DocumentCode :
2670282
Title :
MAS energy management of a microgrid based on fuzzy logic control
Author :
Serraji, Maria ; Boumhidi, Jaouad ; Nfaoui, El Habib
Author_Institution :
Dept. of Comput. Sci., Sidi Mohammed ben Abdellah Univ., Fez, Morocco
fYear :
2015
fDate :
25-26 March 2015
Firstpage :
1
Lastpage :
7
Abstract :
This paper proposes a design and implementation of an autonomous multi agent system (MAS) for optimal micro grid (MG) scheduling energy control based on fuzzy logic decision. The complexity of climate makes renewable energy source included in a micro grid, difficult to be scheduled with traditional energy sources in centralized system. Furthermore the scheduling depend on energy sources constraints and market price changing extend the environment uncertainty and imprecision. The proposed approach is designed in order to satisfy load while trying to optimize the total operating cost. The micro grid considered in this paper consists of a wind turbine (WT), a photovoltaic (PV), a fuel cell (FC), micro turbine (MT) and battery storage. A detailed multi agent system based on fuzzy logic control demonstrates its reliability in meeting all the requirements of the system. The result analysis shows that the proposed method is beneficial to handle the problem of scheduling energy through micro grid better than centralized system.
Keywords :
distributed power generation; energy management systems; fuel cells; fuzzy logic; fuzzy reasoning; multi-agent systems; power engineering computing; power generation reliability; power generation scheduling; secondary cells; solar cells; wind turbines; FC; MAS energy management; MG scheduling energy control; MT; PV cell; WT; battery storage; environment uncertainty; fuel cell; fuzzy logic control; fuzzy logic decision; micro turbine; microgrid; multi agent system; photovoltaic cell; renewable energy source; wind turbine; Batteries; Fuzzy logic; Fuzzy sets; Input variables; Optimization; Renewable energy sources; Mico gird; Mult-agent systems(MAS); energy management; fuzzy logic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems and Computer Vision (ISCV), 2015
Conference_Location :
Fez
Print_ISBN :
978-1-4799-7510-5
Type :
conf
DOI :
10.1109/ISACV.2015.7106187
Filename :
7106187
Link To Document :
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