With the advancement of new power system construction, distribution networks are gradually transforming from being a simple energy receiver and distributor to being an integrated power network that integrates sources, networks, loads, and energy storage with interactive and flexible coupling with the upper-level power grid. However, traditional distribution networks lack active control and distribution capabilities, failing to meet the demands of network transformation and upgrading. To address this issue, this paper proposes a method for solving AC/DC power flow calculation considering an electric energy router (EER) based on an alternating iterative method. Initially, the model for the multi-port EER and three types of power flow models for the AC distribution network, DC distribution network, and EER are constructed. By leveraging the properties of the EER and the hybrid power flow calculation model, a method is proposed for calculating the power flow in the AC/DC hybrid distribution network considering the EER. Finally, by solving the power flow in a medium- and low-voltage AC/DC distribution system, the adaptability of the proposed method is compared. The results demonstrate that the AC/DC hybrid distribution network power flow calculation method established in this paper, which incorporates the EER, possesses high accuracy and adaptability, with an error margin of less than 0.05%.

With the increasing proportion of new energy in power systems, the instability issues of novel power systems become more prominent. This paper addresses the transient overvoltage problem in wind power DC transmission systems by proposing a method for transient overvoltage suppression based on doubly-fed wind turbines, high-voltage DC transmission systems, and SVC control parameter optimization. The electromagnetic transient model of the wind power DC transmission system is combined with intelligent optimization algorithms through joint invocation to achieve coordinated optimization of control parameters. Case studies validate the effectiveness of the proposed model and method. The results indicate that the improved genetic algorithm, SEGA, proposed in this paper, effectively suppresses overvoltage at the grid connection point of wind turbines. Furthermore, by simultaneously applying coordinated control strategies based on DFIG and SVC and optimizing parameters of HVDC, DFIG, and SVC, transient overvoltage phenomena can be effectively eliminated.