Simultaneous Reconfiguration and Optimal Capacitor Placement Using Adaptive Whale Optimization Algorithm for Radial Distribution System

Babu, M. Ramesh; Kumar, Chanchal; Anitha, S.

doi:10.1007/s42835-020-00593-5

Cited by 24 publications

(12 citation statements)

References 26 publications

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“…The basis parameters for the bus-33 system are voltage = 12.66 kV and S(MVA) = 100. Power flow analysis calculates the network's actual power losses, as mentioned in [91]. The COOT algorithm determines the actual loss of power by using three numbers of DGs at various PF to lessen the loss of power at optimal sitting and sizing of the DG.…”

Section: Results and Analysismentioning

confidence: 99%

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Optimal allocation of distributed generation in meshed power networks: A metaheuristic approach

Khan,

Waheed,

Shahzad

et al. 2024

IET Renewable Power Gen

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This paper introduces a novel metaheuristic technique, a COOT‐based algorithm, to determine the optimal Distributed Generation (DG) allocation within a loop‐configured network. This method significantly narrows the optimization gap by leveraging a COOT‐based algorithm, ensuring accelerated convergence and resultant global optima. The core incentive for employing this technique is to substantially mitigate power loss, curtail voltage deviation, and bolster system stability in a loop distribution network. To attain optimal outcomes, the elaborated COOT and improved grey wolf optimization improved grey wolf optimization (IGWO) algorithms were executed on IEEE bus‐33 and 69 mesh distribution networks (MDNs) under varying power factors. The derived mathematical results effectively underscore accomplishing the stipulated objectives: a marked reduction in voltage deviation and power loss coupled with an augmentation in system stability. Notably, at unity, incorporating DGs resulted in a paramount reduction in power loss, attaining a decrease of 78% and 85% for bus‐33 and 69 MDNs, respectively. Moreover, an impressive decrease in power loss by 94% and 98% was observed at the optimal power factor for both MDNs. A comparative evaluation of the results accentuates that the proposed COOT and IGWO algorithms eclipse other documented research in performance, showcasing superior efficiency on a techno‐economic basis.

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Section: Results and Analysismentioning

confidence: 99%

“…The proposed methods have been implemented in the IEEE bus‐33 system to analysis the methods—the complete data of the bus‐33, including line and load data described in [91]. Figure 7 shows the single‐line illustration of the bus‐33 Meshed Network.…”

Section: Results and Analysismentioning

confidence: 99%

Optimal allocation of distributed generation in meshed power networks: A metaheuristic approach

Khan,

Waheed,

Shahzad

et al. 2024

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…Table 2. Proposed DOA's performance summary against other existing optimization techniques Algorithm Ties Switches Capacitor size in kVAr (Location) % Reduction BGSA [21] MFPA [22] AWOA [23] IBPSO [24] Fuzzy-HS [20] MWA [25] Proposed DOA 10, 14, 28, 32, 33 7, 14, 9, 32, 37 33, 34, 35, 36, 25 7, 14, 9, 32, 37 6, 9, 32, 34, 37 33, 34, 35, 36, 25 7, 11, 17, 27, 34 450 (6), 300 (12), 900 (30), 600 (29) 750 (6), 150 (28), 850 ( 29) 400 (24), 250 (25), 150 (30) 900 (2), 300 (4), 300 (15), 300 (23), 300 (25), 600 (31), 600 (32) 450 (11), 900 (5), 150 (19), 150 (29), 150 ( 23) 400 (24), 250 (25), 150 (30) 512 (8), 714 (29)…”

Section: Comparison Of Doa Results With Those Of Other Optimization M...mentioning

confidence: 99%

“…Babu et al [25] presented simultaneous network reconfiguration and capacitor deployment in the distribution system to reduce losses, operational costs, and enhance voltages. During network reconfiguration, the Johnson's technique was employed to determine the smallest spanning tree, and an adaptive whale optimization algorithm was utilized to address the problem.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous network reconfiguration and capacitor allocations using a novel dingo optimization algorithm

Ayanlade

Jimoh

Ogunwole

et al. 2023

IJECE

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<span>Power loss and voltage magnitude fluctuations are two major issues in distribution networks that have drawn a lot of attention. Numerous strategies have been put forward to provide remedies to lessen the undesirable effects of these issues. Combining two of these approaches and dealing with them simultaneously to get more effective outcomes is essential. Therefore, this study hybridizes the network reconfiguration and capacitor allocation strategies using a novel dingo optimization algorithm (DOA) to solve the optimization problems. The optimization problems for simultaneous network reconfiguration and capacitor allocations were formulated and solved using a novel DOA. To demonstrate its effectiveness, DOA’s results were contrasted with those of the other optimization techniques. The methodology was validated on the IEEE 33-bus network and implemented in the MATLAB program. The results demonstrated that the best network reconfiguration was accomplished with switches 7, 11, 17, 27, and 34 open, and buses 8, 29, and 30 were the best places for capacitors with ideal sizes of 512, 714, and 495 kVAr, respectively. The voltage profile was significantly improved, and the power losses were significantly decreased. When compared to some of the different methods, DOA came out on top.</span>

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“…Both were used to reduce the power losses and improve the voltage profle with the use of the Hybrid Big Bang Big Crunch (HBB-BC) algorithm on balanced and unbalanced distribution systems in a fuzzy framework. In order to reduce power losses and regulate voltages within safe ranges, an adaptive whale optimization algorithm (AWOA) is suggested in [31] for the optimal capacitor sizing and placement based on loss sensitivity indices and concurrent distribution network reconfguration. But these capacitors introduce high-harmonic current to the distribution system.…”

Section: Introductionmentioning

confidence: 99%

Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System Using Heap-Based Optimizer

Otuo-Acheampong

Rashed

Akwasi

et al. 2023

International Transactions on Electrical Energy Systems

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A distribution system’s network reconfiguration (NR) is the process of changing the status of the switches to change the topology of the feeders. Using optimal NR at various network load levels, this research proposed an economical way for improving the voltage profile and reducing power loss in distribution systems. A new metaheuristic Heap-based optimizer based on the corporate rank hierarchy is used to solve the optimization problem in order to find the optimal radial distribution network. The objective functions used in this article include voltage profile improvement, power loss reduction, reduction of operation cost, and minimization of gas emissions. This novel technique provides accurate results while avoiding the issue of premature convergence and requires fewer control parameter settings. The proposed method is evaluated at three different load levels on a standard IEEE 33-bus test system, and the simulation results are compared to those of other optimization methods published in the literature, demonstrating that the proposed method improves the system voltage profile while minimizing losses and power costs, establishing that this technique is effective in finding the best result. The Wilcoxon and Friedman tests are also used to verify the effectiveness of the proposed technique.

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Simultaneous Reconfiguration and Optimal Capacitor Placement Using Adaptive Whale Optimization Algorithm for Radial Distribution System

Cited by 24 publications

References 26 publications

Optimal allocation of distributed generation in meshed power networks: A metaheuristic approach

Optimal allocation of distributed generation in meshed power networks: A metaheuristic approach

Simultaneous network reconfiguration and capacitor allocations using a novel dingo optimization algorithm

Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System Using Heap-Based Optimizer

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