基于最优带宽的广东海上风电出力非参密度估计与分析

饶志, 王科, 谭俊丰, 黎嘉明, 杨再敏, 蒙文川

太阳能学报 ›› 2023, Vol. 44 ›› Issue (12) : 274-282.

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太阳能学报 ›› 2023, Vol. 44 ›› Issue (12) : 274-282. DOI: 10.19912/j.0254-0096.tynxb.2022-1325

基于最优带宽的广东海上风电出力非参密度估计与分析

  • 饶志1,2, 王科3, 谭俊丰2, 黎嘉明3, 杨再敏1, 蒙文川1
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NON-PARAMETRIC KERNEL DENSITY ESTIMATION AND ANALYSIS OF GUANGDONG OFFSHORE WIND POWER OUTPUT BASED ON OPTIMAL BANDWIDTH

  • Rao Zhi1,2, Wang Ke3, Tan Junfeng2, Li Jiaming3, Yang Zaimin1, Meng Wenchuan1
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摘要

为支撑广东省海上风电规划与电网安全调度,提出一种基于最优带宽参数下的海上风电非参数核密度估计模型,该模型无需依靠先验性的参数结果,可适配出力分布呈多峰性的海上风电。算例分析验证了所提模型的拟合效果可兼具曲线平滑与反映尖峰特征的特点,降低拟合估计的误差,并通过分析多时空尺度下的海上风电非参数核密度估计模型,形成对应地区的发展建议。所得结果可为广东省海上风电规划、电网安全调度提供风电运行的参考借鉴价值。

Abstract

To support offshore wind power planning and grid security scheduling, a non-parametric kernel density estimation model based on the optimal bandwidth parameter is proposed, which does not need to rely on a priori parameter results and can be adapted to offshore wind power with multi-modal output distribution. The case study verifies that the fitting effect of the proposed model can have the characteristics of smooth curve and reflect the characteristics of spikes, reducing the error of fitting estimation. And by analyzing the non-parametric kernel density estimation model of offshore wind power, development suggestions are formed, which can provide reference value for offshore wind power planning and power grid security dispatch in Guangdong Province.

关键词

海上风电 / 非参数核密度估计 / 最优带宽 / 多时空尺度

Key words

offshore wind power / non-parametric kernel density estimation / optimal bandwidth / multiple spatiotemporal scales

引用本文

导出引用
饶志, 王科, 谭俊丰, 黎嘉明, 杨再敏, 蒙文川. 基于最优带宽的广东海上风电出力非参密度估计与分析[J]. 太阳能学报. 2023, 44(12): 274-282 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1325
Rao Zhi, Wang Ke, Tan Junfeng, Li Jiaming, Yang Zaimin, Meng Wenchuan. NON-PARAMETRIC KERNEL DENSITY ESTIMATION AND ANALYSIS OF GUANGDONG OFFSHORE WIND POWER OUTPUT BASED ON OPTIMAL BANDWIDTH[J]. Acta Energiae Solaris Sinica. 2023, 44(12): 274-282 https://doi.org/10.19912/j.0254-0096.tynxb.2022-1325
中图分类号: TM614   

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基金

国家自然科学基金(71701087); 南方电网公司总部科技项目(ZBKJXM20220004)

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