Open AccessFully distributed economic dispatch of distributed generators in active distribution networks considering losses
Author(s) -
KouveliotisLysikatos Iasonas,
Hatziargyriou Nikos
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.2016.0616
Subject(s) - distributed generation , economic dispatch , convergence (economics) , computer science , mathematical optimization , grid , distributed algorithm , distributed computing , computation , distributed power , distribution (mathematics) , distributed element model , smart grid , power (physics) , electric power system , algorithm , engineering , mathematics , mathematical analysis , physics , quantum mechanics , geometry , economics , economic growth , electrical engineering
The increased complexity of the modern distribution system caused by the installation of a large number of distributed energy resources, dictates the necessity for novel, decentralised schemes for the grid operation. In this study, a fully distributed method for the economic dispatch (ED) problem is proposed that takes into account distribution losses. The solution is reached using only local computations and exchange of messages between adjacent nodes without the need of a central coordinating entity. The algorithm presents plug‐and‐play capabilities and is self‐triggered. More specifically, the ED is formulated as a resource allocation problem and a fully distributed algorithm is employed to acquire the solution that is based on the replicator equation model. It takes into account the technical constraints of the generators and it is extended in order to integrate the distributed calculation of active power losses using distributed estimation of the loss penalty factors. Guarantees for the convergence and optimality of the proposed algorithm are provided along with numerical results that demonstrate the effectiveness and efficiency of the algorithm.