RT Conference Proceedings
T1 A Novel Metaheuristic Approach for Loss Reduction and Voltage Profile Improvement in Power Distribution Networks Based on Simultaneous Placement and Sizing of Distributed Generators and Shunt Capacitor Banks
A1 Nasir, Mohammad
A1 Sadollah, Ali
A1 Osaba, Eneko
A1 Del Ser, Javier
A2 Analide, Cesar
A2 Novais, Paulo
A2 Camacho, David
A2 Yin, Hujun
AB In this paper, Neural Network Algorithm is employed for simultaneous placing and sizing Distributed Generators and Shunt Capacitors Banks in distribution network to minimize active power loss and improve the voltage profile. The NNA is a novel developed optimizer based on the concept of artificial neural networks which benefits from its unique structure and search operators for solving complex optimization problems. The difficulty of tuning the initial parameters and trapping in local optima is eliminated in the proposed optimizer. The capability and effectiveness of the proposed algorithm are evaluated on IEEE 69-bus distribution system with considering nine cases and the results are compared with previous published methods. Simulation outcomes of the recommended algorithm are assessed and compared with those attained by Genetic Algorithms, Grey Wolf Optimizer, and Water Cycle Algorithm. The analysis of these results is conclusive in regard to the superiority of the proposed algorithm.
PB Springer
SN 978-3-030-62361-6; 978-3-030-62362-3
SN 9783030623616
YR 2020
FD 2020-10-27
LA eng
NO Nasir , M , Sadollah , A , Osaba , E & Del Ser , J 2020 , A Novel Metaheuristic Approach for Loss Reduction and Voltage Profile Improvement in Power Distribution Networks Based on Simultaneous Placement and Sizing of Distributed Generators and Shunt Capacitor Banks . in C Analide , P Novais , D Camacho & H Yin (eds) , unknown . vol. 12489 , 0302-9743 , Springer , pp. 64-76 , 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 , Guimaraes , Portugal , 4/11/20 . https://doi.org/10.1007/978-3-030-62362-3_7
NO conference
NO Publisher Copyright: © 2020, Springer Nature Switzerland AG.
DS TECNALIA Publications
RD 1 jul 2024