Open AccessMulti-objective optimization configuration of wind-solar-storage microgrid based on NSGA-III
Author(s) -
Jinghao Yu,
Changhai Sun,
Ruixi Kong,
Zhe Zhao
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 - 10.1088/1742-6596/2005/1/012149
Subject(s) - microgrid , mathematical optimization , photovoltaic system , genetic algorithm , pareto principle , grid , computer science , multi objective optimization , reliability (semiconductor) , population , particle swarm optimization , wind power , power (physics) , reliability engineering , engineering , mathematics , physics , geometry , electrical engineering , demography , quantum mechanics , sociology
Reasonable allocation of the capacity of micro power supply such as wind turbine, photovoltaic and battery is the premise to ensure the economic, reliable and environmental protection operation of microgrid. Aiming at the capacity allocation problem of grid connected microgrid, this paper establishes a multi-objective optimal allocation mathematical model of grid connected microgrid considering the economy, reliability and environmental protection of microgrid, and uses the genetic algorithm NSGA-III based on the reference point selection mechanism to obtain the multi-objective Pareto solution set of micro source capacity allocation. The simulation results show that NSGA-III can not only optimize the three objective functions better than NSGA-II, but also improve the distribution uniformity of Pareto solution set and the diversity of population. The simulation results show that NSGA-III algorithm is more suitable for multi-objective optimal configuration of microgrid.