Open AccessDecision‐making method for critical load restoration by using MGs
Author(s) -
Ghasemi Sasan,
Khodabakhshian Amin,
Hooshmand RahmatAllah
Publication year - 2019
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.2019.0254
Subject(s) - unavailability , blackout , computer science , dijkstra's algorithm , reliability engineering , process (computing) , mathematical optimization , path (computing) , analytic hierarchy process , dependability , electric power system , fuzzy logic , cls upper limits , node (physics) , reliability (semiconductor) , shortest path problem , fault (geology) , operations research , power (physics) , engineering , artificial intelligence , mathematics , theoretical computer science , optometry , graph , structural engineering , operating system , quantum mechanics , programming language , medicine , physics , seismology , geology
After occurring extreme events distribution systems might be disconnected from the main grid, and there will be a complete blackout in the distribution network. In such situations, the only way to re‐energise loads is to use available microgrids (MGs). Since power outputs of MGs are limited, the major concern for system operators is to energise the maximum critical loads (CLs) during the time needed for fault isolation and maintenance. To solve this problem, this study provides a systematic restoration process by using MGs. First, after the fault clearance the shortest paths between MGs and CLs are identified by Dijkstra ’ s algorithm. Then, the best paths are determined by using a new modified analytic hierarchical process (AHP) algorithm and fuzzy logic to achieve four goals: increasing restored energy, reducing path preparing time, decreasing number of switching operations and reducing unavailability of path. In the modified AHP, the parameters are so tuned that the engineers’ personal preferences are eliminated for selecting the best restoration paths. Also, the uncertainty of available energy of MGs is considered. The IEEE 123‐node distribution network with MGs and CLs is used for simulations. Results clearly show the benefits of using this method for CL restoration.