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.
Optimal Power Flow of Integrated Hydrogen-Electricity Energy System Based on Reduced-dimension Projection
Review on Optimization Methods for New Power System Dispatch Based on Deep Reinforcement Learning
Review and Prospect of Inter-Regional and Inter-Provincial Power Trading in China
Assessment on Distributed Generation Accomodation Capability for Distribution Network Based on Uncertain Optimal Power Flow
Related Author
PENG Hongyi
YAN Mingyu
ZHOU Yijia
PENG Hongyi
YAN Mingyu
ZHOU Yijia
FENG Bin
HU Yijie
Related Institution
State Key Laboratory of Advanced Electromagnetic Engineering and Technology (Huazhong University of Science and Technology)
State Key Laboratory of Advanced Electromagnetic Engineering and Technology (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology)
College of Electrical Engineering, Zhejiang University
Zhijiang Laboratory
Department of Electrical Engineering, Tsinghua University