基于自动微分技术的内点法最优潮流算法

讨论了一种基于自动微分（AD）技术的内点法最优潮流（OPF）算法。与已有的基于AD技术的OPF算法相比，该算法使用高效的基于操作符重载的AD工具，充分利用直角坐标下雅可比矩阵和海森矩阵的大部分元素是常数的特点，加入了识别上述矩阵中不变元素的功能，避免了重复计算。对一组大规模算例的测试分析表明，该算法在保持代码可维护性、灵活性的同时，计算速度接近手动编程，表明AD技术在电力系统OPF中具有取代传统手动编程的潜力。

An Automatic Differentiation Based Interior-point Method for Optimal Power Flow

This paper presents an improved implementation of automatic differentiation(AD) technique in interior-point optimal power flow(OPF).Distinguished from the existing AD-based OPF algorithms,the proposed algorithm applies operator overloading AD technique and explores the characteristics that most elements in Jacobian matrix and Hessian matrix of constraints in rectangular coordinates are constants,and adds a subroutine to identify all constant derivates to avoid repeated computations.Numerical studies on large-scale test cases indicate that the proposed AD implementation can compete with hand codes in execution speed without loss of maintainability and flexibility,which demonstrates that the proposed AD-based OPF algorithm has on-line application potential.