Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique

Mahajan, Shreya; Vadhera, Shelly

doi:10.1080/21563306.2018.12002410

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…An improved teaching learning based optimization algorithm [19] is utilised to determine the best placement and size of single and multiple wind turbine generation units while taking into account the objectives of loss minimization, increasing voltage profile, voltage stability, and line load-ability margin. A multiobjective stated problem is considered using a human opinion dynamics optimization approach by optimising voltage profile and lowering total losses through the best allocation of DGs in the distribution network discussed in [20]. The best placement of DGs is determined using a matrix-based radial distribution load flow method, and the best placement of EV loads is determined using a heuristic intelligent search method called Reptile Search Algorithm (RSA) [21].…”

Section: Nomenclature δ Imentioning

confidence: 99%

Optimal Power Dispatch of Multiple DGs Using a Hybrid Algorithm for Mitigating Voltage Deviations and Losses in a Radial Distribution System with Economic Benefits

Sunil

Venkaiah

Kumar

2023

DGAEJ

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In this research, a meta-heuristic-based hybrid algorithm was used to optimize the power dispatch of numerous Distributed Generators (DGs) in a Radial Distribution System (RDS) for hourly fluctuating seasonal loads in order to reduce losses and voltage variations while also saving money. With hourly seasonal load changes, renewable DGs like PV, Wind, and Hybrid (PV+Wind) were used. The HA is proposed in this paper as a way to achieve successful outcomes by merging two meta-heuristic algorithms. The findings of the HA are compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Shuffled Frog Leap Algorithm (SFLA), and Jaya Algorithm (JA) when they are applied to a standard IEEE 33 bus RDS and PG&E 69 bus RDS. According to the test findings simulated in the MATLAB environment, Hybrid Algorithm (HA) beat GA, PSO, SFLA, and JA in terms of optimal power dispatch of numerous DGs to minimise losses and voltage variations, as well as the cost-benefit analysis of renewable DGs energy generation.

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Section: Nomenclature δ Imentioning

confidence: 99%

Optimal Power Dispatch of Multiple DGs Using a Hybrid Algorithm for Mitigating Voltage Deviations and Losses in a Radial Distribution System with Economic Benefits

Sunil

Venkaiah

Kumar

2023

DGAEJ

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“…Multiple-objective particle swarm optimization (MOPSO) in [18] could reach power loss reduction and increase purchasing power. In [19], human opinion dynamics (HOD) has successfully dealt with the IEEE 14-bus and 30-bus distribution systems.…”

Section: Related Workmentioning

confidence: 99%

“…Different values have been set to weight factors of the three objectives, and the three objectives from BBO could not be better than those from other compared methods. In general, studies from [12][13][14][15][16][17][18][19][20][21][22][23] have tried to reduce power loss and operation cost and improve voltage, but they have ignored one important 2 Complexity factor, harmonic distortions. Two components to evaluate harmonics, THD and IHD, have not been considered as constraints or objective functions in the studies.…”

Section: Related Workmentioning

confidence: 99%

Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Nguyen

Pham²,

Kien

et al. 2020

Complexity

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This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. In the considered problem, four single objectives consisting of total power losses, capacity of all PVDGUs, voltage profile index, and harmonic distortions are minimized independently while satisfying branch current limits, voltage limits, and harmonic distortion limits exactly and simultaneously. The performance of the proposed ICOA method has been improved significantly since two improvements were carried out on the two new solution generations of the conventional coyote optimization algorithm (COA). By finding four single objectives from two IEEE distribution power systems with 33 buses and 69 buses, the impact of each proposed improvement and two proposed improvements on the real performance of ICOA has been investigated. ICOA was superior to COA in terms of capability of finding higher quality solutions, more stable search ability, and faster convergence speed. Furthermore, we have also applied five other metaheuristic algorithms consisting of biogeography-based optimization (BBO), genetic algorithm (GA), particle swarm optimization algorithm (PSO), sunflower optimization (SFO), and salp swarm algorithm (SSA) for dealing with the same problem and evaluating further performance of ICOA. The result comparisons have also indicated the outstanding performance of ICOA because it could find much better results than these methods, especially SFO, SSA, and GA. Consequently, the proposed ICOA is a very effective method for finding the optimal location and capacity of PVDGUs in radial distribution power systems.

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Optimal allocation of renewable energy sources in electrical distribution systems based on technical and economic indices

Zellagui

Settoul

Hassan

2022

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

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Optimal Location and Sizing of Distributed Generation Unit Using Human Opinion Dynamics Optimization Technique

Cited by 8 publications

References 8 publications

Optimal Power Dispatch of Multiple DGs Using a Hybrid Algorithm for Mitigating Voltage Deviations and Losses in a Radial Distribution System with Economic Benefits

Optimal Power Dispatch of Multiple DGs Using a Hybrid Algorithm for Mitigating Voltage Deviations and Losses in a Radial Distribution System with Economic Benefits

Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Optimal allocation of renewable energy sources in electrical distribution systems based on technical and economic indices

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