Distribution system state estimation: an overview of recent developments

Gang WANG; Georgios B. GIANNAKIS; Jie CHEN; Jian SUN

doi:10.1631/FITEE.1800590

Your Location：

Home >

Browse articles >

Distribution system state estimation: an overview of recent developments

Special Issue on Complex System and Intelligent Control | Updated：2022-05-19

- Distribution system state estimation: an overview of recent developments
- 智能电网状态估计方法最新进展综述
- Frontiers of Information Technology & Electronic Engineering Vol. 20, Issue 1, Pages: 4-17(2019)
- Affiliations：
  
  Department of Electrical and Computer Engineering and Digital Technology Center, University of Minnesota, Minneapolis, MN 55455, USA
  School of Automation, Beijing Institute of Technology, Beijing 100081, China
  Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, Beijing 100081, China
- Author bio：
  
  [ "Gang WANG, E-mail: gangwang@umn.edu" ]
  [ "Georgios B. GIANNAKIS, E-mail: gangwang@umn.edu" ]
  [ "Jie CHEN, E-mail: gangwang@umn.edu" ]
  SUN Jian, E-mail: sunjian@bit.edu.cn
- Funds：
- DOI：10.1631/FITEE.1800590
  CLC： TP311
- Received：23 September 2018，
  
  Revised：2019-;1-;8，
  
  Published：2019-01
- Accepted：
Scan QR Code
Gang WANG, Georgios B. GIANNAKIS, Jie CHEN, et al. Distribution system state estimation: an overview of recent developments[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(1): 4-17.
DOI：

Gang WANG, Georgios B. GIANNAKIS, Jie CHEN, et al. Distribution system state estimation: an overview of recent developments[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(1): 4-17. DOI： 10.1631/FITEE.1800590.

摘要

随着大量不确定可再生能源注入、大规模工业和个体用户市场参与、恶意智能仪表数据篡改等，精确、快速、鲁棒的状态估计方法对未来智能电网系统变得尤为重要。然而，目前电力系统采用的数据采集与监视控制系统只能获取系统状态（即系统所有节点的电压相量）的非线性测量数据。最新智能电网状态估计研究正着力于解决非线性测量数据带给可扩展性状态估计方法建模和计算方面的挑战。为使读者更好理解该领域最新进展，本文综述了基于非线性最小二乘和最小绝对误差的智能电网状态估计方法。为更好比较不同状态估计方法性能，首先描述了智能电网状态估计问题的克拉美罗下界。针对网络攻击问题，引入新的电力系统测量数据攻击模型，并介绍相应鲁棒状态估计方法。最后，分析配电网系统状态估计最新研究进展和挑战。仿真实验验证了该状态估计方法和理论的有效性和优点。

Abstract

In the envisioned smart grid

high penetration of uncertain renewables

unpredictable participation of (industrial) customers

and purposeful manipulation of smart meter readings

all highlight the need for accurate

fast

and robust power system state estimation (PSSE). Nonetheless

most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e.

nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study

we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators

the Cramér-Rao lower bound is developed. Accounting for cyber attacks

new corruption models are introduced

and robust PSSE approaches are outlined as well. Finally

distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.

关键词

Keywords

references

A Abur , , , MK Celik . . A fast algorithm for the weighted least-absolute-value state estimation (for power systems) . . IEEE Trans Power Syst , , 1991 . . 6 ( ( 1 ): ): 1 - - 8 . . DOI: 10.1109/59.131040 http://doi.org/10.1109/59.131040 . .

A Abur , , , A Gómez-Expósito . . Power System State Estimation:Theory and Implementation . . Marcel Dekker, New York, USA. , , 2004 . . .

HG Aghamolki , , , Z Miao , , , L Fan . . SOCP convex relaxation-based simultaneous state estimation and bad data identification . . 2018 . . https://arxiv.org/abs/1804.05130 https://arxiv.org/abs/1804.05130 , , . .

F Ahmad , , , A Rasool , , , E Ozsoy , , , 等 . . Distribution system state estimation-a step towards smart grid . . Renew Sust Energ Rev , , 2018 . . 81 2659 - - 2671 . . DOI: 10.1016/j.rser.2017.06.071 http://doi.org/10.1016/j.rser.2017.06.071 . .

ME Baran . . Challenges in state estimation on distribution systems . . Power Engineering Society Summer Meeting , , 2001 . . p.429 - - 433 . . DOI: 10.1109/PESS.2001.970062 http://doi.org/10.1109/PESS.2001.970062 . .

