Combination of Genetic Algorithm and Ant Colony Algorithm for Distribution Network Planning

Dong, Yongfeng; Gu, Jun; Li, Nana; Hou, Xiangdan; Yan, Weili

doi:10.1109/icmlc.2007.4370288

Cited by 23 publications

(6 citation statements)

References 2 publications

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“…Nevertheless, the reported numerical results satisfy the planning requirements. The authors of [67] recommended utilizing a genetic algorithm and an ant-colony optimizer to create distribution networks for medium-voltage applications. The methodology is tested on a small test feeder with 10 nodes, accounting for different diameter sizes.…”

Section: Application Of Heuristic Methods On Ac MV Gridsmentioning

confidence: 99%

Modern Techniques for the Optimal Power Flow Problem: State of the Art

2022

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Due to its significance in the operation of power systems, the optimal power flow (OPF) problem has attracted increasing interest with the introduction of smart grids. Optimal power flow developed as a crucial instrument for resource planning effectiveness as well as for enhancing the performance of electrical power networks. Transmission line losses, total generation costs, FACTS (flexible alternating current transmission system) costs, voltage deviations, total power transfer capability, voltage stability, emission of generation units, system security, etc., are just a few examples of objective functions related to the electric power system that can be optimized. Due to the nonlinear nature of optimal power flow problems, the classical approaches may become locked in local optimums, hence, metaheuristic optimization techniques are frequently used to solve these issues. The most recent optimization strategies used to solve optimal power flow problems are discussed in this paper as the state of the art (according to the authors, the most pertinent studies). The presented optimization techniques are grouped according to their sources of inspiration, including human-inspired algorithms (harmony search, teaching learning-based optimization, tabu search, etc.), evolutionary-inspired algorithms (differential evolution, genetic algorithms, etc.), and physics-inspired methods (particle swarm optimization, cuckoo search algorithm, firefly algorithm, ant colony optimization algorithm, etc.).

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Section: Application Of Heuristic Methods On Ac MV Gridsmentioning

confidence: 99%

Modern Techniques for the Optimal Power Flow Problem: State of the Art

2022

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“…The reported numerical results satisfy the planning requirements; however, the authors did not compare with other optimization methodologies based on metaheuristics or exact models, and the optimization model does not include different caliber options, which reduces the complexity owing to the reduction in the solution space size. In [7], the authors proposed a combination of a genetic algorithm with an ant-colony optimizer to plan distribution networks in medium-voltage applications. The evaluation of the methodology considers different caliber sizes in a small test feeder comprising 10 nodes; however, no comparison with exact or metaheuristic approaches was provided to demonstrate the efficiency of the methodology.…”

Section: Introductionmentioning

confidence: 99%

Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids

et al. 2021

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The optimal expansion of AC medium-voltage distribution grids for rural applications is addressed in this study from a heuristic perspective. The optimal routes of a distribution feeder are selected by applying the concept of a minimum spanning tree by limiting the number of branches that are connected to a substation (mixed-integer linear programming formulation). In order to choose the caliber of the conductors for the selected feeder routes, the maximum expected current that is absorbed by the loads is calculated, thereby defining the minimum thermal bound of the conductor caliber. With the topology and the initial selection of the conductors, a tabu search algorithm (TSA) is implemented to refine the solution with the help of a three-phase power flow simulation in MATLAB for three different load conditions, i.e., maximum, medium, and minimum consumption with values of 100%, 60%, and 30%, respectively. This helps in calculating the annual costs of the energy losses that will be summed with the investment cost in conductors for determining the final costs of the planning project. Numerical simulations in two test feeders comprising 9 and 25 nodes with one substation show the effectiveness of the proposed methodology regarding the final grid planning cost; in addition, the heuristic selection of the calibers using the minimum expected current absorbed by the loads provides at least 70% of the calibers that are contained in the final solution of the problem. This demonstrates the importance of using adequate starting points to potentiate metaheuristic optimizers such as the TSA.

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“…The one is consummating the algorithm with the improved arithmetic operators or combination other heuristic algorithm. In this way, the adaptability of the algorithm can be improved and the premature convergence can be avoid to a certain extent [2][3][4]. The other is the application for some fields.…”

Section: Introductionmentioning

confidence: 99%

A New Elimination Ant Colony Algorithm for Process Task Distribution

Zhai

2010

2010 International Conference on Management and Service Science

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Task distribution is an important part of process design and affects the cycle of process design. To shorten the design cycle, a distribution method based on part features is prompt by converting task distribution problem to a capacity matrix. For improving algorithm efficiency, an artificial ant model is built with blackboard strategy. This model enhances the communication between ants and environments. Upon this model, the elimination ant colony algorithm is given according to the capacity matrix. Experiments show that the new algorithm, compared with traditional algorithm, leads less iterative steps and better solution.

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Combination of Genetic Algorithm and Ant Colony Algorithm for Distribution Network Planning

Cited by 23 publications

References 2 publications

Modern Techniques for the Optimal Power Flow Problem: State of the Art

Modern Techniques for the Optimal Power Flow Problem: State of the Art

Heuristic Methodology for Planning AC Rural Medium-Voltage Distribution Grids

A New Elimination Ant Colony Algorithm for Process Task Distribution

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