针对柔性高压直流输电系统的交互式教-学优化算法

提出一种针对柔性高压直流输电系统(VSC-HVDC)的交互式教-学优化算法(ITLO)以获取最优PI控制增益.首先在原始教-学优化算法中引入多个班级来扩大搜索范围;然后在不同班级的教师或学生之间建立小世界网络(SWN),通过深度交互学习实现精确搜索.交互式教-学优化算法能够合理权衡搜索范围和搜索精度,从而有效避免算法陷入局部最优.通过3个算例对所提出算法的有效性进行测试,即有功功率和无功功率追踪、电网短路故障和风电并网,仿真结果验证了其相较于现有启发式优化算法的优越性.

Interactive teaching-learning optimization for VSC-HVDC systems

This paper designs an interactive teaching-learning optimization(ITLO) algorithm for voltage source converter based high-voltage direct-current(VSC-HVDC) systems, which is used to optimize the control gains of proportional-integral(PI) control loops. Firetly, a wider exploration is achieved by introducing multiple classes into the teaching-learning based optimization(TLBO) algorithm. Then, a small world network(SWN) is employed for a deep interactive learning among the teachers or students from different classes, so that a more accurate exploitation can be realized. As a result, ITLO is able to effectively avoid a local optimum thanks to its proper trade-off between explorations and exploitations. Three case studies are undertaken, such as active and reactive power tracking, short-circuit fault at power grid, and wind farm integration. Simulation results show that the proposed approach has great advantage compared with typical meta-heuristic optimization algorithms.