基于超短期风电功率预测的混合储能控制策略研究
为了改善风机出力特性,提出了一种基于超短期风电功率预测的混合储能控制策略。首先,利用解析模态分解方法从风电信号中提取低频信号,采用了一种改进布谷鸟方法优化支持向量机的惩罚因子参数和核函数参数进行超短期功率预测;然后,对低频预测信号建立1 min时间尺度和30 min时间尺度的功率波动并网指标,判断是否触发蓄电池动作,若动作,采用AMD分解自适应调整低频预测信号的截止频率,直到满足并网要求,确定蓄电池补偿功率指令。最后根据蓄电池荷电状态和补偿功率指令自适应调节原始风电信号截止频率,高频信号通过模糊控制由超级电容器补偿。仿真算例表明,该方法可以有效平滑功率波动,减少蓄电池的循环次数,同时保证了蓄电...
Saved in:
Published in | 电测与仪表 Vol. 54; no. 15; pp. 50 - 57 |
---|---|
Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
华北电力大学 河北省输变电设备安全防御重点实验室,河北 保定,071003
2017
|
Subjects | |
Online Access | Get full text |
ISSN | 1001-1390 |
Cover
Loading…
Summary: | 为了改善风机出力特性,提出了一种基于超短期风电功率预测的混合储能控制策略。首先,利用解析模态分解方法从风电信号中提取低频信号,采用了一种改进布谷鸟方法优化支持向量机的惩罚因子参数和核函数参数进行超短期功率预测;然后,对低频预测信号建立1 min时间尺度和30 min时间尺度的功率波动并网指标,判断是否触发蓄电池动作,若动作,采用AMD分解自适应调整低频预测信号的截止频率,直到满足并网要求,确定蓄电池补偿功率指令。最后根据蓄电池荷电状态和补偿功率指令自适应调节原始风电信号截止频率,高频信号通过模糊控制由超级电容器补偿。仿真算例表明,该方法可以有效平滑功率波动,减少蓄电池的循环次数,同时保证了蓄电池储能的平滑能力,避免过充过放,延长蓄电池的寿命。 |
---|---|
Bibliography: | Li Yanqing, Yuan Yanwu, Guo Tong, Wang Zirui, Tong Nian, Shi Yiming (Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding 071003, Hebei, China) 23-1202/TH hybrid energy storage, AMD, ICSA, ultra-short-term wind power prediction, power fluctuation, adjusted self-adaptively An operation control strategy based on ultra-short-term wind power prediction for hybrid energy storage is proposed in order to improve the output characteristics of wind farm. Firstly, the low frequency signals are extracted from the wind signals by analytical mode decomposition (AMD) method, and the penalty parameter and kernel func- tion parameter of support vector machines (SVM) are found by using improved cuckoo search algorithms (ICSA) to predict the future wind power. Then, the power fluctuation index of the 1 rain time scale and the 30 rain time scale of low frequency predicted signal is established to judge whether the battery is triggered. If triggered, the cu |
ISSN: | 1001-1390 |