Because a single monitoring index cannot fully reflect the overall operating status of the hydropower unit, a comprehensive state evaluation model for hydropower units based on the analytic hierarchy process (AHP) and the Gaussian threshold improved fuzzy evaluation is proposed. First, the unit equipment was divided into a hierarchical system, and a three-tier structure system (target layer-project layer-index layer) of the unit was constructed, and the weight of each component in the system was determined by the comprehensive weighting method. Secondly, according to the characteristics of the normal distribution of the historical health data of the unit, the upper and lower limits of the index were determined based on the Gaussian threshold principle, the real-time monitoring index degradation degree was calculated according to the index limit, and the degradation degree was applied to the fuzzy evaluation model to obtain the fuzzy judgment matrix. The result of assessment was divided into four sections: good, qualified, vigilant, and abnormal. Finally, combined with the unit hierarchical structure system, the weighted calculation of the fuzzy judgment matrix of each indicator, the overall fuzzy judgment matrix of the upper-level indicators of the unit was obtained, and the operating status of the unit was judged according to the matrix. Taking a real power plant unit as an example, the model was verified, and compared with other evaluation methods, the effectiveness and advantages of the proposed method were verified. In addition, the method proposed in this paper effectively solved the problems of index weighting and index limit determination in the existing model of unit condition evaluation.

Speed governing control is significant in ensuring the stable operation of pumped storage units. In this study, a state-space equation mathematical model of the pumped storage governing system considering the complex hydraulic pipeline structure of the pumped storage plant is proposed to describe the system’s dynamic behaviors under small disturbance conditions. Considering the frequent operating condition transitions and the complicated nonlinear dynamic characteristics of the pumped storage units, the fractional-order PID (FOPID) scheme that possesses a higher degree of control freedom than the traditional PID scheme is discussed in detail. To optimize the control parameters of the unit governor, an improved gravitational search algorithm (IGSA) that combines the basic searching mechanisms of the gravitational search algorithm and chaotic search, elastic sphere boundary treatment, and elite guidance strategy is developed. Comparative studies have been carried out under frequency and load disturbance conditions. Simulation results indicate that the control performance of FOPID is better than that of PID under diverse operating conditions and the proposed IGSA has satisfactory parameter optimization capability.

The penetration of distributed generators (DGs)-based power electronic devices leads to low inertia and damping properties of the modern power grid. As a result, the system becomes more susceptible to disruption and instability, particularly when the power demand changes during critical loads or the system needs to switch from standalone to a grid-connected operation mode or vice versa. Developing a robust controller to deal with these transient cases is a real challenge. The inverter control method via the virtual synchronous generator (VSG) control method is a better way to supply the system’s inertia and damping features to boost system stability. Therefore, a nonlinear control strategy for VSG with uncertain disturbance is proposed in this paper to enhance the system stability in the islanded, grid-connected, and transition modes. Firstly, the mechanical equations for a VSG’s rotor, which include virtual inertia and damping coefficient, are presented, and the matching mathematical model is produced. Then, the nonlinear backstepping controller (BSC) method combined with the extended state observer (ESO) is constructed to compensate for the uncertainty. The Lyapunov criteria were used to prove the method’s stability. Considering the issue of uncertain items, a second-order ESO is built to estimate uncertainty and external disruption. Finally, the suggested control strategy is validated through three simulation experiments; the findings reveal that the proposed control method has an excellent performance with fast response and tracking under various operating situations.

To address the problem that the hydraulic turbine governing system (HTGS) exhibits poor anti-disturbance ability and instability phenomena under traditional PID control, an improved new integral sliding mode control strategy based on a nonlinear disturbance observer (NISMC-NDO) is designed for the HTGS. This study first establishes a nonlinear mathematical model of HTGS and analyzes its dynamic characteristics. The uncertain disturbances of the system are then accurately estimated using a disturbance observer, and a suitable nonlinear gain function is designed to achieve feedforward compensation of the controller by ensuring that the disturbance observation error converges. To design the controller, a proportional-integral sliding mode surface is selected, and the sliding mode exponential convergence law is improved by using the nonlinear power combination function $fal$instead of $sign$ or $sat$. This improves the system’s stability, convergence speed, and tracking accuracy. The simulation results demonstrate that the equilibrium point can be quickly reached and stabilized by the HTGS with chaotic phenomena under the influence of NISMC-NDO. Furthermore, this paper also verifies that the designed controller has good dynamic performance. The findings of this study can serve as a valuable reference for optimizing the operation of hydraulic turbine regulation systems in control applications.

In today’s human society, diesel generators (DGs) are widely applied in the human energy and electricity supply system due to its technical, operational, and economic advantages. This paper proposes an intelligent nonlinear $H_2/H_{\infty }$ robust controller based on the chaos particle swarm gravity search optimization algorithm (CPSOGSA), which controls the speed and excitation of a DG. In this method, firstly, establish the nonlinear mathematical model of the DG, and then design the nonlinear $H_2/H_{\infty }$ robust controller based on this. The direct feedback linearization and the $H_2/H_{\infty }$ robust control theory are combined and applied. Based on the design of the integrated controller for DG speed and excitation, the system’s performance requirements are transformed into a standard robust $H_2/H_{\infty }$ control problem. The parameters of the proposed solution controller are optimized by using the proposed CPSOGSA. The introduction of CPSOGSA completes the design of an intelligent nonlinear $H_2/H_{\infty }$ robust controller for DG. The simulation is implemented in MATLAB/Simulink, and the results are compared with the PID control method. The obtained results prove that the proposed method can effectively improve the dynamic accuracy of the system and the ability to suppress disturbances and improve the stability of the system.