Overview of Data-driven Power Flow Linearization

被引:3
作者
Jia, Mengshuo [1 ]
Hug, Gabriela [1 ]
机构
[1] Swiss Fed Inst Technol, Power Syst Lab, Zurich, Switzerland
来源
2023 IEEE BELGRADE POWERTECH | 2023年
关键词
Power flow linearization; data-driven; machine learning; regression; programming; RIDGE-REGRESSION; SENSITIVITY; MODEL;
D O I
10.1109/POWERTECH55446.2023.10202779
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The accuracy limitation of physics-driven power flow linearization approaches and the widespread deployment of advanced metering infrastructure render data-driven power flow linearization (DPFL) methods a valuable alternative. While DPFL is still an emerging research topic, substantial studies have already been carried out in this area. However, a comprehensive overview and comparison of the available DPFL approaches are missing in the existing literature. This paper intends to close this gap and, therefore, provides a narrative overview of the current DPFL research. Both the challenges (including data-related and power-system-related issues) and methodologies (namely regression-based and tailored approaches) in DPFL studies are surveyed in this paper; numerous future research directions of DPFL analysis are discussed and summarized as well.
引用
收藏
页数:6
相关论文
共 55 条
[1]   Statistical Characterization of PMU Error for Robust WAMS Based Analytics [J].
Ahmad, Tabia ;
Senroy, Nilanjan .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (02) :920-928
[2]  
[Anonymous], 2009, Convex optimization
[3]  
[Anonymous], 2001, The Elements of Statistical Learning
[4]   Application of Recursive Least Squares Algorithm With Variable Forgetting Factor for Frequency Component Estimation in a Generic Input Signal [J].
Beza, Mebtu ;
Bongiorno, Massimo .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2014, 50 (02) :1168-1176
[5]  
Brown M, 2016, IEEE POW ENER SOC GE
[6]   An Integrated Approach for Value-Oriented Energy Forecasting and Data-Driven Decision-Making Application to Renewable Energy Trading [J].
Carriere, Thomas ;
Kariniotakis, George .
IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (06) :6933-6944
[7]   Data-Driven Piecewise Linearization for Distribution Three-Phase Stochastic Power Flow [J].
Chen, Jiaqi ;
Wu, Wenchuan ;
Roald, Line A. .
IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (02) :1035-1048
[8]   Data-driven Power Flow Method Based on Exact Linear Regression Equations [J].
Chen, Yanbo ;
Wu, Chao ;
Qi, Junjian .
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2022, 10 (03) :800-804
[9]   From Optimization-Based Machine Learning to Interpretable Security Rules for Operation [J].
Cremer, Jochen L. ;
Konstantelos, Ioannis ;
Strbac, Goran .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (05) :3826-3836
[10]   SIMPLS - AN ALTERNATIVE APPROACH TO PARTIAL LEAST-SQUARES REGRESSION [J].
DEJONG, S .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1993, 18 (03) :251-263