Parameter Design of Symmetric Dual-Core Phase Shifting Transformer Using Improved Grasshopper Optimization Algorithm

Symmetric dual-core phase shifting transformers (SDCPSTs) provide a reliable and economical solution to control the power flow, which attract wide attention in operation control of power system with high penetration of intermittent renewable energy. This paper presents a high efficiency parameter design method based on intelligent algorithm for SDCPSTs. By introducing the working principle and basic topology of SDCPSTs, an optimization model with multi-objective, including material cost, overall volume, and volume difference, is presented. To solve the optimization problem, an improved grasshopper optimization algorithm (IGOA) integrating local gradient descent method (GD) into standard GOA is proposed. Finally, comparative studies based on a 110MVA/110kV SDCPST were performed, and the results demonstrate the feasibility and effectiveness of the proposed IGOA-based design method.