A modified particle swarm optimization algorithm and its application in optimal power flow problem

Wang, Cuiru; Yuan, Hejin; Huang, Zhiqiang; Zhang, Jiang-wei; Sun, Chenjun

doi:10.1109/icmlc.2005.1527435

Cited by 26 publications

(5 citation statements)

References 7 publications

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“…The conventional PSO has been improved by introducing a biological notion of the passive congregation. A modified PSO has been proposed in [49] to resolve the OPF issues. Particles in this modified PSO increase the possibility of finding the global solution while decreasing the particles' initial positions effect.…”

Section: Optimal Power Flow For Transmission Power Systemsmentioning

confidence: 99%

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

et al. 2023

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Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field.

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Section: Optimal Power Flow For Transmission Power Systemsmentioning

confidence: 99%

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

et al. 2023

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“…The MathWorks Matlab platform was used to implement the methodology described in the following subsection. The implemented solution technique uses PSO, where a maximum population of fifty species has been defined, with a maximum of ten iterations for reproduction and a penalty of 10 12 , this methodology was used in similar works to perform the PF (Cui-Ru Wang et al, 2005) and SC (Baghaee et al, 2011) calculation ,just like these parameters (Ferraz et al, 2019).…”

Section: Optimization Processmentioning

confidence: 99%

Use of the Particle Swarm Technique to Optimize Parameters of Photovoltaic Generators on Networks with High Integration of Distributed Generation

Tonini

Silva

Ferraz

et al. 2020

Anais Do Simpósio Brasileiro De Sistemas Elétricos 2020

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In search of greater diversity in energy sources, to meet the demand of the electricity power, the use of photovoltaic generators is increasing. Such components have their power generation specified by IEEE 1547/2018, which limits the power parameters of each one. In a situation of high penetration of distributed generation, generators can contribute to the electric current that will circulate within the system in case of a fault, causing major disruption to the mesh and the users. Seeking to reduce this impact, the paper will minimize the value of the short circuit current by adjusting the parameters of the photovoltaic generators. The analysis will be done on IEEE Test Feeder 13 and 34 nodes and will refer to generators from category A, B and without reactive power injection in the mesh.

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“…Particle swarm optimization. The computational flow of PSO technique can be described in the following steps [7].…”

Section: Optimal Power Flowmentioning

confidence: 99%

Enhanced OPF for DG Penetrated Power System Network under Variable Load Conditions

Sivakumar¹,

Rajapandiyan²

2014

AMR

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In modern power systems, distributed generation turns out to be progressively significant. Conversely, the growing utilize of distributed generators origins the concerns on the growing system hazard owing to their probable breakdown or unruly power productivity based on such renewable energy sources as wind and the sun. Power contribution at the required proportion by the grids is the chief performance consideration which depends upon the penetration of distributed generation and the accessibility of conventional sources during the load transform. In this paper, the projected approach is that the essential load power is divided evenly between the grids composed of Distributed Generation (DG) units and the utility based on the PSO algorithm during the load transform. A case study is carried out based on the New England test system (10-Generator-39-Bus) as a standard by using Particle swarm optimization (PSO) algorithm.

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A modified particle swarm optimization algorithm and its application in optimal power flow problem

Cited by 26 publications

References 7 publications

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Review of Metaheuristic Optimization Algorithms for Power Systems Problems

Use of the Particle Swarm Technique to Optimize Parameters of Photovoltaic Generators on Networks with High Integration of Distributed Generation

Enhanced OPF for DG Penetrated Power System Network under Variable Load Conditions

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