Optimal placement of multi-type facts controllers using real coded genetic algorithm

Shah, Ishit; Srivastava, Neha; Sarda, Jigar

doi:10.1109/iceeot.2016.7755627

Cited by 9 publications

(3 citation statements)

References 4 publications

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“…The simulations results have been obtained for the IEEE-30 bus network showed the applicability of this applied technique. RCGA was utilized by [100] to know the proper placements of TCSC, SVC and UPFC for reducing the transmission losses in the IEEE 30-bus test system. However, in [101], The proper location of FACTS devices has been based on practical considerations, such as the estimated annual load curve in order to increase the accuracy of this placement.…”

Section: Summary Of Meta Heuristic Methods Related To Facts Devices O...mentioning

confidence: 99%

Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods

Ismail¹,

Guesmi²,

Alshammari³

et al. 2023

Preprint

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Using flexible AC transmission system (FACTS) devices in power systems while adhering to some equality and inequality constraints, researchers around the world sought to address this issue with the objectives of improving the voltage profile, reducing power losses in transmission lines, and increasing system reliability and safety. The recent development of FACTS controllers opens up new perspectives for safer and more efficient operation of electrical power networks by continuous and rapid action on power systems parameters, such as phase angle shifting, voltage injection and line impedance compensation. Thus, an improvement on voltage profile and enhancement of power transfer capability can be obtained. It is for that, the idea behind the FACTS concept is to enable the transmission system to be an active element in increasing the flexibility of power transfer requirements and in securing stability of integrated power system. It may also be effective in transient stability improvement, power oscillations damping and balancing power flow in parallel lines. The primary issue that has significantly piqued the interest of a number of researchers working in this field is the FACTS optimization problem, which involves determining the optimal type, location, and size of FACTS devices in electrical power systems. For solving this mixed integer, nonlinear and non-convex optimization problem, this paper provides an in-depth and comprehensive review of the various optimization techniques covered in published works in the field. In this review, a classification of optimization techniques in five main groups that are widely used, such as classical optimization techniques or conventional optimization approaches, Meta heuristic methods, analytic methods or sensitive index methods and mixed or hybrid methods, is summarized. In addition, a performance descriptions and comparison of these different optimization techniques are discussed in this study. Finally, some advice is offered for future research in this field.

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Section: Summary Of Meta Heuristic Methods Related To Facts Devices O...mentioning

confidence: 99%

Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods

Ismail¹,

Guesmi²,

Alshammari³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The simulation results obtained for the IEEE 30-bus network showed the applicability of this technique. An RCGA was utilized by [100] to determine the proper placements of TCSC, SVC, and UPFC for reducing the transmission losses in the IEEE 30-bus test system. However, in ref.…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods

et al. 2023

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The use of FACTS devices in power systems has become increasingly popular in recent years, as they offer a number of benefits, including improved voltage profile, reduced power losses, and increased system reliability and safety. However, determining the optimal type, location, and size of FACTS devices can be a challenging optimization problem, as it involves mixed integer, nonlinear, and nonconvex constraints. To address this issue, researchers have applied various optimization techniques to determine the optimal configuration of FACTS devices in power systems. The paper provides an in-depth and comprehensive review of the various optimization techniques that have been used in published works in this field. The review classifies the optimization techniques into four main groups: classical optimization techniques, metaheuristic methods, analytic methods, and mixed or hybrid methods. Classical optimization techniques are conventional optimization approaches that are widely used in optimization problems. Metaheuristic methods are stochastic search algorithms that can be effective for nonconvex constraints. Analytic methods involve sensitivity analysis and gradient-based optimization techniques. Mixed or hybrid methods combine different optimization techniques to improve the solution quality. The paper also provides a performance comparison of these different optimization techniques, which can be useful in selecting an appropriate method for a specific problem. Finally, the paper offers some advice for future research in this field, such as developing new optimization techniques that can handle the complexity of the optimization problem and incorporating uncertainties into the optimization model. Overall, the paper provides a valuable resource for researchers and practitioners in the field of power systems optimization, as it summarizes the various optimization techniques that have been used to solve the FACTS optimization problem and provides insights into their performance and applicability.

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“…Shah has used real coded genetic algorithms to place several types of FACTS such as: UPFC, Static Var Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC) into the IEEE-30 network. These have made possible to increase the power flow capacity of the lines [7]. E. Ghahremani has developed a Genetic Algorithm (GA) based approch to select nodes for simultaneous placement of UPFCs, SVCs, TCSCs and Thyristor Controlled Voltage Regulator (TCVR) in a 57node transmission network [8].…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement of an Unified Power Flow Controller in a Transmission Network by Unified Non Dominated Sorting Genetic Algorithm-III and Differential Evolution Algorithm

Oloulade¹,

Adolphe²,

François-Xavier³

et al. 2019

IJECEC

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The interconnected transmission network of the Benin Electric Community (CEB) presents excessive losses that will increase further by 2025 and severely degrade the power quality supplying. This paper presents the quarto-criterion optimization of the positioning of a UPFC in the CEB's HTB network by U-NSGA III and DE. The positioning of an UPFC on line 3 and node 6 of this network has qualitatively improved the technical performance of this transmission network with an optimal installation cost of US $ 13126657.03. The hypervolumes of the two calculated methods showed that the U-NSGA-III is more accurate in terms of trend toward global solutions than DE. These convincing results confirm the performance of the U-NSGA-III method compared to the DE which also resulted in results close to those obtained by the U-NSGA-III with more or less narrow difference.

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Optimal placement of multi-type facts controllers using real coded genetic algorithm

Cited by 9 publications

References 4 publications

Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods

Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods

Optimized FACTS Devices for Power System Enhancement: Applications and Solving Methods

Optimal Placement of an Unified Power Flow Controller in a Transmission Network by Unified Non Dominated Sorting Genetic Algorithm-III and Differential Evolution Algorithm

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