Open AccessMultitime scale coordinated scheduling for electric vehicles considering photovoltaic/wind/battery generation in microgrid
Author(s) -
Ren Lina,
Song Zeyu,
Mao Chenhong,
Liu Fucai
Publication year - 2019
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.2821
Subject(s) - microgrid , scheduling (production processes) , particle swarm optimization , photovoltaic system , mathematical optimization , optimization problem , computer science , wind power , engineering , automotive engineering , renewable energy , electrical engineering , mathematics
Summary The problem of multitime scale coordinated scheduling for electric vehicles (EVs) with vehicle‐to‐grid (V2G) technology is formulated for a microgrid with photovoltaic/wind/battery generation. The life of the energy storage system in the microgrid, and the benefits for EV users are considered as the optimization goals. Reasonable measures of the charging and discharging behaviors of EVs are considered to construct the objective functions. A stratified sequencing method is designed to transform the multiobjective optimization problem into a single‐objective nonlinear optimization problem that can be solved through adaptive particle swarm optimization (APSO). Then an optimal multitime scale coordinated scheduling scheme can be obtained. The effectiveness and feasibility of the methods are verified by simulation results.