Open AccessOptimal performance of a self‐healing microgrid
Author(s) -
Chandak Sheetal,
Rout Pravat Kumar
Publication year - 2020
Publication title -
iet smart grid
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.612
H-Index - 11
ISSN - 2515-2947
DOI - 10.1049/iet-stg.2019.0177
Subject(s) - microgrid , computer science , power flow , power (physics) , electric power system , mathematical optimization , graph , path (computing) , stability (learning theory) , control theory (sociology) , reliability engineering , engineering , mathematics , computer network , control (management) , physics , theoretical computer science , quantum mechanics , artificial intelligence , machine learning
This study proposes a multi‐objective binary differential evolution algorithm to reconfigure the system and restore the loads within the stand‐alone microgrid. The approach aims to attain a restoration path having maximum power flow with the minimum number of interrupted loads and switching operations. To execute the discrete optimisation strategy, the power network has been reframed as a capacitated graph, where the edges are capacitated by the loading capacity of the feeder. The strategy implements the maximum power flow theorem, which has been enhanced using the centrality index. The major operational constraints of the microgrid have been strictly followed to maintain system stability. The proposed restoration algorithm is examined on an islanded 13‐bus microgrid system with the two test scenarios of irregular power generation, and the fault instance is isolating a healthy section of a microgrid. Moreover, the efficacy of the proposed approach has been further examined on a 39‐bus system, and the results are compared with the other optimisation strategies implemented for restoration.