Open AccessFully distributed multi‐area dynamic economic dispatch method with second‐order convergence for active distribution networks
Author(s) -
Xu Tong,
Wu Wenchuan,
Sun Hongbin,
Wang Liming
Publication year - 2017
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.2016.1945
Subject(s) - convergence (economics) , computer science , economic dispatch , mathematical optimization , order (exchange) , distributed algorithm , dual (grammatical number) , rate of convergence , point (geometry) , basis (linear algebra) , distribution (mathematics) , distributed computing , mathematics , computer network , electric power system , mathematical analysis , power (physics) , physics , finance , quantum mechanics , economics , economic growth , art , channel (broadcasting) , geometry , literature
In active distribution networks, distributed generators are integrated into microgrids or geographically distributed subsystems. They may belong to different owners and are operated independently to preserve privacy. Therefore, fully distributed economic dispatch (ED) methods are needed and most existing algorithms show first‐order convergence. This study introduces a fully distributed dynamic ED with second‐order convergence, which is based on a parallel primal–dual interior‐point algorithm with a matrix‐splitting technique. In this method, each area optimises its own problem with limited information exchanged with its neighbours, and no central coordinator is needed. Numerical tests demonstrate that the algorithm can converge at a second‐order rate. On the basis of a peer‐to‐peer communication paradigm, this method can achieve a global optimum while the privacy of each area is obliquely protected.