Optimal DG allocation for enhancing voltage stability and minimizing power loss using hybrid gray wolf optimizer

Kamel, Salah; Awad, Ayman; Abdel-Mawgoud, Hussein

doi:10.3906/elk-1805-66

Cited by 36 publications

(13 citation statements)

References 18 publications

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“…The annual cost of energy occurs at the end of the year and, therefore, it has to be accumulated to present value by using the capital recovery factor β as shown in Eq. (16). β is calculated as shown in Eq.…”

Section: Methods Of Economic Assessmentmentioning

confidence: 99%

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Analysis of Optimal Deployment of Several DGs in Distribution Networks Using Plant Propagation Algorithm

et al. 2020

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In recent years, the substantial upsurge of electricity demand has directly impacted the performance of the distribution networks concerning the active power losses and voltage drops. In such circumstances, the distributed generators (DGs) could uphold these concerns if they are optimally deployed in terms of sizing and placement. For this reason, in current research, the optimal deployment of DGs has been proposed with the plant propagation algorithm (PPA) to simultaneously maximize the total active power loss reduction and to upgrade the magnitude of the minimum bus voltage. Alongside, the authors have examined four rounds of DGs. In that context, the optimal deployment of one DG is investigated in the first round. In each succeeding round, the number of DGs is increased: in the second round, this investigation is carried out for two DGs, for three DGs in the third round, and finally, for four DGs in the fourth round of the investigation. The effectiveness of the proposed PPA has been tested on IEEE 33 and 69-bus test networks in the load flow analysis, and results are compared with the standard optimization algorithms. Thereafter, a post deployment economic assessment based on loss calculation has been undertaken out as well. The ANOVA test has also been performed for statistical evaluation of standard algorithms. The simulation results exhibit that the proposed algorithm outdo other algorithms both technically and economically. It has been seen that as the deployment of DGs is increased, the total active power losses and voltage drops are also reduced. In terms of economic assessments, the total cost decreases with the increased deployment of DGs in IEEE 33-bus test network, whereas, the total cost increases with the increased deployment of DGs in IEEE 69-bus test network. INDEX TERMS Distributed generators, load flow analysis, sizing and placement of DGs, total active power losses, voltage drops, test networks, plant propagation algorithm (PPA).

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Section: Methods Of Economic Assessmentmentioning

confidence: 99%

“…In [15], the authors have implemented CSFS optimizer to find numbers, sizes, and sites of multiple DGs. In [16], a GWO is proposed for the allocation of one to two DGs to cater voltage stability and losses. The authors in [17], have introduced an EMA for the sizing and siting of both one and two DGs in the abovementioned test networks.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Optimal Deployment of Several DGs in Distribution Networks Using Plant Propagation Algorithm

et al. 2020

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“…The ranked up to 50% PLSF values of nodes can be regarded as candidate nodes for optimal integration of PV and BESs in DS [26][27][28][29]. In this study, 34 and 58 nodes have been selected as candidate buses for 69-node and 118-node test systems, respectively.…”

Section: Plsfmentioning

confidence: 99%

Optimal planning DG and BES units in distribution system considering uncertainty of power generation and time-varying load

Khasanov¹,

Kamel²,

Awad³

et al. 2021

Turk J Elec Eng & Comp Sci

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Global environmental problems associated with traditional energy generation have led to a rapid increase in the use of renewable energy sources (RES) in power systems. The integration of renewable energy technologies is commercially available nowadays, and the most common of such RES technology is photovoltaic (PV). This paper proposes an application of hybrid teaching-learning and artificial bee colony (TLABC) technique for determining the optimal allocation of PV based distributed generation (DG) and battery energy storage (BES) units in the distribution system (DS) with the aim of minimizing the total power losses. Besides, some potential nodes identified by the Power Loss Sensitivity Factor (PLSF). Thereupon TLABC is applied to determine the location of the DG and its size from the candidate nodes. The Beta probability distribution function (PDF) is employed to characterize the randomness of solar radiation. High penetration of RES can lead to a high level of risk in DS stability. To maintain system stability, BES is considered to smooth out the fluctuations and improve supply continuity. The benefits of using BES is mainly dependent on operational strategies related to PV and storage in DS. The performance of the developed approach is tested on the 69 node and 118 node DSs and compared with the Differential Evolution (DE) algorithm, Genetic Algorithm (GA), for a fair comparison. Besides, the developed approach compared with other methods in literature which are solved the same problem. The results show how practical is the developed approach compared with other techniques.

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“…To validate the obtained results, a comparison is carried out with four other methods, which are the hybrid gray wolf optimizer method [28], the fast approach ELF [10], one analytical method [27], and the PSO technique [29]. As represented in Table 2, all methods point to the same DG location (bus 6), except for the PSO technique in the case of the 4th DG type that yields bus 30.…”

Section: Comparative Studymentioning

confidence: 99%

Multiple distributed generations placement and sizing based on voltage stabilityindex and power loss minimization

Garfi¹,

Aloui²

2019

Turk J Elec Eng & Comp Sci

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This paper proposes a rapid analytical method to determine the locations and sizes of multiple distributed generations (DGs) inside a distribution network. DGs' locations are chosen with the aim of enhancing voltage stability and their sizes are picked so as to minimize system power losses. To evaluate the effect of the DG's nature on the system's performance, the proposed DG allocation method is tested for all DG types and the impact of the combination of different types of DGs is equally investigated, which offers a guide to designing an optimal hybrid network.

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Optimal DG allocation for enhancing voltage stability and minimizing power loss using hybrid gray wolf optimizer

Cited by 36 publications

References 18 publications

Analysis of Optimal Deployment of Several DGs in Distribution Networks Using Plant Propagation Algorithm

Analysis of Optimal Deployment of Several DGs in Distribution Networks Using Plant Propagation Algorithm

Optimal planning DG and BES units in distribution system considering uncertainty of power generation and time-varying load

Multiple distributed generations placement and sizing based on voltage stabilityindex and power loss minimization

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