TY - GEN
T1 - Implementation of Multi-objective Particle Swarm Optimization in Distribution Network for High-efficiency Allocation and Sizing of SAPFs
AU - Yang, Zebin
AU - Zhuo, Fang
AU - Tao, Ran
AU - Zhang, Ziqian
AU - Yi, Hao
AU - Wang, Meng
AU - Zhu, Chengzhi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - The traditional control strategies of shunt active power filter (SAPF) is primarily focused on the compensation of local non-linear loads, which may become uneconomical for the network with a number of distributed non-linear loads. In this paper, two methods applied to the allocation and sizing of multiple shunt active filters in distribution network are proposed and compared, including an improved particle swarm optimization (PSO) algorithm with one mixed objective function and a multi-objective particle swarm optimization (MOPSO) algorithm. To evaluate the capability of the proposed methods, the IEEE 18-bus test system is employed in simulation. Simulation results confirms that both methods can achieve the goal but the MOPSO-based algorithm is more efficient and universal in the allocation and sizing of multiple SAPFs compared with the PSO based algorithm.
AB - The traditional control strategies of shunt active power filter (SAPF) is primarily focused on the compensation of local non-linear loads, which may become uneconomical for the network with a number of distributed non-linear loads. In this paper, two methods applied to the allocation and sizing of multiple shunt active filters in distribution network are proposed and compared, including an improved particle swarm optimization (PSO) algorithm with one mixed objective function and a multi-objective particle swarm optimization (MOPSO) algorithm. To evaluate the capability of the proposed methods, the IEEE 18-bus test system is employed in simulation. Simulation results confirms that both methods can achieve the goal but the MOPSO-based algorithm is more efficient and universal in the allocation and sizing of multiple SAPFs compared with the PSO based algorithm.
KW - Harmonic compensation
KW - Multi-objective particle swarm optimization(MOPSO)
KW - Particle swarm optimization(PSO)
KW - Shunt active power filter (SAPF)
UR - https://www.scopus.com/pages/publications/85077130720
U2 - 10.1109/ICEMS.2019.8922399
DO - 10.1109/ICEMS.2019.8922399
M3 - 会议稿件
AN - SCOPUS:85077130720
T3 - 2019 22nd International Conference on Electrical Machines and Systems, ICEMS 2019
BT - 2019 22nd International Conference on Electrical Machines and Systems, ICEMS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference on Electrical Machines and Systems, ICEMS 2019
Y2 - 11 August 2019 through 14 August 2019
ER -