Computationally Efficient and Accurate Approach for Commutation Failure Risk Areas Identification in Multi-Infeed LCC-HVdc Systems

Earlier approaches for commutation failure (CF) risk areas identification in multi-infeed LCC-HVdc systems include the simulation-based and analytical types. However, the former and latter will cause the low computational efficiency and inaccurate result, respectively. Thus, this article first clarifies CF performances caused by voltage depression and distortion in multi-infeed LCC-HVdc systems. Second, an ac-dc interaction factor (ADIF) index along with its analytical calculation method is proposed to quantify the voltage interaction between arbitrary ac line location and inverter bus. The ADIF is then used to develop a critical ADIF index for identifying the voltage depression induced CF. Third, a distortion ADIF index along with its mathematical expression is developed for identifying the voltage distortion induced CF. Fourth, combining the voltage depression and distortion induced CF identification methods, CF correlation regions where ac faults can induce CF in inverters are introduced to develop the proposed approach. Compared to earlier simulation-based approaches, the proposed approach is more efficient without recourse to simulations. Compared to earlier analytical approaches ignoring ac lines faults and the voltage distortion induced CF, the proposed approach is more accurate with these factors comprehensively considered. Finally, case study on an 8-infeed LCC-HVdc system validates the proposed approach.