TY - JOUR
T1 - Distribution system state estimation
T2 - an overview of recent developments
AU - Wang, Gang
AU - Giannakis, Georgios B.
AU - Chen, Jie
AU - Sun, Jian
N1 - Publisher Copyright:
© 2019, Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - Bad data detection
KW - Composite optimization
KW - Cramér-Rao bound
KW - Cyber attack
KW - Feasible point pursuit
KW - Proximal linear algorithm
KW - Semidefinite relaxation
KW - State estimation
KW - TP311
UR - http://www.scopus.com/inward/record.url?scp=85061248792&partnerID=8YFLogxK
U2 - 10.1631/FITEE.1800590
DO - 10.1631/FITEE.1800590
M3 - Review article
AN - SCOPUS:85061248792
SN - 2095-9184
VL - 20
SP - 4
EP - 17
JO - Frontiers of Information Technology and Electronic Engineering
JF - Frontiers of Information Technology and Electronic Engineering
IS - 1
ER -