%0 Journal Article %1 ismail_adeyemi_adeyemo_2022_7180413 %A ADEYEMO, Ismail Adeyemi %A AKINROGUNDE, Oluwadare Olatunde %A SALIMON, Sunday Adeleke %A ADEBIYI, Oluwaseyi Wasiu %D 2022 %J Global Journal of Engineering and Technology Advances %K Adaptive PSO %N 3 %P 077–094 %R 10.30574/gjeta.2022.12.3.0162 %T Adaptive particle swarm optimization approach to simultaneous reconfiguration and shunt capacitor allocation in radial distribution network %U https://gjeta.com/content/adaptive-particle-swarm-optimization-approach-simultaneous-reconfiguration-and-shunt %V 12 %X Simultaneous radial distribution network reconfiguration (RDNR) and shunt capacitor allocation (SCA) is one of the compensation techniques that are used for getting an improved radial structure with reduced real power loss and enhanced voltage stability. This study presents a novel adaptive particle swarm optimisation (APSO) technique for the simultaneous RDNR and SCA, which is a complex and nonlinear optimisation problem. Unlike the conventional particle swarm optimization (PSO) technique in which an initial population of particles is randomly generated, the fundamental loop concept is used to populate the search space of APSO with the candidate branches for each tie switch (open branch) in the loop. The candidate branches are preselected with the graph theory. This is done to mitigate infeasible configurations in the optimization process and also to ensure that the conditions for radiality of the network are satisfied. The effectiveness of the proposed APSO technique for simultaneous RDNR and SCA is demonstrated on the standard IEEE 33-bus and Nigerian Ayepe 34-bus RDNs using six event cases. The efficacy of the proposed APSO technique is further validated with the comparison of the observed simulation results with the reported results of similar work implemented with established algorithms like improved binary particle swarm optimization (IBPSO), modified pollinated flower algorithm (MFPA) and mixed integer linear programming (MILP). The result of the comparative study reveals that the proposed APSO technique outperforms the selected algorithms in most of the considered event cases.

@article{ismail_adeyemi_adeyemo_2022_7180413, abstract = {Simultaneous radial distribution network reconfiguration (RDNR) and shunt capacitor allocation (SCA) is one of the compensation techniques that are used for getting an improved radial structure with reduced real power loss and enhanced voltage stability. This study presents a novel adaptive particle swarm optimisation (APSO) technique for the simultaneous RDNR and SCA, which is a complex and nonlinear optimisation problem. Unlike the conventional particle swarm optimization (PSO) technique in which an initial population of particles is randomly generated, the fundamental loop concept is used to populate the search space of APSO with the candidate branches for each tie switch (open branch) in the loop. The candidate branches are preselected with the graph theory. This is done to mitigate infeasible configurations in the optimization process and also to ensure that the conditions for radiality of the network are satisfied. The effectiveness of the proposed APSO technique for simultaneous RDNR and SCA is demonstrated on the standard IEEE 33-bus and Nigerian Ayepe 34-bus RDNs using six event cases. The efficacy of the proposed APSO technique is further validated with the comparison of the observed simulation results with the reported results of similar work implemented with established algorithms like improved binary particle swarm optimization (IBPSO), modified pollinated flower algorithm (MFPA) and mixed integer linear programming (MILP). The result of the comparative study reveals that the proposed APSO technique outperforms the selected algorithms in most of the considered event cases.}, added-at = {2022-11-15T13:41:20.000+0100}, author = {ADEYEMO, Ismail Adeyemi and AKINROGUNDE, Oluwadare Olatunde and SALIMON, Sunday Adeleke and ADEBIYI, Oluwaseyi Wasiu}, biburl = {https://www.bibsonomy.org/bibtex/2aba21c466d797d20debc3a531294038a/gjetajournal}, doi = {10.30574/gjeta.2022.12.3.0162}, interhash = {745c68200c6a475ded854080e01ee777}, intrahash = {aba21c466d797d20debc3a531294038a}, issn = {2582-5003}, journal = {{Global Journal of Engineering and Technology Advances}}, keywords = {Adaptive PSO}, month = sep, number = 3, pages = {077–094}, timestamp = {2022-11-15T13:41:20.000+0100}, title = {Adaptive particle swarm optimization approach to simultaneous reconfiguration and shunt capacitor allocation in radial distribution network}, url = {https://gjeta.com/content/adaptive-particle-swarm-optimization-approach-simultaneous-reconfiguration-and-shunt}, volume = 12, year = 2022 }