基于传输线模型的解析计算是研究海缆环流的经典方法，但是这种方法认为海缆铠装层是均匀的整层结构，而实际铠装由金属丝（钢丝）绞合而成，这将导致误差，降低海缆环流分析精度。为此提出一种基于改进的鲸鱼优化算法（ improved whale optimisation algorithm，IWOA）的金属丝铠装海缆传输线模型优化方法。首先搭建基于海缆简化替代模型的测试平台，基于实测数据验证了二维有限元仿真模型计算金属丝铠装结构海缆环流的有效性，进而采用IWOA算法进行有限元-MATLAB联合分析，获得铠装整层等效后的电阻率和磁导率，基于该等效结果建立反映金属丝铠装结构的海缆传输线解析模型。以220 kV海缆为对象进行算例分析，参照有限元结果，相对于直接将金属丝铠装简化为整层结构的传统解析计算方式，采用所提方法进行计算所得的感应电压和接地环流精度分别提升了290 %和40%，绝对误差分别小于4.9 %和1.3 %，且计算效率显著高于有限元模型。

Analytical calculation based on transmission line model is a classical method to study the circulation of submarine cables, but this method considers the submarine cable armour layer is a uniform whole layer structure, while the actual armour is made of metal wires (steel wires) stranded together, and it will lead to errors and reduce the accuracy of submarine cable circulation analysis. For this reason, an optimization method for the transmission line model of metal wire armoured submarine cable is proposed based on the improved whale optimization algorithm (IWOA). Firstly, a test platform based on the simplified substitution model of submarine cable is built, and the validity of the 2D finite element simulation model for calculating the circulation flow of submarine cable with metal wire armouring structure is verified based on the measured data, and then the IWOA algorithm is used to carry out the joint analysis of finite element-MATLAB, to obtain the electrical resistivity and magnetic permeability of the whole layer of the armouring after equivalence, and the analytical model of submarine cable transmission line reflecting the structure of the metal wire armouring is established based on the equivalence results. Taking the 220 kV submarine cable as an object for example analysis, referring to the finite element results, compared with the traditional analytical calculation method which directly reduces the wire armouring to the whole layer structure, the accuracy of induced voltage and ground loop current obtained by the method proposed is improved by 290 % and 40 %, respectively, and the absolute error is less than 4.9% and 1.3 %, respectively, and the computational efficiency is significantly higher than that of the finite element model.