The invention discloses a
new energy electric vehicle ordered charging method considering
multiple factors, which realizes ordered charging through a closed-loop framework of data driving, multi-objective optimization, intelligent scheduling and dynamic feedback based on multi-dimensional data such as user demand,
power grid stability, economical efficiency and
renewable energy utilization, and can improve the charging efficiency on the basis of meeting the charging demand of a user. Peak clipping and valley filling of
power grid loads, efficient utilization of
renewable energy sources and user charging
cost optimization are achieved,
power grid load fluctuation is reduced, the
electric energy quality is improved, the
renewable energy sources are utilized to the maximum extent, it is ensured that the requirements of
new energy electric vehicle users are met, and meanwhile the economical efficiency and stability of a power grid are achieved. Meanwhile, through an intelligent
scheduling system and load prediction, charging tasks are uniformly distributed to night valley periods, so that a power grid load curve is more stable, and the utilization efficiency of power
grid resources is optimized; and meanwhile, through an intelligent
algorithm and a
big data technology, the charging demand prediction accuracy is improved, and charging scheduling is more intelligent and accurate.