A Ben-Tal , , , A Nemirovski . . Lectures on Modern Convex Optimization:Analysis, Algorithms, and Engineering Applications . . SIAM, Philadelphia, USA. , , 2001 . . .

DP Bertsekas . . Nonlinear Programming . . Athena Scientific, Belmont, Massachusetts, USA. , , 1999 . . .

S Bhela , , , V Kekatos , , , S Veeramachaneni . . Enhancing observability in distribution grids using smart meter data . . IEEE Trans Smart Grid , , 2018 . . 9 ( ( 6 ): ): 5953 - - 5961 . . DOI: 10.1109/TSG.2017.2699939 http://doi.org/10.1109/TSG.2017.2699939 . .

JV Burke , , , MC Ferris . . A Gauss-Newton method for convex composite optimization . . Math Programm , , 1995 . . 71 ( ( 2 ): ): 179 - - 194 . . DOI: 10.1007/BF01585997 http://doi.org/10.1007/BF01585997 . .

EJ Candès , , , X Li , , , M Soltanolkotabi . . Phase retrieval via Wirtinger flow:theory and algorithms . . IEEE Trans Inform Theory , , 2015 . . 61 ( ( 4 ): ): 1985 - - 2007 . . DOI: 10.1109/TIT.2015.2399924 http://doi.org/10.1109/TIT.2015.2399924 . .

E Caro , , , A Conejo . . State estimation via mathematical programming:a comparison of different estimation algorithms . . IET Gener Transm Distrib , , 2012 . . 6 ( ( 6 ): ): 545 - - 553 . . DOI: 10.1049/iet-gtd.2011.0663 http://doi.org/10.1049/iet-gtd.2011.0663 . .

RD Christie . . Power Systems Test Case Archive . . University of Washington. , , 1999 . . https://labs.ece.uw.edu/pstca/ https://labs.ece.uw.edu/pstca/ , , . .

KA Clements . . The impact of pseudo-measurements on state estimator accuracy . . IEEE Power and Energy Society General Meeting , , 2011 . . p.1 - - 4 . . DOI: 10.1109/PES.2011.6039370 http://doi.org/10.1109/PES.2011.6039370 . .

D Della Giustina , , , M Pau , , , PA Pegoraro , , , 等 . . Electrical distribution system state estimation:measurement issues and challenges . . IEEE Instrum Meas Mag , , 2014 . . 17 ( ( 6 ): ): 36 - - 42 . . DOI: 10.1109/MIM.2014.6968929 http://doi.org/10.1109/MIM.2014.6968929 . .

JC Duchi , , , F Ruan . . Solving (most) of a set of quadratic equalities:composite optimization for robust phase retrieval . . Inform Infer J IMA , iay015 , , 2017a . . DOI: 10.1093/imaiai/iay015 http://doi.org/10.1093/imaiai/iay015 . .

JC Duchi , , , F Ruan . . Stochastic methods for composite optimization problems . . 2017b . . https://arxiv.org/abs/1703.08570 https://arxiv.org/abs/1703.08570 , , . .

I Džafić , , , RA Jabr , , , T Hrnjić . . High performance distribution network power flow using Wirtinger calculus . . IEEE Trans Smart Grid , in press , , 2018a . . DOI: 10.1109/TSG.2018.2824018 http://doi.org/10.1109/TSG.2018.2824018 . .

I Džafić , , , RA Jabr , , , T Hrnjić . . Hybrid state estimation in complex variables . . IEEE Trans Power Syst , , 2018b . . 33 ( ( 5 ): ): 5288 - - 5296 . . DOI: 10.1109/TPWRS.2018.2794401 http://doi.org/10.1109/TPWRS.2018.2794401 . .

P Fairley . . Cybersecurity at US utilities due for an upgrade:tech to detect intrusions into industrial control systems will be mandatory . . IEEE Spectr , , 2016 . . 53 ( ( 5 ): ): 11 - - 13 . . DOI: 10.1109/MSPEC.2016.7459104 http://doi.org/10.1109/MSPEC.2016.7459104 . .

R Fletcher , , , GA Watson . . First and second order conditions for a class of nondifferentiable optimization problems . . Math Programm , , 1980 . . 18 ( ( 1 ): ): 291 - - 307 . . DOI: 10.1007/BF01588325 http://doi.org/10.1007/BF01588325 . .

