Affiliations: LIIAN Laboratory, Faculty of Sciences Dhar Mehraz, Sidi Mohammed ben Abdellah University, Fez, Morocco
Correspondence:
[*]
Corresponding author: Maria Serraji, LIIAN Laboratory, Faculty of Sciences Dhar Mehraz, Sidi Mohammed ben Abdellah University, Fez 30000, Morocco. E-mail:maria.serraji@usmba.ac.ma
Abstract: Micro grids (MG) are seen as the future power system
providing clear economic and environmental benefits. Most MG energy
management solutions rely on centralized controller which is not suitable to
guarantee the flexibility and the adaptability that modern electricity
market needs. In other hand, multi objective optimization for fully
decentralized system in MG environment is not realizable without certain
level of coordination between agents. In this paper, we present an adaptive
multi-agents system (AMAS) for MG power management based on enhanced fuzzy
decision using multi swarm optimization (MS-PSO) algorithm. In the proposed
architecture each agent presents a different MG unit. Fuzzy logic is used by
each agent to estimate the amount of energy to be generated in order to
cover the uncertainty and imprecision related to renewable energy sources
and the MG constraints. For the MAS coordination, a MS-PSO algorithm is used
by a coordinator agent to find the best compromised solution to satisfy
economical/environmental objective based on agent proposals in order to
improve them. Simulation results show the importance of the chosen
optimization algorithm for the AMAS with MS-PSO algorithm which is compared
to the basic particle swarm optimization for the same encapsulated
knowledge.
Keywords: Multi-agent systems, multi swarm optimization, fuzzy logic inference, micro grid, energy management
