TY - GEN
T1 - Optimal Meter Configuration Based on Harmonic State Estimation Model and Binary Particle Swarm Optimization
AU - Wei, Wei
AU - Yi, Hao
AU - Zhang, Huaying
AU - Wang, Qing
AU - Yang, Zebin
AU - Zhuo, Fang
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The monitoring and estimation of harmonic is of great significance to maintain the stable operation of distribution networks. In order to determine the harmonic state level in network and reduce the investment and difficulty of installation, it is necessary to carry out research on the optimization of meter configuration. Therefore, this paper proposes a method of optimal meter configuration combining harmonic state estimation model and binary particle swarm optimization, which aims at estimating all harmonic state variables in the network while using fewer meters. Harmonic state estimation is the process of estimating the harmonic voltage and current state with limited data collected by meters according to the harmonic state estimation model. The rules of state estimation model are established based on the topology connection in network and Kirchhoff's law. IEEE-18 bus network is employed to apply the state estimation model and the result of optimization algorithm shows that only six meters are required to measure and estimate all the harmonic state variables. Finally, the real harmonic values of this network are obtained from Simulink/MATLAB to compare with the estimation values, which verifies the effectiveness of the proposed method.
AB - The monitoring and estimation of harmonic is of great significance to maintain the stable operation of distribution networks. In order to determine the harmonic state level in network and reduce the investment and difficulty of installation, it is necessary to carry out research on the optimization of meter configuration. Therefore, this paper proposes a method of optimal meter configuration combining harmonic state estimation model and binary particle swarm optimization, which aims at estimating all harmonic state variables in the network while using fewer meters. Harmonic state estimation is the process of estimating the harmonic voltage and current state with limited data collected by meters according to the harmonic state estimation model. The rules of state estimation model are established based on the topology connection in network and Kirchhoff's law. IEEE-18 bus network is employed to apply the state estimation model and the result of optimization algorithm shows that only six meters are required to measure and estimate all the harmonic state variables. Finally, the real harmonic values of this network are obtained from Simulink/MATLAB to compare with the estimation values, which verifies the effectiveness of the proposed method.
KW - binary particle swarm optimization
KW - harmonic state estimation
KW - optimal configuration
UR - https://www.scopus.com/pages/publications/85154589031
U2 - 10.1109/EEBDA56825.2023.10090766
DO - 10.1109/EEBDA56825.2023.10090766
M3 - 会议稿件
AN - SCOPUS:85154589031
T3 - 2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2023
SP - 991
EP - 994
BT - 2023 IEEE 2nd International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2023
Y2 - 24 February 2023 through 26 February 2023
ER -