Open AccessOptimisation configuration of hybrid AC/DC microgrid containing electric vehicles based on the NSGA‐II algorithm
Author(s) -
Ye Bin,
Shi Xuemei,
Wang Xuli,
Wu Hongbin
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.5043
Subject(s) - microgrid , sorting , genetic algorithm , computer science , function (biology) , electric vehicle , control theory (sociology) , mathematical optimization , algorithm , control (management) , power (physics) , mathematics , machine learning , artificial intelligence , evolutionary biology , biology , physics , quantum mechanics
Based on the development of hybrid AC/DC microgrid, considering the objectives of microgrid life‐cycle cost, self‐balancing rate and converter losses, an optimisation configuration model of a hybrid AC/DC microgrid is established here. Based on the different model of EVs to connect with grid, the matching control strategies for the model are proposed. The elitist non‐dominated sorting genetic algorithm (NSGA‐II) is applied to solve the optimisation configuration model. With the example system simulation, the demand response function of EVs is analysed, and the impacts of different EVs charging modes on optimisation configuration results of the hybrid AC/DC microgrid are studied and discussed. The rationality and effectiveness of proposed models and strategies are verified.