RT Journal Article
A1 Zhifang Yang
A1 Haiwang Zhong
A1 Qing Xia
A1 Chongqing Kang

PB iet
T1 Solving OPF using linear approximations: fundamental analysis and numerical demonstration
JN IET Generation, Transmission & Distribution
VO 11
IS 17
SP 4115
OP 4125
AB Due to the unique advantages in computational robustness and convergence, the linear approximation approach is and will remain to be an important method to solve the optimal power flow (OPF) problem, especially for industrial applications. The DC power flow method, which is currently used in the majority of power industries, is the representative. Many studies extend the DC power flow method by including voltage magnitude, reactive power, and losses. This study provides a detailed analysis and breakdown investigation of existing linear approximations of the OPF problem. The formulation and accuracy of existing linear approximations are compared. Taking advantage of the decoupled formulation of linear approximations, the property of power flow equations is illustrated from a new perspective. Why reactive power flow equations are hard to linearise is explained theoretically. The numerical performance of existing linear approximations is demonstrated in IEEE and Polish test systems. Evidence from the theoretical analysis and numerical studies shows that the accuracy of linear approximations could be substantially improved using a mathematical transformation of the non-linear voltage magnitude term. This finding provides a new research direction for solving the OPF problem using linear approximations.
K1 optimal power flow problem
K1 Polish test systems
K1 IEEE test systems
K1 reactive power flow equations
K1 mathematical transformation
K1 nonlinear voltage magnitude term
K1 OPF
K1 linear approximation approach
K1 numerical performance
K1 DC power flow method
K1 power industries
DO https://doi.org/10.1049/iet-gtd.2017.1078
UL https://digital-library.theiet.org/;jsessionid=51upq9m12lbnf.x-iet-live-01content/journals/10.1049/iet-gtd.2017.1078
LA English
SN 1751-8687
YR 2017
OL EN