Multiobjective optimization of underground power cable systems

Abstract

Abstract This paper presents a modified Jaya algorithm (MJaya) for optimizing the material costs and electric-thermal performance of an Underground Power Cable System (UPCS). Three power cables arranged in flat formation are considered. Three XLPE high voltage cables are situated in the thermal backfill layer for ensuring the optimal thermal performance of the cable system. The cable backfill dimensions, cable backfill material, and cable conductor area are selected as design variables in the optimization problem. In the study, the Finite Element Method model is validated experimentally. The Particle Swarm Optimization (PSO), Jaya, and MJaya algorithms are used for multiobjective optimization in order to design a cable system in such a way to minimize the cable backfill costs and maximize the allowable electric current flowing through the cables. For the case study, calculations performed using the Jaya algorithm indicated 1.7\xa0mln Euro cable system costs while cable ampacity is equal to I\xa0=\xa01460 A. The calculations are performed for the objective function values equal to w1\xa0=\xa00.5 and w2\xa0=\xa00.5. Such an optimization parameters set\xa0allow obtaining low costs of UPCS alongside with reasonable cable line ampacity. What is more, the results of the optimization obtained by Jaya, MJaya, and PSO algorithms are compared. Therefore, Coverage and Hypervolume metrics are incorporated. It is concluded that both the Jaya and MJaya algorithms performed better when compared to the PSO algorithm.