发电技术 ›› 2024, Vol. 45 ›› Issue (3): 412-422.DOI: 10.12096/j.2096-4528.pgt.23153
周丹1, 袁至1, 李骥2, 范玮3
收稿日期:
2023-11-19
修回日期:
2024-01-19
出版日期:
2024-06-30
发布日期:
2024-07-01
通讯作者:
袁至
作者简介:
基金资助:
Dan ZHOU1, Zhi YUAN1, Ji LI2, Wei FAN3
Received:
2023-11-19
Revised:
2024-01-19
Published:
2024-06-30
Online:
2024-07-01
Contact:
Zhi YUAN
Supported by:
摘要:
目的 现有的混合储能系统控制策略难以在保持荷电状态(state of charge,SOC)处于合理范围的同时,满足未来时刻风电波动造成的混合储能系统超前充放电需求,因此提出一种考虑平抑未来时刻风电功率波动的混合储能系统超前模糊控制策略。 方法 首先,通过采用集合经验模态分解(ensemble empirical mode decomposition,EEMD)方法分解得到不同类型储能设备需要平抑的风电功率;其次,根据混合储能系统SOC和功率饱和程度整定功率修正参数,对混合储能系统输出功率进行修正;再次,由风电预测算法得到前瞻周期内风电功率预测值,根据前瞻周期内风电功率波动情况和超前控制理论整定提前充放电参数,校正储能系统输出功率;最后,以某风电场的实际数据为例,通过仿真验证了所提超前模糊控制策略的有效性。 结果 提出的控制策略不仅能够降低风电并网波动越限概率,显著减少总输出功率与目标功率偏差值,而且能够使混合储能系统的SOC控制在合理范围内。 结论 该策略可以为平抑风电波动的相关研究提供有益参考。
中图分类号:
周丹, 袁至, 李骥, 范玮. 考虑平抑未来时刻风电波动的混合储能系统超前模糊控制策略[J]. 发电技术, 2024, 45(3): 412-422.
Dan ZHOU, Zhi YUAN, Ji LI, Wei FAN. An Advanced Fuzzy Control Strategy for Hybrid Energy Storage Systems Considering Smoothing of Wind Power Fluctuations at Future Moments[J]. Power Generation Technology, 2024, 45(3): 412-422.
NB | NS | ZO | PS | PB | |
---|---|---|---|---|---|
NB | ZE | ZE | ZE | NM | NB |
NS | ZE | ZE | ZE | NS | NM |
ZO | ZE | ZE | ZE | ZE | ZE |
PS | PM | PS | ZE | ZE | ZE |
PB | PB | PM | ZE | ZE | ZE |
表1 整定αx 的模糊逻辑规则
Tab. 1 Fuzzy logic rules for the adjustment of αx
NB | NS | ZO | PS | PB | |
---|---|---|---|---|---|
NB | ZE | ZE | ZE | NM | NB |
NS | ZE | ZE | ZE | NS | NM |
ZO | ZE | ZE | ZE | ZE | ZE |
PS | PM | PS | ZE | ZE | ZE |
PB | PB | PM | ZE | ZE | ZE |
NB | NS | ZO | PS | PB | |
---|---|---|---|---|---|
NB | VB | VB | B | B | B |
NS | B | B | M | M | S |
ZO | S | VS | VS | VS | S |
PS | S | M | M | B | B |
PB | B | B | B | VB | VB |
表2 整定β的模糊逻辑规则
Tab. 2 Fuzzy logic rules for the adjustment of β
NB | NS | ZO | PS | PB | |
---|---|---|---|---|---|
NB | VB | VB | B | B | B |
NS | B | B | M | M | S |
ZO | S | VS | VS | VS | S |
PS | S | M | M | B | B |
PB | B | B | B | VB | VB |
控制策略 | 越限次数 | 越限概率/% |
---|---|---|
EEMD控制 | 487 | 16.23 |
单层模糊控制 | 116 | 3.87 |
双层模糊控制 | 81 | 2.70 |
超前模糊控制 | 62 | 2.07 |
表3 波动越限统计
Tab. 3 Statistics on fluctuation value overruns
控制策略 | 越限次数 | 越限概率/% |
---|---|---|
EEMD控制 | 487 | 16.23 |
单层模糊控制 | 116 | 3.87 |
双层模糊控制 | 81 | 2.70 |
超前模糊控制 | 62 | 2.07 |
1 | 康佳乐,余浩,段瑶,等 .风电场次同步振荡等值建模方法研究[J].发电技术,2022,43(6):880-891. doi:10.12096/j.2096-4528.pgt.21121 |
KANG J L, YU H, DUAN Y,et al .Equivalent modeling method of sub-synchronous oscillation in wind farm[J].Power Generation Technology,2022,43(6):880-891. doi:10.12096/j.2096-4528.pgt.21121 | |
2 | 董文博,顾秀芳,陈艳宁 .风电并网价值分析[J].发电技术,2020,41(3):320-327. doi:10.12096/j.2096-4528.pgt.19117 |
DONG W B, GU X F, CHEN Y N .Value analysis of wind power integration[J].Power Generation Technology,2020,41(3):320-327. doi:10.12096/j.2096-4528.pgt.19117 | |
3 | 薛明军,陈福锋,杨林刚,等 .海上风电交流送出线路继电保护优化设计[J].电力系统保护与控制,2023,51(20):150-159. |
