Grid voltage swell causes transient DC flux component on doubly fed induction generator (DFIG) stator winding even stronger than grid voltage dip , resulting in a much more serious stator, rotor current, and torque oscillation. The current study analyzes the dynamic behavior of DFIG during gird voltage swell. Based on the analysis results, the virtual resistance control strategy manages best to suppress the rotor current and torque oscillation, but prolongs the transient duration, resulting in a higher rotor voltage. Thus, this study proposed a virtual impedance control strategy to enhance the high voltage ride-through capability of DFIG. In order to improve the dynamic performance, the optimization algorithm of virtual impedance is proposed in the paper. The effectiveness of the proposed control strategy was verified by simulation and experimental results. Index Terms-Wind power generator, doubly fed induction generator (DFIG), virtual impedance, high voltage ride-throughManuscript

Conventional model predictive direct torque control (MP-DTC) of permanent magnet synchronous generator (PMSG) suffers from weighing factor tuning work and relatively large calculation amount. This study proposes a simplified MP-DTC method without weighting factors for PMSG-based wind power system. First, the torque and stator flux magnitude are predicted on the stationary reference frame instead of on the synchronous rotating reference frame, hence reducing the calculation amount. Second, a new cost function based on the torque and the reactive torque is developed in this study. As the torque and the reactive torque have the same order of magnitude, the weighting factor which is needed in the conventional MP-DTC system is eliminated. Meanwhile, the stator current and stator flux magnitude can be controlled indirectly by controlling the torque and reactive torque simultaneously, which ensures the stability of the system. Besides, the robustness of the proposed strategy to unknown PMSG parameter variations is improved to a certain extent. The experimental results validate the effectiveness of the proposed method.

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The rapid development of renewable energy power has improved global energy and environmental problems. However, with the high volatility of renewable energy, it is an important challenge to guarantee the consumption of renewable energy and the reliable operation of high percentage renewable energy power systems. To solve this problem, this paper proposes a tracking absorption strategy for renewable energy based on the interaction between the supply side and the demand side, which adjusts the charging process of electric vehicles (EVs) through electric vehicle aggregator (EVA) to realize the tracking absorption of renewable energy abandoned electricity. In view of this process, we analyze the interaction among power grid, EVA and renewable energy generation (REG) as well as their market characteristics. The master-slave game model of EVA and REG was constructed considering the charging behavior characteristics of EVs and the output characteristics of REGs. Then the model solving strategy based on soft actor-critic (SAC) algorithm is proposed, and the REG pricing strategy and EVA scheduling strategy are calculated to optimize the mutual benefits. The case analysis shows that, under the same scale of electric vehicles, the proposed method can promote about 93.89% of the power abandonment consumption of wind power system, 96.00% of the photovoltaic system, and 97.41% of the wind-solar system. This strategy reduces the electricity purchase cost of EVA, promotes the interaction among renewable energy , vehicles and power grid, and improves the utilization efficiency of renewable energy.

At the present stage, China’s energy development has the following characteristics: continuous development of new energy technology, continuous expansion of comprehensive energy system scale, and wide application of multi-energy coupling technology. Under the new situation, the accurate prediction of power load is the key to alleviate the problem that the planning and dispatching of the current power system is more complex and more demanding than the traditional power system. Therefore, firstly, this paper designs the calculation method of the power load demand of the grid under the multi-energy coupling mode, aiming at the important role of the grid in the power dispatching in the comprehensive energy system. This load calculation method for regional power grid operating load forecasting is proposed for the first time, which takes the total regional load demand and multi-energy coupling into consideration. Then, according to the participants and typical models in the multi-energy coupling mode, the key factors affecting the load in the multi-energy coupling mode are analyzed. At this stage, we fully consider the supply side resources and the demand side resources, innovatively extract the energy system structure characteristics under the condition of multi-energy coupling technology, and design a key factor index system for this mode. Finally, a least squares support vector machine optimized by the minimal redundancy maximal relevance model and the adaptive fireworks algorithm (mRMR-AFWA-LSSVM) is proposed, to carry out load forecasting for multi-energy coupling scenarios. Aiming at the complexity energy system analysis and prediction accuracy improvement of multi-energy coupling scenarios, this method applies minimal redundancy maximal relevance model to the selection of key factors in scenario analysis. It is also the first time that adaptive fireworks algorithm is applied to the optimization of adaptive fireworks algorithm, and the results show that the model optimization effect is good. In the case of A region quarterly load forecasting in southwest China, the average absolute percentage error of a least squares support vector machine optimized by the minimal redundancy maximal relevance model and the adaptive fireworks algorithm (mRMR-AFWA-LSSVM) is 2.08%, which means that this model has a high forecasting accuracy.