Open AccessOptimal Dispatching of Microgrid Based on Improved Particle Swarm Optimization
Author(s) -
Feihang Zhou,
Siyu Bian,
Dan Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1871/1/012141
Subject(s) - particle swarm optimization , microgrid , inertia , mathematical optimization , computer science , convergence (economics) , multi swarm optimization , scheduling (production processes) , swarm behaviour , mathematics , artificial intelligence , control (management) , physics , classical mechanics , economics , economic growth
In order to enable the microgrid to meet the system load demand while performing economically optimal operation scheduling, this paper establishes an island-type microgrid model, which is optimized by using an improved immune particle swarm algorithm, and the inertia weight and learning the two parameters of the factor are improved. On the basis of the immune particle swarm algorithm, a power exponential function operator is added to the inertia weight to improve the search ability of the algorithm, in order to reduce the computing time, the dynamically adjusted learning factor is introduced to optimize the immune particle swarm algorithm the local search ability is stronger. Two examples are selected to verify the algorithm, the results prove that the method has better global convergence and local search capabilities and the convergence speed has been improved.