Online power system parameter estimation and optimal operation

doi:10.23919/ACC50511.2021.9482814

	Online power system parameter estimation and optimal operation
	Xu Du1 ; Alexander Engelmann 2; Timm Faulwasser 2; Boris Houska1
	2021-05-25
会议录名称	PROCEEDINGS OF THE AMERICAN CONTROL CONFERENCE
ISSN	0743-1619
卷号	2021-May
页码	3126-3131
发表状态	已发表
DOI	10.23919/ACC50511.2021.9482814
摘要	The integration of renewables into electrical grids calls for novel control schemes, which usually are model based. Classically, for power systems parameter estimation and optimization-based control are often decoupled, which may lead to increased cost of system operation during the estimation procedures. The present work proposes a method for simultaneously minimizing grid operation cost and estimating line parameters. To this end, we rely on methods from optimal design of experiments. This approach leads to a substantial reduction in cost for optimal estimation and in higher accuracy in the parameters compared with standard combination of optimal power flow and maximum-likelihood estimation. We illustrate the performance of the proposed method on simple benchmark system. © 2021 American Automatic Control Council.
会议录编者/会议主办者	et al. ; Halliburton ; MathWorks ; Mitsubishi Electric Research Laboratory (MERL) ; US National Member Organization (NMO) of the International Federation of Automatic Control (IFAC) ; Wiley
关键词	Benchmarking Cost estimating Design of experiments Electric load flow Maximum likelihood estimation-Cost of system operations Estimation and optimization Estimation procedures Integration of renewables Novel control scheme Optimal estimations Power system parameter estimation Substantial reduction
会议名称	2021 American Control Conference, ACC 2021
会议地点	Virtual, New Orleans, LA, United states
会议日期	May 25, 2021 - May 28, 2021
URL	查看原文
收录类别	EI ; CPCI ; CPCI-S
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20213210733407
EI主题词	Parameter estimation
EI分类号	706.1 Electric Power Systems ; 901.3 Engineering Research ; 911 Cost and Value Engineering ; Industrial Economics ; 922 Statistical Methods
原始文献类型	Conference article (CA)
来源库	IEEE
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/135784
专题	信息科学与技术学院信息科学与技术学院_PI研究组_Boris Houska组信息科学与技术学院_博士生
作者单位	1.School of Information Science and Technology, ShanghaiTech University, China 2.Institute of Energy Systems, Energy Efficiency and Energy Economics, TU Dortmund University, Germany
第一作者单位	信息科学与技术学院
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Xu Du,Alexander Engelmann,Timm Faulwasser,et al. Online power system parameter estimation and optimal operation[C]//et al., Halliburton, MathWorks, Mitsubishi Electric Research Laboratory (MERL), US National Member Organization (NMO) of the International Federation of Automatic Control (IFAC), Wiley:Institute of Electrical and Electronics Engineers Inc.,2021:3126-3131.