XUE M J, CHEN F F, YANG L G,et al .Optimized design of relay protection for an offshore wind power outgoing transmission line[J].Power System Protection and Control,2023,51(20):150-159. | |
4 | 杨德健,许益恩,郑太英,等 .基于可变增益的双馈风电机组频率波动平抑方法[J].太阳能学报,2023,44(4):173-179. |
YANG D J, XU Y E, ZHENG T Y,et al .Frequency fluctuation mitigation scheme of doubly-fed wind turbine generator based on variable coefficients[J].Acta Energiae Solaris Sinica,2023,44(4):173-179. | |
5 | 陈磊,邓欣怡,陈红坤,等 .电力系统韧性评估与提升研究综述[J].电力系统保护与控制,2022,50(13):11-22. |
CHEN L, DENG X Y, CHEN H K,et al .Review of the assessment and improvement of power system resilience[J].Power System Protection and Control,2022,50(13):11-22. | |
6 | 施进炜,张程,原冬芸 .基于数据修正的概率稀疏自注意短期风电功率预测[J].智慧电力,2023,51(10):54-61. doi:10.3969/j.issn.1673-7598.2023.10.008 |
SHI J W, ZHANG C, YUAN D Y . Short-term wind power prediction based on data correction with probabilistic sparse self-attention[J].Smart Power,2023,51(10):54-61. doi:10.3969/j.issn.1673-7598.2023.10.008 | |
7 | 于欣楠 .考虑风电场功率爬坡的超短期组合预测研究[D].吉林:东北电力大学,2023. |
YU X N .Study on ultra-short-term combined forecasting considering wind farm power ramp events[D].Jilin:Northeast Electric Power University,2023. | |
8 | 王康,张青蕾,王泽,等 .高比例风电系统的爬坡备用需求评估[J].电网与清洁能源,2022,38(8):94-101. doi:10.3969/j.issn.1674-3814.2022.08.012 |
WANG K, ZHANG Q L, WANG Z,et al .Evaluation of ramping reserve requirement for high-proportion wind power systems[J].Power System and Clean Energy,2022,38(8):94-101. doi:10.3969/j.issn.1674-3814.2022.08.012 | |
9 | 马瑞,李浩,吴震宇 .考虑置信水平的混合储能平抑风电波动[J].电力科学与技术学报,2022,37(1):35-40. |
MA R, LI H, WU Z Y,et al .Wind power fluctuations suppression with hybrid energy storage considering the confidence level[J].Journal of Electric Power Science and Technology, 2022,37(1):35-40. | |
10 | 杨京渝,罗隆福,阳同光,等 .计及谷时段风电消纳的储能系统平抑风电功率波动控制策略[J].电力系统保护与控制,2023,51(10):131-141. |
YANG J Y, LUO L F, YANG T G,et al .Smoothing wind power fluctuation control strategy for an energy storage system considering wind power consumption in the valley period[J].Power System Protection and Control,2023,51(10):131-141. | |
11 | 禹海峰,黄婧杰,蒋诗谣,等 .计及储能使用年寿命的风电场整体性储能配置[J].电力科学与技术学报,2022,37(4):152-160. |
YU H F, HUANG J J, JIANG S Y,et al .The overall energy storage configuration of wind farms considering the service life of electric energy storage[J].Journal of Electric Power Science and Technology,2022,37(4):152-160. | |
12 | 马兰,谢丽蓉,叶林,等 .基于混合储能双层规划模型的风电波动平抑策略[J].电网技术,2022,46(3): 1016-1029. |
MA L, XIE L R, YE L,et al .Wind power fluctuation suppression strategy based on hybrid energy storage bi-level programming model[J].Power System Technology,2022,46(3):1016-1029. | |
13 | 陈洪磊,孙泽贤 .模糊控制下混合储能平抑风电波动控制策略[J].低温与超导,2023,51(7):82-89. |
CHEN H L, SUN Z F .Hybrid energy-storage control strategy based on fuzzy control to stabilize wind power fluctuation[J].Cryogenics & Superconductivity,2023,51(7):82-89. | |
