BibTex format

author = {Nanchian, SN and Majumdar, AM and Pal, BP},
doi = {10.1109/PESGM.2016.7741159},
publisher = {IEEE},
title = {Three-phase state estimation using hybrid particle swarm optimization},
url = {},
year = {2016}

RIS format (EndNote, RefMan)

AB - This paper proposes a method for three-phase state estimation (SE) in power distribution network including onload tap changers (OLTC) for voltage control. The OLTC tap positions are essentially discrete variables from the SE point of view. Estimation of these variables in SE presents a formidable challenge. The proposed methodology combines discrete and continuous state variables (voltage magnitudes, angles, and tap positions). A hybrid particle swarm optimization (HPSO) is applied to obtain the solution. The method is tested on standard IEEE 13- and 123-bus unbalanced test system models. The proposed algorithm accurately estimates the network bus voltage magnitudes and angles, and discrete tap values. The HPSO-based tap estimation provides a more accurate estimation of losses in the network, which helps in fair allocation of cost of losses in arriving at overall cost of electricity.
AU - Nanchian,SN
AU - Majumdar,AM
AU - Pal,BP
DO - 10.1109/PESGM.2016.7741159
PY - 2016///
TI - Three-phase state estimation using hybrid particle swarm optimization
UR -
ER -