TY - JOUR
T1 - A multi-objective artificial electric field optimization algorithm for allocation of wind turbines in distribution systems
AU - Naderipour, Amirreza
AU - Abdul-Malek, Zulkurnain
AU - Mustafa, Mohd Wazir Bin
AU - Guerrero, Josep M.
N1 - Funding Information:
The authors gratefully acknowledge financial support from the Universiti Teknologi Malaysia (Post-Doctoral Fellowship Scheme grant 05E09 , and RUG grants 01M44 , 02M18 , 05G88 , 4B482 ) and the VILLUM FONDEN, Denmark under the VILLUM Investigator Grant (no. 25920 ): Center for Research on Microgrids (CROM); www.crom.et.aau.dk .
Publisher Copyright:
© 2021 Elsevier B.V.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/7
Y1 - 2021/7
N2 - This paper presents wind turbine allocation in distribution systems to reduce active power loss and voltage deviations using a multi-objective Artificial Electric Field Algorithm (MOAEFA). The proposed method is a mathematical algorithm which is suitably capable to find optimal solutions based on the Pareto solution set using a fuzzy decision-making method. The proposed problem is implemented on 10, 33 and 69 bus IEEE radial distribution networks. The installation location, size and power factors of wind turbines are determined optimally using the MOAEFA method. Single and multi-objective allocation problem of wind turbines is implemented using AEFA, GWO, PSO and MOAEFA, MOGWO, MOPSO methods. The obtained the results of AEFA method achieves less power loss and voltage deviations compared to the conventional GWO and PSO methods. Moreover, the results of multi-objective fuzzy allocation show that there is a compromise between single-objective results and MOAEFA method provides better performance given the loss power and voltage deviation reduction in distribution networks. Furthermore, MOAEFA method has found a better voltage profile in the allocation of wind turbines in the distribution network compared to the other methods. The performance comparison between MOAEFA method and the previous methods given in the literature verifies the superiority of the MOAEFA method.
AB - This paper presents wind turbine allocation in distribution systems to reduce active power loss and voltage deviations using a multi-objective Artificial Electric Field Algorithm (MOAEFA). The proposed method is a mathematical algorithm which is suitably capable to find optimal solutions based on the Pareto solution set using a fuzzy decision-making method. The proposed problem is implemented on 10, 33 and 69 bus IEEE radial distribution networks. The installation location, size and power factors of wind turbines are determined optimally using the MOAEFA method. Single and multi-objective allocation problem of wind turbines is implemented using AEFA, GWO, PSO and MOAEFA, MOGWO, MOPSO methods. The obtained the results of AEFA method achieves less power loss and voltage deviations compared to the conventional GWO and PSO methods. Moreover, the results of multi-objective fuzzy allocation show that there is a compromise between single-objective results and MOAEFA method provides better performance given the loss power and voltage deviation reduction in distribution networks. Furthermore, MOAEFA method has found a better voltage profile in the allocation of wind turbines in the distribution network compared to the other methods. The performance comparison between MOAEFA method and the previous methods given in the literature verifies the superiority of the MOAEFA method.
KW - Active power loss
KW - Distribution network
KW - Fuzzy decision-making
KW - Multi-objective artificial electric field algorithm
KW - Voltage deviation
KW - Wind turbine
UR - http://www.scopus.com/inward/record.url?scp=85102627008&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2021.107278
DO - 10.1016/j.asoc.2021.107278
M3 - Journal article
AN - SCOPUS:85102627008
SN - 1568-4946
VL - 105
JO - Applied Soft Computing
JF - Applied Soft Computing
M1 - 107278
ER -