摘要
根据风电预测精度随时间尺度的减小逐级提高的固有特性,建立了多时间尺度多目标协调调度的滚动优化模型。依据风电并网标准与分布式电池储能系统(distributed battery energy storage system,DBESS)能快速修正风电波动的低频分量,以系统经济性最优和弃风电量最小为目标函数建立优化模型,采用加入4个风电场(wind farm,WF)和2个电池储能系统(battery energy storage systems,BESSs)的IEEE-39节点标准系统进行算例分析,遗传算法(genetic algorithm,GA)对目标函数进行迭代求解。结果证明,本研究提出的基于DBESS的风储有功滚动优化调度模型,可以有效降低系统运行经济性以及提高电网对风电的接纳能力。
According to the inherent characteristics of wind power that forecased accuracy increasing with the time-scale decreasing,a multi-time scale and multi-objective coordinated rolling optimal dispatch model was established. Based on the wind power grid-connected standards and combined with distributed battery energy storage system（DBESS）,the low-frequency fluctuation of wind power could be damped in time. An optimized model was established with objectives of minimizing the economy of the system and the curtailed wind power. The IEEE 39-bus system with four wind farms and two battery energy storage systems（BESSs） was added for utilizing to verify the optimization dispatch model proposed,and it was solved by genetic algorithm（GA） iteratively. The results showed that the proposed wind-storage rolling optimal dispatch model based on DBESS could reduce the cost of the system operation and increase the amount of wind power griding effectively.
出处
《山东大学学报（工学版）》
CAS
北大核心
2017年第6期89-94,共6页
Journal of Shandong University（Engineering Science）
基金
国网山东省电力公司科技资助项目(52061016007)
关键词
风储联合发电系统
协调调度
滚动优化
风电
多目标优化
遗传算法
wind-storage combined power system
coordinative dispatch
rolling optimal
wind power
multi-objectiveoptimal
genetic algorithm （GA）