14 | 徐玉韬,谈竹奎,肖永,等 .基于HHT与滤波算法的风电波动平抑策略研究[J].电气传动,2019,49(2):56-60. |
XU Y T, TAN Z K, XIAO Y,et al .Research on wind power fluctuation mitigation based on HHT and filtering algorithm[J].Electric Drive,2019,49(2):56-60. | |
15 | 郭玲娟,魏斌,韩肖清,等 .基于集合经验模态分解的交直流混合微电网混合储能容量优化配置[J].高电压技术,2020,46(2):527-537. |
GUO L J, WEI B, HAN X Q,et al .Capacity optimal configuration of hybrid energy storage in hybrid AC/DC micro-grid based on ensemble empirical mode decomposition[J].High Voltage Engineering,2020,46(2):527-537. | |
16 | 李洋,陈洁,王小军,等 .微电网中混合储能双层模糊控制优化策略[J].计算机仿真,2022,39(6):103-107. doi:10.3969/j.issn.1006-9348.2022.06.020 |
LI Y, CHEN J, WANG X J,et al .Double layer fuzzy control optimization strategy for hybrid energy storage in microgrid[J].Computer Simulation,2022,39(6):103-107. doi:10.3969/j.issn.1006-9348.2022.06.020 | |
17 | 赵爱云 .储能电池平抑风电功率波动控制策略及容量优化[D].青岛:青岛大学,2020. |
ZHAO A Y .Control strategy and capacity optimization of energy storage battery for smoothing wind power fluctuation[D].Qingdao:Qingdao University,2020. | |
18 | 刘颖明,王维,王晓东,等 .结合风功率预测及储能能量状态的模糊控制策略平滑风电出力[J].电网技术,2019,43(7):2535-2543. |
LIU Y M, WANG W, WANG X D,et al .A fuzzy control strategy combined with wind power prediction and energy storage SOE for smoothing wind power output[J].Power System Technology,2019,43(7):2535-2543. | |
19 | 刘颖明,王晓东,彭朝阳 .计及储能出力水平的平滑风电功率模型预测控制策略[J].电网技术,2020,44(5):1723-1731. |
LIU Y M, WANG X D, PENG Z Y,et al .Model predictive control strategy for smoothing wind power with energy storage output level[J].Power System Technology,2020,44(5):1723-1731. | |
20 | 李征,房宏才,柯熙政,等 .滑动平均法在MEMS陀螺信号趋势项提取中的应用[J].电子测量与仪器学报,2019,33(7):43-49. |
LI Z, FANG H C, KE X Z,et al .Application of sliding average method to MEMS gyroscope signal trend extraction[J].Journal of Electronic Measurement and Instrumentation,2019,33(7):43-49. | |
21 | 张东英,代悦,张旭,等 .风电爬坡事件研究综述及展望[J].电网技术,2018,42(6):1783-1792. |
ZHANG D Y, DAI Y, ZHANG X,et al .Review and prospect of research on wind power ramp events[J].Power System Technology,2018,42(6):1783-1792. | |
22 | 王永生,关世杰,刘利民,等 .基于XGBoost扩展金融因子的风电功率预测方法[J].浙江大学学报(工学版),2023,57(5):1038-1049. |
WANG Y S, GUAN S J, LIU L M,et al .Wind power prediction method based on XGBoost extended financial factor[J].Journal of Zhejiang University(Engineering Science),2023,57(5):1038-1049. | |
23 | 陈峰,余轶,徐敬友,等 .基于Bayes-LSTM网络的风电出力预测方法[J].电力系统保护与控制,2023,51(6):170-178. |
CHEN F, YU Y, XU J Y,et al .Prediction method of wind power output based on a Bayes-LSTM network[J].Power System Protection and Control,2023,51(6):170-178. | |
24 | 刘芳,汪震,刘睿迪, 等 .基于组合损失函数的BP神经网络风力发电短期预测方法[J].浙江大学学报(工学版),2021,55(3):594-600. |
LIU F, WANG Z, LIU R D,et al .Short-term forecasting method of wind power generation based on BP neural network with combined loss function[J].Journal of Zhejiang University(Engineering Science),2021,55(3):594-600. |
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