Voltage Stability Analysis of Front-End Speed Controlled Wind Turbine Integrated into Regional Power Grid Based on Bifurcation Theory

Since wind power has characteristics such as intermittent and fluctuation, the integration of large-scale wind turbines into the power grid will bring a great impact on the voltage stability of the system. In this paper, the influence of the front-end speed controlled wind turbine (FSCWT) on the system voltage stability is studied. An actual model of the wind turbines, including the FSCWTs, connected to a regional power grid in Zhangye, Gansu Province, is established. Firstly, differential-algebraic equations (DAEs) describing the dynamic characteristics of the wind turbine are given and the mathematical model of the system includes FSCWT is established. The continuation method is used to track the balance solution of the DEAs within given parameter intervals. Based on that, the influence of the reactive power variation and wind speed fluctuation on the stability of system voltage is analyzed through both the bifurcation theory and the time-domain simulation. Results show that the Hopf bifurcation (HB) and the saddle-node bifurcation (SNB) are inherited for the system, indicating that such bifurcations are the essence of nonlinear dynamics that lead to voltage instability. The greater the disturbance of the bifurcation parameter Q1, the shorter the time of voltage collapse and the smaller the stable operation area of the system. With the increase of wind speed, the amplitude of system voltage will increase slightly, but the HB point will appear in advance, which is more likely to lead to voltage instability and further reduce the stable operation area of system voltage

On Variable-Universe Fuzzy Control for Drive Chain of Front-End Speed Regulated Wind Generator

The rapid development of wind generation technology has boosted types of the new topology wind turbines. Among the recently invented new wind turbines, the front-end speed regulated (FSR) wind turbine has attracted a lot of attention. Unlike conventional wind turbine, the speed regulation of the FSR machines is realized by adjusting the guide vane angle of a hydraulic torque converter, which is converterless and much more grid-friendly as the electrically excited synchronous generator (EESG) is also adopted. Therefore, the drive chain control of the wind turbine owns the top priority. To ensure that the FSR wind turbine performs as a general synchronous generator, this paper firstly modeled the drive chain and then proposed to use the variable-universe fuzzy approach for the drive chain control. It helps the wind generator operate in a synchronous speed and outperform other types of wind turbines. The multipopulation genetic algorithm (MPGA) is adopted to intelligently optimize the parameters of the expansion factor of the designed variable-universe fuzzy controller (VUFC). The optimized VUFC is applied to the speed control of the drive chain of the FSR wind turbine, which effectively solves the contradiction between the low precision of the fuzzy controller and the number of rules in the fuzzy control and the control accuracy. Finally, the main shaft speed of the FSR wind turbine can reach a steady-state value around 1500 rpm. The response time of the results derived using VUFC, compared with that derived from a neural network controller, is only less than 0.5 second and there is no overshoot. The case study with the real machine parameter verifies the effectiveness of the proposal and results compared with conventional neural network controller, proving its outperformance

Investigation of the influence of model control parameters on fracture characteristics of GPU parallel FDEM

Abstract Surrounding rock mass fracture characteristics play a significant role in the understanding of the CO2 geological storage and utilization (CGSU) engineering practices in abandoned mines. The combined finite discrete element method (FDEM) shows advantages in simulating fracture and fragmentation of rock-like materials, however, many computational parameters and a lack of basis for accurate values affect the simulation results. For systematic explorations of the influence of the effect of model parameters with different time steps, this study conducted different loading rate specimen tests and unloading rate tests both in laboratory-scale tests and field-scale based on the CUDA-based GPU parallel FDEM program. In laboratory-scale uniaxial compressive strength (UCS) tests, a smaller loading rate ensures a quasi-static loading process and should be below 0.1 ms−1 for simulation. Then, continuous optimization and improvement of the GPU parallel FDEM in tunnel excavation were proposed, and the model parameters reflect the continuous improvement of the simulation results. In the process, the tunnel excavation simulation method with the reduction rate of the opening zone’s Young's modulus in the excavation was performed to investigate the unloading mode and rate by continuing to optimize the GPU parallel FDEM program and model parameters. Besides, the main factor in fracture mode and failure mechanism of the surrounding rock mass also was calibrated. The results indicate that the system kinetic energy of the model is maintained at a small level with the reasonable unloading mode and critical threshold set at a small value, the damping parameters, dissipation mechanism, and excavation fractures are clearer and reasonable, and the computational cost is significantly reduced with GPU parallel FDEM