Open AccessOptimal Control of Ship Microgrid Based on Improved Genetic Algorithms
Author(s) -
Xiaodi Zhang,
Ruicheng Dai,
Jianrui Song,
Liu Ji-yun,
Bin Ren
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/529/1/012001
Subject(s) - microgrid , photovoltaic system , wind power , automotive engineering , matlab , genetic algorithm , stand alone power system , computer science , power (physics) , engineering , renewable energy , control engineering , distributed generation , electrical engineering , physics , quantum mechanics , machine learning , operating system
Wind energy and solar energy are natural clean energy. If wind power is used to generate electricity, rational allocation of wind turbines, photovoltaic cells, storage batteries, and diesel engines to supply the ship’s electricity will be of great significance for energy conservation and emission reduction. This article proposes a specific research object, that is, research on the optimal configuration of the hybrid power generation system for small-scale barges berthed at the port, the establishment of a hybrid power system mathematical model of wind turbines, photovoltaic cells, batteries and diesel engines, and the use of improved genetic algorithms to the total cost of the system is the minimum. The power supply reliability of the system is the constraint condition to solve the mathematical model of the optimized configuration. Finally, the simulation results are analyzed in MATLAB.