Residential College | false |
Status | 已發表Published |
Optimal Control of AGC Systems Considering Non-Gaussian Wind Power Uncertainty | |
Chen,Xiaoshuang1; Lin,Jin1; Liu,Feng1; Song,Yonghua2,3 | |
2019-01-16 | |
Source Publication | IEEE Transactions on Power Systems |
ISSN | 0885-8950 |
Volume | 34Issue:4Pages:2730-2743 |
Abstract | Wind power uncertainty poses significant challenges for automatic generation control (AGC) systems. It can enhance control performances to explicitly consider wind power uncertainty distributions within controller design. However, widely accepted wind uncertainties usually follow non-Gaussian distributions, which may lead to complicated stochastic AGC modeling and high computational burdens. To overcome the issue, this paper presents a novel Itô-theory-based model for the stochastic control problem (SCP) of AGC systems, which reduces the computational burden of optimization considering non-Gaussian wind power uncertainty to the same scale as that for deterministic control problems. We present an Itô process model to exactly describe non-Gaussian wind power uncertainty, and then propose an SCP based on the concept of stochastic assessment functions (SAFs). Based on a convergent series expansion of the SAF, the SCP is reformulated as a certain deterministic control problem without sacrificing performance under non-Gaussian wind power uncertainty. The reformulated control problem is proven as a convex optimization, which can be solved efficiently. A case study demonstrates the efficiency and accuracy of the proposed approach compared with several conventional approaches. |
Keyword | Automatic Generation Control Itô Theory Non-gaussian Distribution Stochastic Control Stochastic Differential Equation Wind Power Uncertainty |
DOI | 10.1109/TPWRS.2019.2893512 |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Engineering |
WOS Subject | Engineering, Electrical & Electronic |
WOS ID | WOS:000472579200023 |
Scopus ID | 2-s2.0-85067808387 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Faculty of Science and Technology |
Corresponding Author | Lin,Jin |
Affiliation | 1.State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment,Department of Electrical Engineering,Tsinghua University,Beijing,China 2.Department of Electrical and Computer Engineering,University of Macau,Macao 3.Department of Electrical Engineering,Tsinghua University,Beijing,100084,China |
Recommended Citation GB/T 7714 | Chen,Xiaoshuang,Lin,Jin,Liu,Feng,et al. Optimal Control of AGC Systems Considering Non-Gaussian Wind Power Uncertainty[J]. IEEE Transactions on Power Systems, 2019, 34(4), 2730-2743. |
APA | Chen,Xiaoshuang., Lin,Jin., Liu,Feng., & Song,Yonghua (2019). Optimal Control of AGC Systems Considering Non-Gaussian Wind Power Uncertainty. IEEE Transactions on Power Systems, 34(4), 2730-2743. |
MLA | Chen,Xiaoshuang,et al."Optimal Control of AGC Systems Considering Non-Gaussian Wind Power Uncertainty".IEEE Transactions on Power Systems 34.4(2019):2730-2743. |
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