GB Giannakis , , , V Kekatos , , , N Gatsis , , , 等 . . Monitoring and optimization for power grids:a signal processing perspective . . IEEE Signal Process Mag , , 2013 . . 30 ( ( 5 ): ): 107 - - 128 . . DOI: 10.1109/MSP.2013.2245726 http://doi.org/10.1109/MSP.2013.2245726 . .

M Gl , , , A Abur . . LAV based robust state estimation for systems measured by PMUs . . IEEE Trans Smart Grid , , 2014 . . 5 ( ( 4 ): ): 1808 - - 1814 . . DOI: 10.1109/TSG.2014.2302213 http://doi.org/10.1109/TSG.2014.2302213 . .

YF Huang , , , S Werner , , , J Huang , , , 等 . . State estimation in electric power grids:meeting new challenges presented by the requirements of the future grid . . IEEE Signal Process Mag , , 2012 . . 29 ( ( 5 ): ): 33 - - 43 . . DOI: 10.1109/MSP.2012.2187037 http://doi.org/10.1109/MSP.2012.2187037 . .

PJ Huber . . Robust Statistics . . In:Lovric M (Ed.), International Encyclopedia of Statistical Science. Springer, Berlin , , 2011 . . p.1248 - - 1251 . . . .

R Jabr , , , B Pal . . Iteratively re-weighted least-absolutevalue method for state estimation . . IET Gener Transm Distrib , , 2003 . . 150 ( ( 4 ): ): 385 - - 391 . . DOI: 10.1049/ip-gtd:20030462 http://doi.org/10.1049/ip-gtd:20030462 . .

R Jabr , , , B Pal . . Iteratively reweighted least-squares implementation of the WLAV state-estimation method . . IET Gener Transm Distrib , , 2004 . . 151 ( ( 1 ): ): 103 - - 108 . . DOI: 10.1049/ip-gtd:20040030 http://doi.org/10.1049/ip-gtd:20040030 . .

SM Kay . . Fundamentals of Statistical Signal Processing, Vol. I: Estimation Theory . . Prentice Hall, Englewood Cliffs, USA , , 1993 . . .

V Kekatos , , , GB Giannakis . . Distributed robust power system state estimation . . IEEE Trans Power Syst , , 2013 . . 28 ( ( 2 ): ): 1617 - - 1626 . . DOI: 10.1109/TPWRS.2012.2219629 http://doi.org/10.1109/TPWRS.2012.2219629 . .

V Kekatos , , , G Wang , , , H Zhu , , , 等 . . PSSE redux: convex relaxation, decentralized, robust, and dynamic approaches . . 2017 . . https://arxiv.org/abs/1708.03981 https://arxiv.org/abs/1708.03981 , , . .

SJ Kim , , , G Wang , , , GB Giannakis . . Online semidefinite programming for power system state estimation . . IEEE Conf on Acoustics, Speech, and Signal Process , , 2014 . . p.6024 - - 6027 . . DOI: 10.1109/ICASSP.2014.6854760 http://doi.org/10.1109/ICASSP.2014.6854760 . .

O Kosut , , , L Jia , , , J Thomas , , , 等 . . Malicious data attacks on the smart grid . . IEEE Trans Smart Grid , , 2011 . . 2 ( ( 4 ): ): 645 - - 658 . . DOI: 10.1109/TSG.2011.2163807 http://doi.org/10.1109/TSG.2011.2163807 . .

WW Kotiuga , , , M Vidyasagar . . Bad data rejection properties of weighted least-absolute-value techniques applied to static state estimation . . IEEE Trans Power Appar Syst , , 1982 . . 101 ( ( 4 ): ): 844 - - 853 . . DOI: 10.1109/TPAS.1982.317150 http://doi.org/10.1109/TPAS.1982.317150 . .

K Kreutz-Delgado . . The complex gradient operator and the CR-calculus . . 2009 . . https://arxiv.org/abs/0906.4835 https://arxiv.org/abs/0906.4835 , , . .

AS Lewis , , , SJ Wright , , , 等 . . A proximal method for composite minimization . . Math Programm , , 2016 . . 158 ( ( 1-2 ): ): 501 - - 546 . . DOI: 10.1007/s10107-015-0943-9 http://doi.org/10.1007/s10107-015-0943-9 . .

Y Liu , , , P Ning , , , MK Reiter . . False data injection attacks against state estimation in electric power grids . . ACM Trans Inform Syst Sec , , 2011 . . 14 ( ( 1 ): ): 1 - - 33 . . DOI: 10.1145/1952982.1952995 http://doi.org/10.1145/1952982.1952995 . .

