基于风电功率预测的复合储能超前优化控制策略

超短期风电功率预测的可靠性及精度均逐步提升,文中将其引入风电场复合储能系统(HESS)控制过程,并利用预测功率信息提出了HESS超前优化控制策略。通过相邻充放电区间时长的概率分布统计,确定预测信息的时长区间,并将其作为优化控制策略中的超前控制时间区间;通过分析影响HESS运行效率的主要约束,构建了高效的HESS充放电控制策略;以荷电状态偏移方差最小为目标函数,构建HESS各存储介质同步启动情况下的优化控制模型,并考虑充放电功率和容量限值约束,获取未来时间区间HESS介质的充放电功率控制模式;最后,给出了求解算法和实现步骤。以实际风电场运行数据进行算例分析,计算结果表明本文所提方法可有效实现HESS的高效控制,具有一定实际应用价值。

An Optimal Look-ahead Control Strategy for Hybrid Energy Storage System Based on Wind Power Prediction

With continuously increased accuracy and reliability, wind power prediction is introduced into the control process of hybrid energy storage system (HESS), and an optimal look-ahead control strategy for HESS is proposed. Firstly, the section length of predicted information is confirmed according to the probability distribution of contiguous charge and discharge time section length, and then the look-ahead time section is determined. Secondly, considering the dominant factors that influence the HESS efficiency, an efficient charge and discharge strategy for HESS is developed. Based on this, an optimization model under the synchronous starting of storage media of HESS is constructed, taking minimum-variance of state of charge (SOC) offset as objective function and considers the constraint conditions on charge/discharge power and HESS capacity, then the coordinated control model for next look-ahead time section is determined. Finally, the steps of algorithm solution are given. The analysis of actual wind farm power data shows that the method proposed is efficient in the HESS control with practical application value. This work is supported by National Natural Science Foundation of China (No. 51307101, No. 51177091), Science and Technology Foundation for Middle-aged and Young Scientist of Shandong Province, China (No. BS2013NJ011), and Qinghai Province Key Laboratory of Photovoltaic Grid Connected Power Generation Technology (No. 2014-Z-Y34A).