摘要
随着新能源发电与并网技术的不断发展,虛拟同步发电机(VSG)技术被广泛应用,提高了包含新能源的电力系统的稳定性,但传统的虚拟同步发电机控制方法仍存在两方面不足:一方面,VSG系统的运行参数众多,传统的参数优化计算过程十分复杂;另一方面,传统的VSG控制系统参数恒定,暂态调节过程中存在严重的超调现象。为解决上述问题,首先,以降低系统的输出误差和总谐波失真度为优化目标,利用改进粒子群算法对VSG的参数进行寻优;然后,根据VSG系统的暂态功角特性,通过灵活调节转动惯量和阻尼系数来动态地改变阻尼比进而优化系统的动态响应。最后,与现有的控制策略进行仿真对比,结果证明,该策略不仅能够在多目标优化条件下避免复杂的参数计算过程,还可以改善VSG系统的暂态性能与输出电能质量,优于现有的控制策略。
With the continuous development of new energy power generation and grid-connected technology, virtual synchronous generator(VSG) technology has been widely used to improve the stability of power systems containing new energy. However, the traditional virtual synchronous generator control method still has two shortcomings. Firstly, the VSG system has many operating parameters, and the traditional parameter optimization calculation process is very complicated. Secondly, the parameters of the traditional VSG control system are constant, leading to serious overshoot in the transient adjustment process. In order to solve the above problems, it took reducing the output error and total harmonic distortion of the system as the optimization goal. The improved particle swarm algorithm was first used to optimize the parameters of the VSG, and then according to the transient power angle characteristics of the VSG system, the rotation was adjusted flexibly. The inertia and damping coefficient were used to dynamically change the damping ratio to optimize the dynamic response of the system. Finally, it was compared with the existing control strategy. The result proves that this strategy can not only avoid the calculation process of complex parameters under the condition of multi-objective optimization, but also improve the transient performance and output power quality of the VSG system, which is better than the existing control strategy.
作者
郭建祎
樊友平
GUO Jian-yi;FAN You-ping(School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China)
出处
《电机与控制学报》
EI
CSCD
北大核心
2022年第6期72-82,共11页
Electric Machines and Control
基金
国家重点研发计划项目(2016YFB0900903)。
关键词
虚拟同步发电机
粒子群算法
转动惯量
阻尼系数
多目标优化
总谐波失真度
virtual synchronous generator
particle swarm optimization
rotational inertia
damping
multi-objective optimization
total harmonic distortion
