Comparison of UPFC and SEN Transformer for ATC enhancement in restructured electricity markets

Kumar, Ashwani; Kumar, J. Senthil

doi:10.1016/j.ijepes.2012.03.019

Cited by 40 publications

(18 citation statements)

References 36 publications

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“…8.1.2 Sensitivity of injected power to control variables of TAST/UPFC: Line loading PI sensitivity factors with respect to the control parameters of the TAST and UPFC (magnitude and phase angle of the series injected voltage V T and ∅ T , respectively) can be formulated as follows: c 1 k = ∂PI ∂V T V T = 0 ≡ Sensitivity of PI with respect to V T (18) c 2 k = ∂PI V T ∂∅ T ∅ T = 0 ≡ Sensitivity of PI with respect to ∅ T (19) The sensitivity of PI with respect to the control parameter X k V T and ∅ T of the TAST and the UPFC connected between buses i and j is given by…”

Section: Discussionmentioning

confidence: 99%

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Power flow control capability of the power transistor‐assisted Sen transformer and the unified power flow controller: a close comparison

Mohamed

2020

IET Generation, Transmission & Distribution

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Section: Discussionmentioning

confidence: 99%

“…In [17], the authors have compared the ST and the UPFC when used for congestion management. In [18], the authors have compared the ST and UPFC when used for available transfer capability enhancement. Chanana and Kumar [19] have compared the ST and UPFC on spot price variation of real and reactive power under maximum load-ability condition.…”

Section: Introductionmentioning

confidence: 99%

Power flow control capability of the power transistor‐assisted Sen transformer and the unified power flow controller: a close comparison

Mohamed

2020

IET Generation, Transmission & Distribution

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“…From the literature, ATC computation methods can be classified as follows: (i) AC/DC power transfer distribution factor (PTDF) [1,29,30]; (ii) repeated power flow (RPF) [31,32]; (iii) optimal power flow (OPF) [33];…”

Section: Problem Formulationmentioning

confidence: 99%

Available transfer capability enhancement with FACTS using hybrid PI-PSO

Sadiq¹,

Adamu²,

Buhari³

2019

Turk J Elec Eng & Comp Sci

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In deregulation, growth in electrical loads necessitates improving power delivery, while nondiscriminatory access to transmission grid is a requirement. Deregulation causes a significant rise in transactions, which requires adequate transfer capability to secure economic transactions. In sustainable power delivery, FACTS devices are deployed to enhance available transfer capability (ATC). However, the high investment cost of FACTS makes the problem formulation a multiobjective optimization: power transfer maximization and minimization of FACTS sizes. Furthermore, due to the complexity in optimizing the control variables of voltage source converter types of FACTS, often the solution results in local optima and high computational time. This paper proposes a hybrid of real power flow performance index sensitivity (∂P I) and particle swarm optimization (PI-PSO) to solve the multiobjective optimization of ATC maximization with minimum FACTS sizes using continuation power flow. ∂P I identifies some high-potential locations with enhanced ATC at minimum FACTS size to constitute the PSO's reduced search space. As ∂P I may exhibit masking effects, iterative nexponent and Newton's divided difference approaches are proposed to reduce masking. The proposed PI-PSO is implemented with a thyristor control series compensator and static synchronous series compensator for both bilateral and multilateral transactions. Results show the effectiveness of the proposed PI-PSO over PSO regarding convergence characteristics, avoidance of local optima, and superior ATC values.

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“…The distribution system networks areclassified as primary and secondary distribution system.Also, the well known thing about the distribution system network is that, it's built as interconnected meshed networks, but its structure arranges in the radial or tree structure in the operation.There are many researchers have worked on the index basedmulti-objective function to find the optimal location and size of DG such as [1][2].The Butterfly-particle swarm optimization (Butterfly-PSO or BF-PSO) technique based on the butterfly swarm characteristic behavior, intelligence and search process described in [3][4]). The many approaches for optimal allocation and sizing of DG in distribution systemsare introduced by [5][6][7][12][13].The calculation of available transfer capability (ATC) and the shift factors such as the power transfer distribution factors (PTDF) for the transmission system is discussed in [8][9]. The concepts of the power flow and optimal power flow for the system are described by [10][11].…”

Section: Introductionmentioning

confidence: 99%

The Opf And Butterfly-Pso (Bf-Pso) Technique Based Optimal Location And Sizing Of Distributed Generation In Mesh System

Bohre¹,

Agnihotri²,

Dubey³

2015

ELELIJ

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This paper presents the combined optimal power flow (OPF) and Butterfly-particle swarm optimization (Butterfly-PSO or BF-PSO) techniques to determine the optimal location and sizing of distributed generation (DG). The multi-objective function based on the performance index consider for the multiobjective optimization. The 30-bus mesh system is used for the optimal planning of distributed generation.The comparative result analysis of the proposed methodology and the existing methodology is also reported in this work. The results show that the totalgenerating costand the nodal price are more economical. Also, the reduction in losses (active and reactive power loss) and the improvement in overall performance are efficient.

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Comparison of UPFC and SEN Transformer for ATC enhancement in restructured electricity markets

Cited by 40 publications

References 36 publications

Power flow control capability of the power transistor‐assisted Sen transformer and the unified power flow controller: a close comparison

Power flow control capability of the power transistor‐assisted Sen transformer and the unified power flow controller: a close comparison

Available transfer capability enhancement with FACTS using hybrid PI-PSO

The Opf And Butterfly-Pso (Bf-Pso) Technique Based Optimal Location And Sizing Of Distributed Generation In Mesh System

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