Multi‐objective optimization method for control parameters of flexible direct current transmission converters based on intelligent algorithms

Abstract

AbstractIn order to meet the current needs of power transmission, people have turned their attention to direct current (DC) transmission. When the alternating current(AC) power grid (PG) fails, it is easy to cause commutation failure in the DC system, thereby increasing the fault scope of the system. Therefore, this article adopts a flexible DC transmission system. Flexible DC converters have many control parameters, and there are mutual influences and conflicts between these parameters. By applying intelligent algorithms to multi‐objective optimization (MOP), these complex MOP problems can be effectively solved and an optimal set of control parameter combinations can be found. This method has an important contribution and novelty for optimizing the converter control parameters of flexible DC transmission systems. This article achieves fast and accurate MOP of the control parameters of flexible DC transmission converters by continuously detecting the similarities between antibodies and maintaining the diversity of the population. The research results show that the average DC side current is about 405A in the first 20 seconds, and the DC side current fluctuates regularly after 20 seconds. This article lays the foundation for establishing a real‐time simulation model of flexible DC transmission systems suitable for real‐time simulation systems.