Abstract
The influence of parameters on system states for parametric problems in power systems is to be evaluated. These parameters could be renewable generation outputs, load factor, etc. Polynomial approximation has been applied to express the nonlinear relationship between system states and parameters, governed by the nonlinear and implicit equations. Usually, sampling-based methods are applied, e.g., data fitting methods and sensitivity methods, etc. However, the accuracy and stability of these methods are not guaranteed. This paper proposes an innovative method based on Galerkin method, providing global optimal approximation. Compared to traditional methods, this method enjoys high accuracy and stability. IEEE 9-bus system is used to illustrate its effectiveness, and two additional studies including a 1648-bus system are performed to show its applications to power system analysis.
| Original language | English |
|---|---|
| Pages (from-to) | 500-511 |
| Number of pages | 12 |
| Journal | Journal of Modern Power Systems and Clean Energy |
| Volume | 7 |
| Issue number | 3 |
| Early online date | 21 Dec 2018 |
| DOIs | |
| Publication status | Published - 1 May 2019 |
Keywords
- Galerkin method
- Global approximation
- Load flow problems
- Optimal approximation
- Parametric problems
- Polynomial approximation
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
Cite this
Global optimal polynomial approximation for parametric problems in power systems. / Zhou, Yongzhi; Wu, Hao; Gu, Chenghong; Song, Yonghua.
In: Journal of Modern Power Systems and Clean Energy, Vol. 7, No. 3, 01.05.2019, p. 500-511.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Global optimal polynomial approximation for parametric problems in power systems
AU - Zhou, Yongzhi
AU - Wu, Hao
AU - Gu, Chenghong
AU - Song, Yonghua
PY - 2019/5/1
Y1 - 2019/5/1
N2 - The influence of parameters on system states for parametric problems in power systems is to be evaluated. These parameters could be renewable generation outputs, load factor, etc. Polynomial approximation has been applied to express the nonlinear relationship between system states and parameters, governed by the nonlinear and implicit equations. Usually, sampling-based methods are applied, e.g., data fitting methods and sensitivity methods, etc. However, the accuracy and stability of these methods are not guaranteed. This paper proposes an innovative method based on Galerkin method, providing global optimal approximation. Compared to traditional methods, this method enjoys high accuracy and stability. IEEE 9-bus system is used to illustrate its effectiveness, and two additional studies including a 1648-bus system are performed to show its applications to power system analysis.
AB - The influence of parameters on system states for parametric problems in power systems is to be evaluated. These parameters could be renewable generation outputs, load factor, etc. Polynomial approximation has been applied to express the nonlinear relationship between system states and parameters, governed by the nonlinear and implicit equations. Usually, sampling-based methods are applied, e.g., data fitting methods and sensitivity methods, etc. However, the accuracy and stability of these methods are not guaranteed. This paper proposes an innovative method based on Galerkin method, providing global optimal approximation. Compared to traditional methods, this method enjoys high accuracy and stability. IEEE 9-bus system is used to illustrate its effectiveness, and two additional studies including a 1648-bus system are performed to show its applications to power system analysis.
KW - Galerkin method
KW - Global approximation
KW - Load flow problems
KW - Optimal approximation
KW - Parametric problems
KW - Polynomial approximation
UR - http://www.scopus.com/inward/record.url?scp=85065591156&partnerID=8YFLogxK
U2 - 10.1007/s40565-018-0469-2
DO - 10.1007/s40565-018-0469-2
M3 - Article
VL - 7
SP - 500
EP - 511
JO - Journal of Modern Power Systems and Clean Energy
JF - Journal of Modern Power Systems and Clean Energy
SN - 2196-5695
IS - 3
ER -