Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation

Niknam, Taher; Kavousi‐Fard, Abdollah; Aghaei, Jamshid

doi:10.1049/iet-rpg.2011.0256

Cited by 128 publications

(102 citation statements)

References 24 publications

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“…Other studies were performed by Niknam et al [30] to work out several scenarios, taking into account the uncertainty of wind speed, power injection by wind turbines, and varying both active and reactive loads. A WeibullGaussian probabilistic distribution function was used to identify the scenarios stochastically.…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

Quintero-Duran

Candelo-Becerra

Sousa

2017

JESTR

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Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topic.

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Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

Quintero-Duran

Candelo-Becerra

Sousa

2017

JESTR

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“…Active loss reduction [1][2], load equalization and power restoration optimization are currently the most popular technical methods for distribution network reconfiguration, the main objective of which is loss reduction. Regarding optimization algorithms, the differential evolution algorithm [3][4], particle swarm algorithm [5], genetic algorithm [6] and so on [7] have been widely applied. A reconfiguration algorithm of a distribution network based on an improved shuffled frog leaping algorithm is proposed in this paper.…”

Section: Introductionmentioning

confidence: 99%

Distribution Network Reconfiguration Method with Distributed Generators Based on an Improved Shuffled Frog Leaping Algorithm

Xiang¹,

Wu²,

Chen³

et al. 2018

EasyChair Preprints

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Abstract-Reconstruction of a distribution network is a complex nonlinear combinatorial optimization problem. A reconfiguration algorithm of a distribution network based on an improved shuffled frog leaping algorithm using molecular dynamics theory and cloud simulation theory was proposed to solve the problems of slow convergence for current distribution network reconfiguration method. The reconstruction optimization process of the distribution network was as follows. First, the integer coding strategy based on the independent loop was adopted, and the initial data of distribution network was input, followed by random generation of the effective initial swarm of corresponding scale; Second, the distribution network was simplified, and the effective solution was obtained based on the reconfiguration network simplification principle; Third, the back forward sweep algorithm method for was used for the power flow calculation of effective solutions; Finally, iterative swarm optimization was conducted based on the improved shuffled frog leaping algorithm(SFLA). The simulation results based on the IEEE33 node distribution system showed that the active network loss value of the system was decreased obviously, reaching 16.57%. The active power P increased significantly compared with that before the reconfiguration in which the distributed generators (DGs) were accessed. The proposed algorithm has good optimization performance in solving the problem of distribution network reconfiguration compared with the traditional particle swarm optimization (PSO) and the differential evolution algorithm (DE).Index Terms-Distributed generator, distribution network, reconfiguration algorithm, improved shuffled frog leaping algorithm.

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“…From a theoretical perspective, a network reconfiguration is an optimisation problem which may have different objective functions, such as minimum switching operations, minimum power loss, balanced feeder load balancing, or their combination [3][4][5][6][7][8][9] to comply with a set of operational constraints such as bus bar voltage limits, line or cable capacity ratings and fault levels. Generally these methods can be grouped into several categories; classic optimization technique [10][11][12][13], sensitivities analysis method [14], knowledge-based heuristic method [15][16][17][18], and Genetic Algorithms [19].…”

Section: Introductionmentioning

confidence: 99%

Distribution network reconfiguration validation with uncertain loads – network configuration determination and application

Bai

Mavrocostanti

Strickland

et al. 2016

IET Generation, Transmission & Distribution

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Automatic load transfer (ALT) on the 11kV network is the process by which circuit breakers on the network are switched to form open points in order to feed load from different primary substations. Some of the potential benefits that may be gained from dynamically using ALT include maximising utilisation of existing assets, voltage regulation and reduced losses. One of the key issues, that has yet to be properly addressed in published research, is how to validate that the modelled benefits really exist. On an 11kV distribution network where the load is continually changing and the load on each distribution substation is unlikely to be monitored -reduction in losses from moving the normally open point is particularly difficult to prove. This paper proposes a method to overcome this problem and uses measured primary feeder data from two parts of the Western Power Distribution 11kV Network under different configurations. The process of choosing the different configurations is based on a heuristic modelling method of locating minimum voltages to help reduce losses.

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Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation

Cited by 128 publications

References 24 publications

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

Distribution Network Reconfiguration Method with Distributed Generators Based on an Improved Shuffled Frog Leaping Algorithm

Distribution network reconfiguration validation with uncertain loads – network configuration determination and application

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