Optimized Inductive Filter Device Design for a Novel Transformer Based on Improved Immune Genetic Algorithm

In order to improve the power quality of 220kV transformer substations in power system, the harmonic currents on the 110kV and 35kV sides can flow into the superconducting loop which is composed of the inductive filter winding of four-winding inductive filter transformer and the inductive filter device, and thus the currents on 220kV side are pollute-less. The parameters of inductive filter device in the loop is the key to affect the entire filtering performance. Therefore, an immune genetic algorithm(IGA) of improved operator is applied to optimize the design of inductive filter device in this paper, which uses the total investment cost of the device, the reactive power compensation and the filtering performance as the optimized objectives. Besides the ability of global searching of the genetic algorithm(GA), the IGA involves the mechanisms of immune system such as memory cell and antibody diversity-keeping. By updating the memory cell bank and dynamically adjusting the immune function through the improved operator, the convergent speed of the IGA is accelerated and the global optimal solution is obtained. Simulation results show that the IGA is more effective than the traditional algorithm(TA) for optimizing the design of the inductive filter device.