Reconfiguration of power systems by applying Tabu search to minimize voltage sag indexes

Garcia-Martinez, S.; Espinosa-Juárez, Elisa

doi:10.1109/naps.2011.6025100

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…Garcia and Espinosa used a TS algorithm to solve the reconfiguration problem in a reduction of voltage sag events presented during one year in a distribution system [101]. Two approaches are performed for analyzing voltage sag events.…”

Section: Tabu Search (Ts)mentioning

confidence: 99%

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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: Tabu Search (Ts)mentioning

confidence: 99%

“…Garcia and Espinosa continued the work presented in [101] by applying an extension in [102]. In this work, the scenario where each bus has a threshold of voltage sag SARFIx is considered, which is the number of sags presented in a bus, group of buses, or the whole system.…”

Section: Tabu Search (Ts)mentioning

confidence: 99%

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

Quintero-Duran

Candelo-Becerra

Sousa

2017

JESTR

View full text Add to dashboard Cite

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“…Many authors have performed distribution network reconfiguration to minimize power loss [3], [4], [13], [5]- [12]. Most researchers have used metaheuristic techniques to reduce the time evaluation by finding good solutions and redirecting the search process to the best-found solutions [14]; however, these algorithms have some convergence problems and the solutions are not always obtained near the optimal [15].…”

Section: Introductionmentioning

confidence: 99%

Distribution Network Reconfiguration with Large Number of Switches Solved by a Modified Binary Bat Algorithm and Improved Seed Population

Quintero-Duran

Candelo-Becerra

2019

Teh. vjesn.

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The paper presents a methodology based on a Modified Binary Bat Algorithm (MBBA) and Improved Seed Population search that provides nearly optimal solutions to the power loss minimization problem, considering network reconfiguration and a large number of switches. The existence of many switches leads to a very large number of combinations, making it hard for algorithms to find a good solution. The proposed method is based on eliminating non-feasible solutions and defining an initial matrix with improved seed population for searching the optimal solution. This seed is used for the random process of the algorithm to produce new solutions and is continually updated to obtain better results close to the optimal solutions found during the searching process of the metaheuristic algorithm. This algorithm was tested against the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and the Seed Population search alone on the modified versions of the IEEE 13-node test and IEEE 123-node test feeders. From several runs, the proposed method reached the optimal solution more times than the other algorithms and the remainder achieved near-optimal solutions. With this result, the MBBA provides good options to improve the solutions in the network reconfiguration problem with a large number of switches.

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“…disturbances that can affect the electrical conditions of power supply and can cause malfunction or damage to equipment and processes [9] [10].…”

mentioning

confidence: 99%

“…A voltage sag is a short duration reduction in RMS voltage at the power frequency for durations from 0.5 cycles to 1 minute. They can be predicted and analyzed by means of stochastic and state estimation methods [9].…”

mentioning

confidence: 99%

Application of Tabu Search for transmission expansion planning considering power quality aspects

Garcia-Martinez

Espinosa-Juárez

Rico-Melgoza

2012

2012 9th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

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In this paper, an optimization process based on the application of the Tabu Search is developed, in order to expand electrical networks by searching the topology that minimizes the voltage sag/year number in the electrical system. A case study is presented, in which a static transmission expansion planning in an IEEE test system is addressed, in order to demonstrate the application of the developed methodology.Keywords-Network expansion, power quality, tabu search, voltage sags (dips). I. INTRODUCTIONThe demand of electricity has been increasing over the years. For this reason, the expansion of electrical networks is necessary, and efficient and reliable construction techniques are required. These techniques must be consistent with the competitive environment of the current electricity market.The objective of the network expansion planning consists in determining an (optimal) expansion plan for the electric network with circuits that satisfy the operational requirements for a forecasted demand growth [1]. Basically, the problem to be addressed is how to minimize the cost of the expansion network, maintaining a certain level of reliability [2]-[6].The network expansion, both at distribution and transmission level, may be studied using static or by dynamic models. A static model tries to answer questions like where and which type of new circuits should be built in an optimal way planning horizon. A dynamic model tries to answer the same questions but, in addition, answers the question of when to add new circuits. In other words, the dynamic model considers several horizons in the same issue [1] [7].On the other hand, in the past, both aspects of operation and planning were in the hands of centralized institutions. Today, the separation of the electricity business has created new challenges in the restructuring industry that must be faced. The restructuring of the electricity industry has resulted in the appearance of new actors, such as traders and independent power producers, which make the expansion planning more difficult [2] [8].Moreover, the electricity market deregulation has led to an increased need for quality indicators, in order to be more competitive and to attract end-users which are demanding higher levels of power quality that is related to electrical

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Reconfiguration of power systems by applying Tabu search to minimize voltage sag indexes

Cited by 4 publications

References 15 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 with Large Number of Switches Solved by a Modified Binary Bat Algorithm and Improved Seed Population

Application of Tabu Search for transmission expansion planning considering power quality aspects

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