| 基于风电概率预测的风电场调频容量估计方法 |
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| 引用本文： | 杨锡运,刘雅欣,邢国通,张悦超. 基于风电概率预测的风电场调频容量估计方法[J]. 太阳能学报, 2022, 43(7): 409-416. DOI: 10.19912/j.0254-0096.tynxb.2020-1085 |
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| 作者姓名： | 杨锡运 刘雅欣 邢国通 张悦超 |
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| 作者单位： | 1.华北电力大学控制与计算机工程学院,北京 102206; 2.中国核电工程有限公司郑州分部,郑州 450052; 3.龙源（北京）风电工程技术有限公司,北京 100084 |
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| 基金项目： | 国家自然科学基金（51677067）； |
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| 摘 要： | 考虑风电的不确定性,提出一种基于风电功率概率预测区间和储能设备的风电场调频容量估计新方法。首先基于风电场弃风数据,利用粒子群算法得到风电场储能系统容量配置;然后建立Copula分位数回归模型求得日前风电功率预测区间;最后结合日前风电限值和不同置信概率下的风功率预测曲线产生最优调频容量估计。风电场实际数据的仿真证实所提方法的有效性,可为风电场调频能力研究提供有益的探索。
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| 关 键 词： | 风电功率 预测 粒子群算法 储能最优配置 风电场调频容量估计 Copula分位数回归 |
| 收稿时间： | 2020-10-15 |
METHOD OF ESTIMATING FREQUENCY REGULATION CAPACITY OF WIND FARM BASED ON WIND POWER PROBABILITY PREDICTION |
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| Yang Xiyun,Liu Yaxin,Xing Guotong,Zhang Yuechao. METHOD OF ESTIMATING FREQUENCY REGULATION CAPACITY OF WIND FARM BASED ON WIND POWER PROBABILITY PREDICTION[J]. Acta Energiae Solaris Sinica, 2022, 43(7): 409-416. DOI: 10.19912/j.0254-0096.tynxb.2020-1085 |
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| Authors: | Yang Xiyun Liu Yaxin Xing Guotong Zhang Yuechao |
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| Affiliation: | 1. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; 2. China Nuclear Power Engineering Co., Ltd. Zhengzhou Branch, Zhengzhou 450052, China; 3. Longyuan（Beijing）Wind Power Engineering Technology Co., Ltd., Beijing 100084, China |
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| Abstract: | Considering the uncertainty of wind power, this paper proposes a new method to estimate the frequency regulation capacity of wind farms based on the probability prediction intervals of wind power and energy storage equipment. Firstly, based on the abandoned data of wind power in the wind farm, the capacity allocation of its energy storage system can be obtained by using particle swarm optimization （PSO）. Then, the Copula quantile regression model is established to get the probability prediction intervals of wind power. Finally, the estimated optimal capacity for frequency regulation is generated by combining the probability prediction curves under different confidence probabilities and the day-ahead limits of wind power. The simulation of the actual data provided by a wind farm proves the effectiveness of this method, which provides a useful exploration for the study of the frequency regulation ability of wind farms. |
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| Keywords: | wind power forecasting particle swarm optimization（PSO） optimal allocation of energy storage estimation of wind farm frequency regulation capacity Copula quantile regression |
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