2024 : 4 : 21
Amirhossein Abolmasoumi

Amirhossein Abolmasoumi

Academic rank: Associate Professor
ORCID: https://orcid.org/0000-0001-9739-1340
Education: PhD.
ScopusId: 26664422200
Faculty: Engineering
Address: Arak University
Phone:

Research

Title
An Improved TPM-Based Distribution Network State Estimation Considering Loads/DERs Correlations
Type
JournalPaper
Keywords
State estimation, Probabilistic loads , Pseudo-measurements, Weighted least squares (WLS), Two-point method (TPM)
Year
2021
Journal Electrical Engineering
DOI
Researchers Bahman Abedi ، Aliasghar Ghadimi ، Amirhossein Abolmasoumi ، Mohammad Reza Miveh ، Francisco Jurado

Abstract

This paper proposes an improved probabilistic load and distributed energy resources (DERs) modeling as pseudo-measurements by considering the correlation to be used for distribution network state estimation. The two-point method (TPM) is applied for the modeling of pseudo-measurements. The proposed method has the ability to estimate the states of a distribution network with high accuracy and short computational time. To implement the proposed scheme, the probability density functions (PDFs) of uncertain loads and DERs at different buses are extracted using historical data. Then, the TPM achieves two concentration points at each bus from obtained PDFs. Finally, the weighted least squares state estimation method is utilized at these two concentration points to obtain the probabilistic distribution of output variables. To examine the effectiveness of the suggested model, simulations are carried out on IEEE 69-bus standard test system. The proposed TPM-based state estimation approach is then compared with other conventional methods such as the Gaussian-based model, Gaussian mixture model (GMM) and Monte Carlo simulation. The superiority of the proposed TPM-based state estimation model over the GMM and Gaussian model is confirmed by a significant decrease in the running time and a noteworthy increase in the accuracy of all estimated variables.