基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制OA

The sub-synchronous oscillation(SSO)problem in offshore wind farms connected to grids through flexible DC systems occurs frequently.It is urgent to thoroughly understand the mechanism of offshore wind farm,flexible DC system,and SVG on SSO,and to develop effective sub-synchronous oscillation suppression methods.A small-signal model for a direct-drive wind turbine-based offshore wind farm equipped with SVG is constructed.Using the eigenvalue analysis method and the participation factor method,the system oscillation mode is investigated to identify the dominant state variables associated with SSO in offshore wind farms connected to the grid through flexible DC systems.The control parameters involved in the dominant state variables are optimized through the improved artificial bee colony algorithm(ABC)with chaotic mapping,aiming to further suppress the occurrence of SSO.The analysis results indicate that the offshore wind farm,the flexible DC system and the SVG jointly affect the oscillation mode of system SSO.Specifically,the offshore wind farm and the flexible DC system have different impacts on SSO under different oscillation modes,and the impact of the SVG on the SSO remains unaffected by changes in the oscillation mode.Further optimization of the controller parameters through the improvements to the ABC algorithm leads to an enhanced system eigenroot distribution and damping ratio,which effectively enhances the system stability.