Optimal Placement and Control of Unified Power Flow Control devices using Evolutionary Computing and Sequential Quadratic Programming

Kalyani, R.P.; Crow, M.L.; Tauritz, Daniel R.

doi:10.1109/psce.2006.296442

Cited by 13 publications

(12 citation statements)

References 6 publications

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“…† Method II was proposed by Shaheen et al [19] and used to determine optimal operation of UPFC in order to minimise the active power loss of a system. † Method III uses the sequential quadratic programming [21] to determine the optimal settings of UPFC for the enhancement of line loading condition during post-contingency.…”

Section: Methods Comparisonmentioning

confidence: 99%

Optimal unified power flow controller application to enhance total transfer capability

Rajabi-Ghahnavieh

Fotuhi‐Firuzabad²,

Othman

2015

IET Generation, Transmission & Distribution

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For a power transfer path, total transfer capability (TTC) represents maximum power that can be transferred over the transmission system. Unified power flow controller (UPFC) is a device that can be used to increase in TTC. This study presents a new method for optimal UPFC application to minimise power loss while enhancing TTC. Based on UPFC injection model, the solution region of UPFC parameters is first found using the proposed method to maximise TTC. It then searches the solution region to find optimal UPFC control mode and setting to minimise system power loss. The proposed method is applied to the IEEE-Reliability Test System and the UPFC application impact are evaluated. Comparative studies are conducted between the TTC results obtained by the proposed method with those obtained using the existing approaches.Nomenclature P PI , P SI active power of parallel and series inverters Q PI , Q SI reactive power of parallel and series inverters P P , Q P active and reactive power injection at PB P PB , P SB active power at PB and SB buses Q PB , Q SB reactive power at PB and SB buses V d UPFC series injected voltage with magnitude and phase angle V d of and θ d V PB PB bus voltage with magnitude and phase angle of V PB and θ PB V SB SB bus voltage with magnitude and phase angle of V SB and θ SB V PI voltage of parallel inverter with magnitude and phase angle of V PI and θ PI V SI voltage of series inverter with magnitude and phase angle of V SI and θ SI I SI , I PI current of the series and parallel inverter I PB , I SB current of PB and SB X PT , X ST reactance of parallel and series transformers V Max I maximum output voltage of the inverters I Max I maximum output current of the inverters S Max

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Section: Methods Comparisonmentioning

confidence: 99%

Optimal unified power flow controller application to enhance total transfer capability

Rajabi-Ghahnavieh

Fotuhi‐Firuzabad²,

Othman

2015

IET Generation, Transmission & Distribution

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“…A Gravitational Optimization (GO) algorithm has been addressed for allocation of SVC in a power system in [85]. Kalyani et al [86] has been suggested an Evolutionary algorithm for optimal location of UPFC and sequential quadratic programming (SQP) to optimize the UPFC control settings. In [178], a knowledge and algorithm based approach is used to VAR planning in a transmission system.…”

Section: Fuzzy Logic (Fl) Algorithmsmentioning

confidence: 99%

“…There are several methods proposed in literatures [3]- [86], [157]- [180], [201], for placement of FACTS controllers in multi-machine power systems from different operating conditions viewpoint. References [3]- [5], classify three broad categories such as a sensitivity based methods, optimization based method, and artificial intelligence based techniques for placement of FACTS controllers from different operating conditions viewpoint in multi-machine power systems.…”

Section: Introductionmentioning

confidence: 99%

“…The various artificial intelligence (AI) based methods proposed in literature includes genetic algorithms (GA) [49]- [64], [175]- [176], [180], tabu search algorithms [65], [66], simulated annealing (SA) based approach [69]- [70], [177], particle swarm optimization (PSO) techniques [71]- [73], [80], artificial neural network (ANN) based algorithms [74]- [76], ant colony optimization (ACO) algorithms [77]- [78], graph search algorithms [79], fuzzy logic based approach [81]- [82], other techniques such as norm forms of diffeomorphism techniques [83], evolution strategies algorithms [84], [86], improved evolutionary programming [68], gravitational optimization techniques [85], benders decomposition techniques [42], augmented Lagrange multiplier approach [67], hybrid meta-heuristic approach [172], heuristic and algorithmic approach [178], energy approach [179].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Comprehensive Survey of Optimal Placement and Coordinated Control Techniques of FACTS Controllers in Multi-Machine Power System Environments

Singh¹,

Sharma²,

Tiwari³

2010

Journal of Electrical Engineering and Technology

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-This paper presents exhaustive review of various methods/techniques for coordinated control between FACTS controllers in multi-machine power systems. It also reviews various techniques/methods for optimal choice and allocation of FACTS controllers. Authors strongly believe that this survey article will be very much useful to the researchers for finding out the relevant references in the field of placement and coordination of FACTS Controllers.

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“…This process is repeated until the most promising locations are identified. Reference [4] proposed the combination of Evolutionary Algorithm (EA) to find the optimal location and Sequential Quadratic Programming (SQP) to optimize the UPFC parameters. In [5]- [7], the Genetic Algorithm (GA) method has been used for determining the optimal location of UPFC.…”

Section: Introductionmentioning

confidence: 99%

Optimal placement of Unified Power Flow Controllers (UPFCs) using Mixed-Integer Non-Linear Programming (MINLP) method

Aminifar

Fotuhi-Firuzabad

Khodaei

et al. 2009

2009 IEEE Power &Amp; Energy Society General Meeting

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Utilization of Unified Power Flow Controllers (UPFCs) can be more beneficial in the restructured power systems due to their capabilities in increasing the transmission line capacities as well as shunt reactive compensation. So, these devices should be installed such that the most benefit can be gained. In this paper, the problem of optimal placement of UPFCs is solved using Mixed-Integer Non-Linear Programming (MINLP) method. Hence, the problem is completely formulated based on this method and is solved using available commercial solvers. The salient feature of this method is having potential to simultaneously determine the optimal location of multi UPFCs. Also, since a full AC Optimal Power Flow (AC-OPF) is fulfilled during this process, functional parameters of UPFCs and results of OPF are obtained finally. Some case studies are examined to illustrate the effectiveness of the proposed formulation.

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Optimal Placement and Control of Unified Power Flow Control devices using Evolutionary Computing and Sequential Quadratic Programming

Cited by 13 publications

References 6 publications

Optimal unified power flow controller application to enhance total transfer capability

Optimal unified power flow controller application to enhance total transfer capability

A Comprehensive Survey of Optimal Placement and Coordinated Control Techniques of FACTS Controllers in Multi-Machine Power System Environments

Optimal placement of Unified Power Flow Controllers (UPFCs) using Mixed-Integer Non-Linear Programming (MINLP) method

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