An analysis of the security of multi-area power transmission lines using fuzzy-ACO

Pal, Kirti; Sachan, Sulabh; Gholian-Jouybari, Fatemeh; Hajiaghaei–Keshteli, Mostafa

doi:10.1016/j.eswa.2023.120070

Cited by 9 publications

(2 citation statements)

References 44 publications

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“…Due to its design principle, the ACO algorithm is highly regarded for its ability to solve a variety of combinatorial optimization problems. Pal et al [ 17 ] suggested an ant colony optimization algorithm that incorporates a fuzzy logic-based contingency ranking index for the transmission and contact lines of a multi-region grid; furthermore, an enhanced ant colony algorithm was employed to reduce transmission active and reactive power losses during contingencies, thus augmenting power flow through other transmission lines. A two-tier multi-objective path planning model was proposed by Sui et al [ 18 ] with the objective of minimizing path length and hazard distance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Ant Colony Optimization with Sub-Population and Fuzzy Logic for 3D Laser Scanning Path Planning

Song,

Pu,

2024

Sensors

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For the precise measurement of complex surfaces, determining the position, direction, and path of a laser sensor probe is crucial before obtaining exact measurements. Accurate surface measurement hinges on modifying the overtures of a laser sensor and planning the scan path of the point laser displacement sensor probe to optimize the alignment of its measurement velocity and accuracy. This manuscript proposes a 3D surface laser scanning path planning technique that utilizes adaptive ant colony optimization with sub-population and fuzzy logic (SFACO), which involves the consideration of the measurement point layout, probe attitude, and path planning. Firstly, this study is based on a four-coordinate measuring machine paired with a point laser displacement sensor probe. The laser scanning four-coordinate measuring instrument is used to establish a coordinate system, and the relationship between them is transformed. The readings of each axis of the object being measured under the normal measuring attitude are then reversed through the coordinate system transformation, thus resulting in the optimal measuring attitude. The nominal distance matrix, which demonstrates the significance of the optimal measuring attitude, is then created based on the readings of all the points to be measured. Subsequently, a fuzzy ACO algorithm that integrates multiple swarm adaptive and dynamic domain structures is suggested to enhance the algorithm’s performance by refining and utilizing multiple swarm adaptive and fuzzy operators. The efficacy of the algorithm is verified through experiments with 13 popular TSP benchmark datasets, thereby demonstrating the complexity of the SFACO approach. Ultimately, the path planning problem of surface 3D laser scanning measurement is addressed by employing the proposed SFACO algorithm in conjunction with a nominal distance matrix.

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Section: Introductionmentioning

confidence: 99%

Adaptive Ant Colony Optimization with Sub-Population and Fuzzy Logic for 3D Laser Scanning Path Planning

Song,

Pu,

2024

Sensors

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“…In turn, the proposed algorithm was tested on a 33-node IEEE test network. The ant colony optimisation (ACO) method is also successfully used to optimize active and reactive power losses, the use of which was proposed and tested on a 39-node test network in [274]. Ant colony optimization is also used for optimal scheduling of generating unit overhauls [275] and for improving the optimization of power system operations to reduce generated air pollution [276].…”

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confidence: 99%

Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue

Pijarski,

Belowski

2024

Energies

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The challenges currently faced by network operators are difficult and complex. Presently, various types of energy sources with random generation, energy storage units operating in charging or discharging mode and consumers with different operating characteristics are connected to the power grid. The network is being expanded and modernised. This contributes to the occurrence of various types of network operating states in practice. The appearance of a significant number of objects with random generation in the power system complicates the process of planning and controlling the operation of the power system. It is therefore necessary to constantly search for new methods and algorithms that allow operators to adapt to the changing operating conditions of the power grid. There are many different types of method in the literature, with varying effectiveness, that have been or are used in practice. So far, however, no one ideal, universal method or methodology has been invented that would enable (with equal effectiveness) all problems faced by the power system to be solved. This article presents an overview and a short description of research works available in the literature in which the authors have used modern methods to solve various problems in the field of power engineering. The article is an introduction to the special issue entitled Advances in the Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering. It is an overview of various current problems and the various methods used to solve them, which are used to cope with difficult situations. The authors also pointed out potential research gaps that can be treated as areas for further research.

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Development of a multi-stage, multi-product solid supply chain network design and solution with meta-heuristic algorithms

Rezaei,

Chaharmahali,

Ghandalipour

et al. 2024

Soft Comput

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An analysis of the security of multi-area power transmission lines using fuzzy-ACO

Cited by 9 publications

References 44 publications

Adaptive Ant Colony Optimization with Sub-Population and Fuzzy Logic for 3D Laser Scanning Path Planning

Adaptive Ant Colony Optimization with Sub-Population and Fuzzy Logic for 3D Laser Scanning Path Planning

Application of Methods Based on Artificial Intelligence and Optimisation in Power Engineering—Introduction to the Special Issue

Development of a multi-stage, multi-product solid supply chain network design and solution with meta-heuristic algorithms

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