Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm

To address the problems of slow convergence speed, easy to fall into local minima and low convergence accuracy presented by previous algorithms in DC distribution network fault location, this paper adopts the improved artificial bee colony slime mould algorithm (SMA) to improve and solve. On the basis of SMA, an adaptive adjustable feedback factor and an improved crossover operator are introduced to improve the convergence speed; artificial bee colony (ABC) algorithm is introduced to improve the search ability to jump out of local minima, and the artificial bee colony slime mould algorithm (ISMA) is formed. Firstly, based on the six-terminal DC distribution network topology, a mathematical model of bipolar short-circuit fault as well as single-pole grounded short-circuit fault is established based on a fault occurring between G-VSC and W-VSC as an example. Then the principle of the improved ISMA is introduced in detail, and a suitable fitness function is established as the measure of fault location in DC distribution network. Finally, experimental simulations are conducted to obtain fault points from the optimization search and compare them with the actual values to verify the accuracy of the algorithm. In addition, the efficiency and robustness of ISMA are further verified by comparing with other algorithms.