Applications of Multi-objective Particle Swarm Optimization Algorithms in Smart Grid: a Comprehensive Survey
Abstract: Multi-objective
optimization problems (MOP) emerging in smart grid, such as optimal operation
of distributed generation (DG) and microgrid, are very complex because of
conflicting objectives, high dimension variables, and numerous operational or
security constraints, and difficult to be solved. Multiobjective particle swarm
optimization (MOPSO) has powerful potential for obtaining Pareto optimal solutions
of these MOPs in a run because it has advantages of parallel computation,
faster convergence, and easier implementation. This paper summarizes general
procedure of MOPSO at first and then well categorizes MOPSO improvements
according to parameter adjusting method, archive update scheme, flying guidance
selection, diversity preservation approach, and hybridization with other
algorithms. Moreover, it also provides a comprehensive survey on MOPSO
applications in smart grid, and gives valuable MOPSO design suggestions to
solve MOP in smart grid. This paper can serve a very useful purpose by
providing a good reference source of MOPSO design to those interested in
Multi-objective optimization issues in smart grid.
Keywords: Multi-objective
optimization, particle swarm optimization, smart grid, distributed generation
Author: Ting Li, Bo Yang, Dong
Liu
Journal Code: jptkomputergg160072
