Optimal Allocation/Sizing of DGs/Capacitors in Reconfigured Radial Distribution System Using Quasi-Reflected Slime Mould Algorithm

Biswal, Saubhagya Ranjan; Shankar, Gauri; Elavarasan, Rajvikram Madurai; Mihet‐Popa, Lucian

doi:10.1109/access.2021.3111027

Cited by 27 publications

(2 citation statements)

References 39 publications

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“…Ref. [5] presents an approach that simultaneously emphasizes the optimal location and capacity of capacitor banks, DGs, and reconfiguration of the radial distribution networks. The proposed algorithm is the first utilization of the suggested quasi-reflection-based slime mold algorithm (QRS-MA), tested in three networks.…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm

Mahdavi,

Asadpour,

Macedo

et al. 2023

Energies

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The economic interest in power loss minimization and regulatory requirements regarding voltage levels in distribution systems are considered. In this paper, a computational technique to assist in the optimization of the power losses and voltage characteristic in the steady state through distribution network reconfiguration and the location and size of the distributed generators is addressed. The whale optimization algorithm (WOA) is chosen to perform this task since it can explore the sizeable combinatorial search space of the problem, which is also nonlinear and nonconvex. The purpose of this study is to mitigate power losses; voltage ranges are borne in mind as the problem restrictions. The proposals for solving the issue are evaluated using a specialized power flow algorithm. The algorithm is implemented in MATLAB and the 33-bus and 69-bus grids are employed to assess the performance of the approach. The results indicate that the WOA method outperforms regarding power loss reduction and voltage characteristic improvement in the concurrent integration of distribution network reconfiguration and distributed generators compared with the four metaheuristics shown in the results section.

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Section: Introductionmentioning

confidence: 99%

Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm

Mahdavi,

Asadpour,

Macedo

et al. 2023

Energies

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“…In addition, [35] proposes an optimization technique for determining the ideal placements and sizes of solar and wind generation systems while also managing EVs to assemble an autonomous microgrid. [36] presents quasi-reflection based slime mould algorithm (QRSMA) for solving optimal allocation and sizing problems of capacitors and distribution generations. Moreover, the authors in [37] have discussed optimal allocation of renewable distributed generation (RDG) into distribution systems considering seasonal uncertainties of solar-wind load demands.…”

Section: Introductionmentioning

confidence: 99%

Optimal Planning of Multiple Renewable Energy-Integrated Distribution System With Uncertainties Using Artificial Hummingbird Algorithm

et al. 2022

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Appropriate installation of renewable energy-based distributed generation units (RDGs) is one of the most important challenges and current topics of interest in the optimal functioning of modern power networks. Due to the intermittent nature of renewable energy sources, optimal allocation and sizing of RDGs, particularly photovoltaic (PV) and wind turbine (WT), remains a critical task. Based on a new metaheuristic known as the Artificial hummingbird algorithm (AHA), this paper provides a novel approach for addressing the problem of RDG planning optimization. Considering various operational constraints, the optimization problem is developed with multiple objectives including power loss reduction, voltage stability margin (VSM) enhancement, voltage deviation minimization, and yearly economic savings. Furthermore, using relevant probability distribution functions, the ambiguities related with the stochastic nature of PV and WT output powers are evaluated. The proposed algorithm was compared to two of the recent metaheuristics applied in this domain known as improved harris hawks and particle swarm optimization algorithm (HHO-PSO) and hybrid of phasor particle swarm and gravitational search algorithm (PPSOGSA). The IEEE 33-bus and 69-bus systems are assessed as the test systems in this study. According to the findings, AHA delivers superior solutions and enhances the techno-economic benefits of distribution systems in all the scenarios evaluated.

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Oppositional arithmetic optimization algorithm for network reconfiguration and simultaneous placement of DG and capacitor in radial distribution networks

Dey,

Roy

2024

Int J Numerical Modelling

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The prime objective of this study is the simultaneous network reconfiguration with distributed generation (DG) and capacitor placement in radial distribution networks (RDN) to get the techno and economic benefits for two separate objectives, which are the minimization of actual power loss and annual economic loss as well as a multi objective combining these two single objectives using an oppositional arithmetic optimization algorithm (OAOA). It is an improved version of the currently suggested arithmetic optimization algorithm (AOA) used in the field of engineering for the optimization task. Though the recently developed AOA shows its efficacy in different optimization tasks but to improve the quality of solutions, convergence behavior, and to avoid the local optima, oppositional behavior is added to AOA. The efficacy and exactness of OAOA are tested on three test systems (33‐bus, 69‐bus, and 118‐bus). For the reduction of power loss and annual economic loss as well as the multi objective optimization, two scenarios with different cases are executed using OAOA in RDNs. In scenario 1, the installation of the capacitor (case 1), the installation of unity power factor (UPF) based DG (case 2), and the placement of optimal power factor (OPF) based DG (case 3) have been executed. In scenario 2, allocation of UPF based DG and capacitors simultaneously (case 1), placement of OPF based DG and capacitors simultaneously (case 2) and simultaneous reconfiguration with installation of OPF based DG and capacitor (case 3) has been executed. This recommended OAOA algorithm provides the percentage improvement in real power loss and yearly economic loss for all cases of 33‐bus, and 69‐bus systems (34.28%, 65.50%, 94.43%, 93.26%, 94.89%, and 95.11%), (28.54%, 56.69%, 83.42%, 79.62%, 83.65%, and 83.71%), and (35.51%, 69.16%, 98.10%, 97.52%, 98.22%, and 98.25%), (30.26%, 61.68%, 88.75%, 85.42%, 88.81%, and 88.98%), respectively. The results and comparative study reveal that the OAOA is better than several optimization algorithms in terms of solution quality and good results. This algorithm has a good speed of response and convergence behavior.

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Optimal Allocation/Sizing of DGs/Capacitors in Reconfigured Radial Distribution System Using Quasi-Reflected Slime Mould Algorithm

Cited by 27 publications

References 39 publications

Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm

Reconfiguration of Distribution Networks with Simultaneous Allocation of Distributed Generation Using the Whale Optimization Algorithm

Optimal Planning of Multiple Renewable Energy-Integrated Distribution System With Uncertainties Using Artificial Hummingbird Algorithm

Oppositional arithmetic optimization algorithm for network reconfiguration and simultaneous placement of DG and capacitor in radial distribution networks

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