A new inductive motors load equivalence algorithm based on coherence is proposed in this paper. In order to partite motors load rapidly and accurately, fuzzy c-means clustering along with particle swarm optimization (PSO-FCM) algorithm is proposed to identify coherent motors base on its physical essence of fuzziness. The merits of PSO algorithm are independent to initial value and convergent to optimum value rapidly, and the validity function is constructed to assess clustering validity. The test on IEEE 39-Bus System is presented to evaluate the effectiveness of the new algorithm, the membership matrix definite not only coherence group of motors but also correlation value of coherence between motors. The algorithm can be used to partite motor load based on coherency in dynamic equivalence with power system operating on different modes.

HVDC transmission system has considerable impact on the surrounding power transformers when the system is running in the unipolar ground mode, which will cause the DC magnetic biasing phenomenon on transformers. This problem would be more serious, after commission and operation of UHVDC transmission system in China. According to the Guangdong power grid under the influence of DC magnetic bias seriously, but little research about the using of blocking device, this paper proposed an optimization scheme about the usage of blocking device combination. Firstly, the subject studied the method of suppressing transformer neutral point DC depending on analysis the mechanism of magnetic biasing, and then found out the changes of power grid after using the capacitance blocking device which is popular used by Guangdong power grid. The particle swarm optimization (PSO) has been used to find a better way to suppress the DC in power grid, and combined with NSGA to solve the mixed integer programming problem. The final data validation of this method is valuable in engineering application.