Open AccessRegularised primal–dual interior‐point method for dynamic optimal power flow with block‐angular structures
Author(s) -
Zhang Chen,
Jian Jinbao,
Yang Linfeng
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2019.1528
Subject(s) - interior point method , computer science , robustness (evolution) , decoupling (probability) , block (permutation group theory) , distributed algorithm , electric power system , mathematical optimization , topology (electrical circuits) , distributed computing , power (physics) , mathematics , algorithm , engineering , geometry , physics , quantum mechanics , combinatorics , biochemistry , chemistry , control engineering , gene
To implement privacy protection and high‐efficiency distributed computing of the large‐scale dynamic optimal power flow (DOPF) of the multi‐area interconnected power system, the regularised term (RT) and primal–dual interior‐point method (PDIPM), denoted by R‐PDIPM, is proposed to distribute and parallel such DOPF solutions. First, the DOPF is transformed into a prime block‐angular problem through the replication of the coupling node variables, and the multi‐area decoupling of the power grid is realised. However, it is easier to develop a singular (ill‐conditioned) block matrix of Newton's system under the distributed computing of PDIPM. Second, though introducing the RT into the Lagrangian function of PDIPM based on regular technology, the matrix of Newton's system becomes quasi‐definite and strongly factorisable. The robustness of distributed computing of PDIPM is enhanced, and the convergence speed is also improved. Case studies on the 3012 and 3074 node systems over 2–4 time intervals are presented. The results show that the R‐PDIPM is more robust in efficiently solving the problem than PDIPM in distributed computing, which is suited for distributed calculation of DOPF in a large‐scale multi‐area power system.