Simultaneous Optimal Placement of DGs and Fixed Capacitor Banks in Radial Distribution Systems using BSA Optimization

Syed, Meera Shareef; Injeti, Satish Kumar

doi:10.5120/18909-0207

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…Furthermore, numerous other artificial intelligencebased optimization algorithms that have been proposed in literature for the simultaneous DG/SC allocation includes ant lion optimization (ALO) [25], biogeography-based optimization (BBO) [26], backtracking search algorithm (BSA) [27,28], bacterial foraging optimization algorithm (BFOA) [29], binary collective animal behavior optimization (BCAO) [30], binary GSA (BGSA) [31], cuckoo search algorithm (CSA) [32], differential evolutionary algorithm (DEA) [33], discrete imperialistic competition algorithm (DICA) [34], intersect mutation differential evolution (IDME) [35], G best -guided artificial bee colony algorithm (GABC) [36], memetic algorithm (MA) [37], symbiotic organisms search (SOS) [38], tabu search (TS) [39], and teaching-learning-based optimization [40].…”

Section: Existing Research and Itsmentioning

confidence: 99%

Parameter-Free Improved Best-Worst Optimizers and Their Application for Simultaneous Distributed Generation and Shunt Capacitors Allocation in Distribution Networks

Leghari

Hussain

Memon

et al. 2022

International Transactions on Electrical Energy Systems

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This paper proposes parameter-free two best-worst optimizers (BWOs) that combine the searching capabilities of Jaya and Rao-1 algorithms to intensify their exploration and exploitation capabilities. For the proposed first optimizer, BWO-1, parallel taxonomy has been adopted for the Jaya and Rao-1 combination to obtain dual sets of updated solutions for a given current solution set. For the proposed second optimizer, BWO-2, along with the parallel taxonomy, a subloop of random scaling factors has been introduced in the solution updating mechanism of both standard Jaya and Rao-1 algorithms to generate multiple sets of updated solutions in a single iteration. The best solutions from obtained multiple solution-sets will survive only and lead to the next iteration. Hence, the proposed solution updating mechanisms for BWO-1 and BWO-2 increase the probability of getting a quality solution under set conditions. The ability and scalability of BWO-1 and BWO-2 were assessed, solving the optimization problem of power loss reduction and voltage deviation minimization in the IEEE 33-bus and 69-bus test systems. The results show that the BWO-2 exhibited a lead of 2.97%, 1.83%, and 0.72% over the Rao-1, Jaya, and BWO-1 techniques, respectively. Besides, the BWO-2 achieves up to 38.76% more reduction in power losses against the existing standard, improved, and hybrid optimization techniques.

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Section: Existing Research and Itsmentioning

confidence: 99%

Parameter-Free Improved Best-Worst Optimizers and Their Application for Simultaneous Distributed Generation and Shunt Capacitors Allocation in Distribution Networks

Leghari

Hussain

Memon

et al. 2022

International Transactions on Electrical Energy Systems

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“…Authors in [35] developed a new hybrid optimization approach based on Artificial Bee Colony (ABC) and Artificial Immune System (AIS) to find the optimal sitting and sizing of DG and SC. In another similar study, the authors suggested a method based on Backtracking Search Algorithm (BSA) to solve the problem of the optimal location of both DG and static capacitor banks for enhance voltage profile and decrease the power loss of distribution system [36].…”

Section: B Literature Reviewmentioning

confidence: 99%

A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

et al. 2020

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Controlling active/reactive power in distribution systems has a great impact on its performance. The placement of distributed generators (DGs) and shunt capacitors (SCs) are the most popular mechanisms to improve the distribution system performance. In this line, this paper proposes an enhanced genetic algorithm (EGA) that combines the merits of genetic algorithm and local search to find the optimal placement and capacity of the simultaneous allocation of DGs/SCs in the radial systems. Incorporating local search scheme enhances the search space capability and increases the exploration rate for finding the global solution. The proposed procedure aims at minimizing both total real power losses and the total voltage deviation in order to enhance the distribution system performance. To prove the proposed algorithm ability and scalability, three standard test systems, IEEE 33 bus, 69 bus, and 119-bus test distribution networks, are considered. The simulation results show that the proposed EGA can efficiently search for the optimal solutions of the problem and outperforms the other existing algorithms in the literature. Moreover, an economic based cost analysis is provided for light, shoulder and heavy loading levels. It was proven, the proposed EGA leads to significant improvements in the technical and economic points of view.

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“…It aimed to provide technical, economical, and environmental advantages by using various objective functions (increasing power losses, voltage deviation, energy cost, and gas emissions) with the proposed algorithm. In [23], the Backtracking Search Algorithm (BSA) was used to resolve the integration of DGs and CBs problem. The proposed algorithm results were compared with the GA/PSO, ICA/GA, and AA algorithms in the literature.…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Distributed Generations and Capacitor Banks in Distribution Systems Using Arithmetic Optimization Algorithm

Pamuk,

Uzun

2024

Applied Sciences

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In this paper, an optimization approach based on an arithmetic optimization algorithm (AOA) is proposed for specifying the optimal allocation of distribution generations/generators (DGs) and capacitor banks (CBs) in radial distribution systems. The AOA is a new population-based meta-heuristic algorithm that is essentially based on using basic arithmetic operators in mathematics. The proposed approach is employed to specify the optimum placement, capacity, and power factor of DGs and CBs to decrease the distribution systems’ total power loss and voltage deviation. To state the performance of the proposed approach, DGs and CBs are placed in IEEE 33-bus and 69-bus systems separately or together. When only DGs are used and the parameters of location, capacity, and power factor of DGs are determined simultaneously, the total active power loss reductions in the IEEE 33-bus and 69-bus systems are achieved at 94.42% and 98.03%, respectively. When the results of other optimization algorithms are examined, it is seen that better results are obtained with AOA.

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Simultaneous Optimal Placement of DGs and Fixed Capacitor Banks in Radial Distribution Systems using BSA Optimization

Cited by 9 publications

References 21 publications

Parameter-Free Improved Best-Worst Optimizers and Their Application for Simultaneous Distributed Generation and Shunt Capacitors Allocation in Distribution Networks

Parameter-Free Improved Best-Worst Optimizers and Their Application for Simultaneous Distributed Generation and Shunt Capacitors Allocation in Distribution Networks

A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

Optimal Allocation of Distributed Generations and Capacitor Banks in Distribution Systems Using Arithmetic Optimization Algorithm

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