As the ratio of newly installed power generation utilizing power electronic converters increases, it results in a decrease in the overall inertia and damping of the power system, as well as the decrease in its ability to resist interference. Aiming to address this issue, the authors propose an adaptive optimal control approach for the parameter in the virtual synchronous generator (VSG). This strategy considers the power angle curve and analyzes the principles of inertia and damping within the oscillation period and its range of values. By coordinating the values of parameters, it achieves the optimization of these parameters. At the same time, in order to take into account the demand for fast regulation response under normal operation control conditions and the demand for synchronization support under disturbance fault conditions, a multi‐mode switching control strategy including virtual synchronization control and conventional PQ control is further proposed. Based on MATLAB/Simulink software, the strategies mentioned above have been proven through simulation. The findings testify the proposed method can significantly enhance the regulation response characteristics of the VSG by optimizing its parameters. Additionally, it enables smooth switching of the control mode independently, based on the specific requirements of different control scenarios. This approach fully leverages the virtual synchronous support and fast regulation characteristics of the power electronic converter, and has practical engineering value.

The volatility and randomness of the source-load sides increase the difficulty for system frequency regulation, while flexible loads like thermostatically controlled loads (TCLs) and hydrogen energy storage system (HESS) can be used to provide frequency auxiliary services. In this article, a hierarchical frequency control framework is established, with TCLs and HESS interacting in a distributed cooperative way to track unmatched power. Then, power allocation principles are proposed, which realizes the rational utilization of various resources and ensures the close tracking of the upper-level power targets. Further, a leader–follower distributed dynamic event-triggered control strategy is designed to guarantee fast convergence speed and synchronization accuracy, where power transmission on demand is realized to save limited network resources. Moreover, sufficient conditions are derived to ensure the stability of the distributed TCLs and HESS system by combining the Lyapunov theory. Finally, case studies assess that the proposed strategy guarantees the effectiveness and rapidity of the frequency control, meanwhile reducing the communication burden.

Hydrogen energy represents an ideal medium for energy storage. By integrating hydrogen power conversion, utilization, and storage technologies with distributed wind and photovoltaic power generation techniques, it is possible to achieve complementary utilization and synergistic operation of multiple energy sources in the form of microgrids. However, the diverse operational mechanisms, varying capacities, and distinct forms of distributed energy sources within hydrogen-coupled microgrids complicate their operational conditions, making fine-tuned scheduling management and economic operation challenging. In response, this paper proposes an energy management method for hydrogen-coupled microgrids based on the deep deterministic policy gradient (DDPG). This method leverages predictive information on photovoltaic power generation, load power, and other factors to simulate energy management strategies for hydrogen-coupled microgrids using deep neural networks and obtains the optimal strategy through reinforcement learning, ultimately achieving optimized operation of hydrogen-coupled microgrids under complex conditions and uncertainties. The paper includes analysis using typical case studies and compares the optimization effects of the deep deterministic policy gradient and deep Q networks, validating the effectiveness and robustness of the proposed method.

It is necessary to model photovoltaic generation system based power system electromechanical transient time scales for large-scale PV connected to power system stability analysis. The model should reflect the non-linear output characteristics, fault ride-through response characteristics and output limits of photovoltaic generation system. A PV model used to meet these demands is proposed in this paper. Base on a 3-generator, 9-bus power system, the comparison and verification of the model is carried out in both DIgSILENT/PowerFactory and PSASP simulation environment

With the large-scale integration of intermittent renewable energy generation presented by wind and photovoltaic power, the security and stability of power system operations have been challenged. Therefore, this article proposes a control strategy of a hydrogen production system based on renewable energy power generation to enable the fast frequency response of a grid. Firstly, based on the idea of virtual synchronous control, a fast frequency response control transformation strategy for the grid-connected interface of hydrogen production systems for renewable energy power generation is proposed to provide active power support when the grid frequency is disturbed. Secondly, based on the influence of VSG’s inertia and damping coefficient on the dynamic characteristics of the system, a VSG adaptive control model based on particle swarm optimization is designed. Finally, based on the Matlab/Simulink platform, a grid-connected simulation model of hydrogen production systems for renewable energy power generation is established. The results show that the interface-transformed electrolytic hydrogen production device can actively respond to the frequency disturbances of the power system and participate in primary frequency control, providing active support for the frequency stability of the power system under high-percentage renewable energy generation integration. Moreover, the system with parameter optimization has better fast frequency response control characteristics.