C Lu , , , J Teng , , , WH Liu . . Distribution system state estimation . . IEEE Trans Power Syst , , 1995 . . 10 ( ( 1 ): ): 229 - - 240 . . DOI: 10.1109/59.373946 http://doi.org/10.1109/59.373946 . .

O Mehanna , , , K Huang , , , B Gopalakrishnan , , , 等 . . Feasible point pursuit and successive approximation of nonconvex QCQPs . . IEEE Signal Process Lett , , 2015 . . 22 ( ( 7 ): ): 804 - - 808 . . DOI: 10.1109/LSP.2014.2370033 http://doi.org/10.1109/LSP.2014.2370033 . .

L Mili , , , MG Cheniae , , , PJ Rousseeuw . . Robust state estimation of electric power systems . . IEEE Trans Circ Syst I Fundam Theory Appl , , 1994 . . 41 ( ( 5 ): ): 349 - - 358 . . DOI: 10.1109/81.296336 http://doi.org/10.1109/81.296336 . .

A Monticelli . . Electric power system state estimation . . Proc IEEE , , 2000 . . 88 ( ( 2 ): ): 262 - - 282 . . DOI: 10.1109/5.824004 http://doi.org/10.1109/5.824004 . .

Y Nesterov . . Introductory Lectures on Convex Optimization:a Basic Course . . Springer Science & Business Media, Boston, USA. , , 2013 . . .

PM Pardalos , , , SA Vavasis . . Quadratic programming with one negative eigenvalue is NP-hard . . J Glob Optim , , 1991 . . 1 ( ( 1 ): ): 15 - - 22 . . DOI: 10.1007/BF00120662 http://doi.org/10.1007/BF00120662 . .

J Park , , , S Boyd . . General heuristics for nonconvex quadratically constrained quadratic programming . . 2017 . . https://arxiv.org/abs/1703.07870 https://arxiv.org/abs/1703.07870 , , . .

Y Saad . . Iterative Methods for Sparse Linear Systems (2nd Ed.) . . Society for Industrial and Applied Mathematics, Philadelphia, USA. , , 2003 . . .

FC Schweppe , , , J Wildes , , , D Rom . . Power system static state estimation:parts Ⅰ, Ⅱ, and Ⅲ . . IEEE Trans Power Appar Syst , , 1970 . . 89 ( ( 1 ): ): 120 - - 135 . . . .

R Singh , , , B Pal , , , R Jabr . . Choice of estimator for distribution system state estimation . . IET Gener Transm Distrib , , 2009 . . 3 ( ( 7 ): ): 666 - - 678 . . DOI: 10.1049/iet-gtd.2008.0485 http://doi.org/10.1049/iet-gtd.2008.0485 . .

P Stoica , , , TL Marzetta . . Parameter estimation problems with singular information matrices . . IEEE Trans Signal Process , , 2001 . . 49 ( ( 1 ): ): 87 - - 90 . . DOI: 10.1109/78.890346 http://doi.org/10.1109/78.890346 . .

G Wang , , , SJ Kim , , , GB Giannakis . . Moving-horizon dynamic power system state estimation using semidefinite relaxation . . IEEE PES General Meeting & Conf Exposition , , 2014 . . p.1 - - 5 . . DOI: 10.1109/PESGM.2014.6939925 http://doi.org/10.1109/PESGM.2014.6939925 . .

G Wang , , , AS Zamzam , , , GB Giannakis , , , 等 . . Power system state estimation via feasible point pursuit . . IEEE Global Conf Signal and Information Process , , 2016 . . p.773 - - 777 . . DOI: 10.1109/GlobalSIP.2016.7905947 http://doi.org/10.1109/GlobalSIP.2016.7905947 . .

G Wang , , , GB Giannakis , , , J Chen . . Robust and scalable power system state estimation via composite optimization . . 2017 . . https://arxiv.org/abs/1708.06013 https://arxiv.org/abs/1708.06013 , , . .

G Wang , , , GB Giannakis , , , Y Saad , , , 等 . . Phase retrieval via reweighted amplitude flow . . IEEE Trans Signal Process , , 2018a . . 66 ( ( 11 ): ): 2818 - - 2833 . . DOI: 10.1109/TSP.2018.2818077 http://doi.org/10.1109/TSP.2018.2818077 . .

