Open AccessHybrid computation of corrective security‐constrained optimal power flow problems
Author(s) -
Zhang Rui,
Dong Zhao Yang,
Xu Yan,
Wong Kit Po,
Lai Mingyong
Publication year - 2014
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.2013.0384
Subject(s) - mathematical optimization , power flow , computer science , robustness (evolution) , computation , electric power system , convergence (economics) , contingency , economic dispatch , state (computer science) , power (physics) , mathematics , algorithm , biochemistry , chemistry , quantum mechanics , physics , linguistics , philosophy , economics , gene , economic growth
Corrective security‐constrained optimal power flow (CSCOPF) considers the use of corrective control to remove system security violations in the post‐contingency state. Its optimality not only depends on the pre‐contingency state, but also the post‐contingency state as well as the involved corrective control actions. This study first gives a comprehensive review on the relevant OPF models and then proposes a hybrid method to solve the CSCOPF problem. It makes use of the evolutionary algorithms to randomly search the maximum feasible region and state‐of‐the‐art OPF solution technique (interior‐point method) to provide deterministic solutions in the found region. The two interact iteratively to progressively approach the final solution. The proposed method is verified on the IEEE 14‐bus and 118‐bus systems. Comparison studies show that (i) CSCOPF can better balance the security and economy and (ii) the hybrid method is overall superior (in solution quality, robustness and convergence characteristic) over the single evolutionary algorithm. Parallel processing is applied to speed‐up the computations.