Open AccessRobust switching control for service restoration in smart grids considering switching malfunction by MAS
Author(s) -
Shirazi Elham,
Jadid Shahram
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.2018.6774
Subject(s) - circuit breaker , plan (archaeology) , service (business) , fault (geology) , multi agent system , computer science , sequence (biology) , distributed computing , reliability engineering , control (management) , engineering , artificial intelligence , genetics , economy , archaeology , seismology , geology , biology , electrical engineering , economics , history
This study proposes an agent‐based approach to have a reliable service restoration scheme, which is vital to restore as many loads as possible after a permanent fault. The proposed multi‐agent system (MAS) has four different types of agents: feeder agents, zone agents, switch agents and DG agents. The agents can communicate and cooperate with each other in order to supply services to out‐of‐service customers. An artificial neural network has been considered to handle DG uncertainties. The restoration plan is built in a distributed manner, based on local data considering system conditions, operational constraints and fault location. The result of the proposed MAS is a switching sequence. After defining this sequence, the command for opening will be received by circuit breaker agents. In case of one switch failure, the plan cannot be implemented, and hence the restoration plan will fail. To have a reliable restoration plan, the main feeder agent has to handle malfunction in order to operate the system at an acceptable range without violating system constraints. Different loading conditions have been considered under different scenarios and the results of the proposed approach for each scenario have been compared. Simulation results show the efficiency of the proposed agent architecture.