使用基于RANSAC的多项式和线性回归与自适应值的风力发电数据清理
Haineng Yang1,2, Jie Tang3, Wu Shao1
1School of Electrical Engineering, Shaoyang University, Shaoyang, 422000, China.
Scientific reports
|February 11, 2025
概括
这项研究引入了一种适应性强回归模型来清理风力发电数据,通过减少72.1%的错误,显著提高了预测准确度. 该方法有效地处理密集的异常,增强电网安全性和可再生能源整合.
科学领域:
- 可再生能源系统可再生能源系统
- 数据科学和分析数据科学和分析
- 电力系统工程 电力系统工程
背景情况:
- 全球对清洁能源需求的不断增长凸显了风力发电的重要性.
- 风力发电数据中的密集异常会降低预测准确度,并危及电网安全.
- 现有的数据清理方法与高比例的密集异常作斗争.
研究的目的:
- 为有效的风力发电数据清理提出一个自适应值可靠回归模型 (RPR模型).
- 为应对风力发电数据集中密集异常的挑战.
- 提高风力发电预测模型的准确性,确保电网安全.
主要方法:
- 开发了一个RPR模型,结合了随机样本共识 (RANSAC) 算法和多项式线性回归.
- 扩展的多项式特征,以捕捉风速和功率之间的非线性关系.
- 根据余量中位数和中位数绝对偏差 (MAD) 进行动态值调整,用于异常检测和清理.
主要成果:
- 与现有方法相比,RPR模型在数据清理方面表现优越 (双向变化点分组四分位数统计模型,主要轮图像处理模型,DBSCAN,SVM).
- 在风力发电预测模型的平均绝对误差 (MAE) 中实现了显著的72.1%的减少.
- 有效地减少了卷积神经网络 (CNN) +门式循环单元 (GRU) 预测模型的预测错误,确保了高准确性.
结论:
- 拟议的自适应值强健回归模型是风力发电数据清理的创新和有效方法.
- 该模型在处理高比例密度异常的数据集方面表现出色,优于传统方法.
- 这种方法为改善风力发电数据质量,预测准确性和电网安全性提供了重大潜力.
相关概念视频
01:15Routh-Hurwitz Criterion I
143
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
143
01:11Residuals and Least-Squares Property
7.3K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.3K
01:20Calibration Curves: Linear Least Squares
1.2K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
For data that follow a straight line, the standard method for fitting is the linear...
1.2K
01:17Wald-Wolfowitz Runs Test I
597
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
The test works...
597
01:19Routh-Hurwitz Criterion II
174
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
174
01:24Fast Decoupled and DC Powerflow
159
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
159