G Wang , , , AS Zamzam , , , GB Giannakis , , , 等 . . Power system state estimation via feasible point pursuit:algorithms and Cramér-Rao bound . . IEEE Trans Signal Process , , 2018b . . 66 ( ( 6 ): ): 1649 - - 1658 . . DOI: 10.1109/TSP.2018.2791977 http://doi.org/10.1109/TSP.2018.2791977 . .

G Wang , , , H Zhu , , , GB Giannakis , , , 等 . . Robust power system state estimation from rank-one measurements . . IEEE Trans Contr Netw Syst , in press , , 2018c . . DOI: 10.1109/TCNS.2019.2890954 http://doi.org/10.1109/TCNS.2019.2890954 . .

G Wang , , , GB Giannakis , , , YC Eldar . . Solving systems of random quadratic equations via truncated amplitude flow . . IEEE Trans Inform Theory , , 2018d . . 64 ( ( 2 ): ): 773 - - 794 . . DOI: 10.1109/TIT.2017.2756858 http://doi.org/10.1109/TIT.2017.2756858 . .

Z Wang , , , B Cui , , , J Wang . . A necessary condition for power flow insolvability in power distribution systems with distributed generators . . IEEE Trans Power Syst , , 2017 . . 32 ( ( 2 ): ): 1440 - - 1450 . . DOI: 10.1109/TPWRS.2016.2588341 http://doi.org/10.1109/TPWRS.2016.2588341 . .

AJ Wood , , , BF Wollenberg . . Power Generation, Operation, and Control (2nd Ed.) . . Wiley & Sons, New York, USA. , , 1996 . . .

WA Wulf . . Great achievements and grand challenges . . Nat Acad Eng , , 2000 . . 30 ( ( 1 ): ): 5 - - 10 . . . .

AS Zamzam , , , X Fu , , , ND Sidiropoulos . . Data-driven learning-based optimization for distribution system state estimation . . 2018 . . https://arxiv.org/abs/1807.01671 https://arxiv.org/abs/1807.01671 , , . .

L Zhang , , , G Wang , , , GB Giannakis . . Going beyond linear dependencies to unveil connectivity of meshed grids . . IEEE 7th Workshop on Computational Advances in Multi-sensor Adaptive Processing , , 2017 . . p.1 - - 5 . . DOI: 10.1109/CAMSAP.2017.8313078 http://doi.org/10.1109/CAMSAP.2017.8313078 . .

L Zhang , , , G Wang , , , GB Giannakis . . Real-time power system state estimation via deep unrolled neural networks . . IEEE Global Conf on Signal and Information Processing, in press. , , 2018a . . .

L Zhang , , , G Wang , , , GB Giannakis . . Real-time power system state estimation and forecasting via deep neural networks . . 2018b . . https://arxiv.org/abs/1811.06146 https://arxiv.org/abs/1811.06146 , , . .

L Zhang , , , G Wang , , , GB Giannakis . . Power system state forecasting via deep recurrent neural networks . . IEEE Conf on Acoustics, Speech, and Signal Process, in press. , , 2019 . . .

H Zhu , , , GB Giannakis . . Estimating the state of AC power systems using semidefinite programming . . North American Power Symp , , 2011 . . p.1 - - 7 . . DOI: 10.1109/NAPS.2011.6024862 http://doi.org/10.1109/NAPS.2011.6024862 . .

H Zhu , , , GB Giannakis . . Robust power system state estimation for the nonlinear AC flow model . . North American Power Symp , , 2012 . . p.1 - - 6 . . DOI: 10.1109/NAPS.2012.6336405 http://doi.org/10.1109/NAPS.2012.6336405 . .

H Zhu , , , GB Giannakis . . Power system nonlinear state estimation using distributed semidefinite programming . . IEEE J Sel Top Signal Process , , 2014 . . 8 ( ( 6 ): ): 1039 - - 1050 . . DOI: 10.1109/JSTSP.2014.2331033 http://doi.org/10.1109/JSTSP.2014.2331033 . .

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Realizing complex beams via amplitude-phase digital coding metasurfaces and semidefinite relaxation optimization

Related Author

Junwei WU

Qiong HUA

Hui XU

Hanqing YANG

Zhengxing WANG

Qiang CHENG

Tie Jun CUI

Related Institution

State Key Laboratory of Millimeter Waves, Southeast University

Peng Cheng Laboratory

Pazhou Laboratory (Huangpu)

Chat

Address：Zhejiang University Press, 148 Tianmushan Road, Hangzhou, China Postal code：310028
Tel：+86-571-88273162 Email：fitee@zju.edu.cn
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