| 风储联合发电系统参与频率响应的模型预测控制策略 |
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| 引用本文： | 虞临波,寇鹏,冯玉涛,冯浩天.风储联合发电系统参与频率响应的模型预测控制策略[J].电力系统自动化,2019,43(12):36-43. |
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| 作者姓名： | 虞临波 寇鹏 冯玉涛 冯浩天 |
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| 作者单位： | 陕西省智能电网重点实验室(西安交通大学),陕西省西安市,710049;陕西省智能电网重点实验室(西安交通大学),陕西省西安市,710049;陕西省智能电网重点实验室(西安交通大学),陕西省西安市,710049;陕西省智能电网重点实验室(西安交通大学),陕西省西安市,710049 |
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| 基金项目： | 国家自然科学基金资助项目(51777162);陕西省自然科学基础研究计划资助项目(2016JQ5080);中央高校基本科研业务费专项资金资助项目(xzy012019022) |
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| 摘 要： | 储能电池的柔性控制作用使其在参与电网调频方面具有优势,将风电和储能相结合,构成风储联合发电系统参与电网调频,具有协同增效的优势。为此,基于模型预测控制方法,提出风储联合调频策略。该策略在考虑风电场和储能各自约束条件的前提下,通过求解滚动时域最优控制问题协调了两者之间的出力分配,并使用滚动时域估计方法来实时估计电网的有功功率不平衡量,从而可根据更准确的系统状态信息来计算最优控制量。最后对提出的策略进行了仿真分析,结果表明该策略能够提高电网的调频性能。
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| 关 键 词： | 风电场 电池储能系统 电网频率 模型预测控制 滚动时域估计 |
| 收稿时间： | 2018/9/23 0:00:00 |
| 修稿时间： | 2019/3/28 0:00:00 |
Model Predictive Control Strategy for Combined Wind-Storage System to Participate in Frequency Response |
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| YU Linbo,KOU Peng,FENG Yutao and FENG Haotian.Model Predictive Control Strategy for Combined Wind-Storage System to Participate in Frequency Response[J].Automation of Electric Power Systems,2019,43(12):36-43. |
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| Authors: | YU Linbo KOU Peng FENG Yutao and FENG Haotian |
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| Affiliation: | Shaanxi Key Laboratory of Smart Grid(Xi''an Jiaotong University), Xi''an 710049, China,Shaanxi Key Laboratory of Smart Grid(Xi''an Jiaotong University), Xi''an 710049, China,Shaanxi Key Laboratory of Smart Grid(Xi''an Jiaotong University), Xi''an 710049, China and Shaanxi Key Laboratory of Smart Grid(Xi''an Jiaotong University), Xi''an 710049, China |
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| Abstract: | The flexible control characteristic of battery energy storage system(BESS)makes it have an advantage in participating in grid frequency regulation. The combination of wind power and energy storage has the effect of synergistic enhancement in providing frequency support. Thus, based on model predictive control(MPC), a coordinated strategy of combined wind-storage system for frequency response is proposed. By solving moving horizon optimization problem, this control strategy can optimally coordinate the output power of wind farm and energy storage while satisfying a set of constraints of the combined system. Moreover, moving horizon estimation(MHE)is used to estimate grid power imbalance in real time, which ensures that the optimization process is based on more accurate system information. Finally, the control strategy is tested through simulations and the results show that the proposed strategy can effectively improve the performance of grid frequency regulation. |
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| Keywords: | wind farm battery energy storage system(BESS) grid frequency model predictive control(MPC) moving horizon estimation(MHE) |
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