基于网格化数值天气预报的区域光伏发电多输出功率预测方法

doi:10.11930/j.issn.1004-9649.202305029

摘要/Abstract

摘要：

区域光伏的短期功率预测是省级及以上电网调控中心制定发电计划、提高光伏消纳率的重要基础之一。光伏短期功率预测本质上是构建数值天气预报与实际功率之间的映射模型，为了实现预测精度的提升，利用网格化的数值天气预报，采用残差网络建立区域光伏的多输出预测模型，充分挖掘区域光伏所属空间的气象资源分布与各光伏电站功率的关联关系，实现以网格化数值天气预报为输入的区域各光伏电站的功率预测。以实际运行数据进行仿真，结果表明，本文方法在各光伏电站的功率和总功率2个方面的预测结果均优于现有成熟方法。

关键词: 光伏功率预测, 网格化数值天气预报, 残差网络, 多输出模型

Abstract:

The short-term power prediction of regional photovoltaic (PV) is one of the important bases for the provincial and above power grid control center to make power generation plans and improve the photovoltaic consumption. In essence, short-term photovoltaic power prediction is to build a mapping model between numerical weather prediction and actual power. In order to improve the prediction accuracy, the grid-based numerical weather prediction and residual network were used in this paper to establish a multi-output prediction model of regional photovoltaic, and fully explore the correlation between the distribution of meteorological resources and the power of each photovoltaic power station in the regional photovoltaic space, thus identifying the grid-based numerical weather prediction as input and the power of each photovoltaic power station in the region as output. The simulation was carried out by use of actual operation data. The results showed that the proposed method was superior to the existing proven methods in predicting the power and total power of each photovoltaic power station.

Key words: photovoltaic power prediction, gird numerical weather prediction, residual network, multi-output forecast model

战文华, 车建峰, 王勃, 丁禹. 基于网格化数值天气预报的区域光伏发电多输出功率预测方法[J]. 中国电力, 2024, 57(3): 144-151.

Wenhua ZHAN, Jianfeng CHE, Bo WANG, Yu DING. A Grid-based Numerical Weather Prediction Method for Multi-output Prediction of Regional Photovoltaic Power[J]. Electric Power, 2024, 57(3): 144-151.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305029

https://www.electricpower.com.cn/CN/Y2024/V57/I3/144

图/表 9

图 1 网格化数值天气预报某时刻单一气象参数

Fig.1 Single meteorological parameter of grid-based NWP at a certain time

图 2 网格化数值天气预报某时刻多个气象参数

Fig.2 Multiple meteorological parameters of grid-based NWP at a certain time

图 3 西北某地区在同一时刻的资源分布

Fig.3 Resource distribution of a certain region in Northwest China at the same time

图 4 区域各光伏电站功率和资源在同一时刻的分布

Fig.4 Distribution of power and resource of each PV station in the region at the same time

图 5 典型的残差单元结构示例

Fig.5 Example of typical residual element structure

图 6 气象参数优选步骤

Fig.6 Steps of selection of meteorological parameters

表 1 不同方法对46座光伏电站总功率的预测性能

Table 1 Performance of different methods for total power prediction of 46 PV stations

算法	E_mae /%	E_rmse /%	r
BPNN	5.87	8.25	0.958
XGBoost	6.60	8.97	0.952
本文方法	5.74	8.00	0.960

图 7 不同方法对46座光伏电站的预测性能

Fig.7 Performance of different methods for power prediction of 46 PV stations

图 8 总出力预测结果

Fig.8 Prediction results of total power

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