A proposal for investment recovery of FACTS devices in deregulated electricity markets

Mithulananthan, Nadarajah; Acharya, Naresh

doi:10.1016/j.epsr.2006.06.007

Cited by 55 publications

(14 citation statements)

References 15 publications

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“…Congestion management, using an Interline Power Flow Controller (IPFC), is performed in [12]. Application of a series of FACTS for congestion management in deregulated electricity markets is discussed in [13][14][15]. These references simplify the optimization problem by assuming given sizes of FACTS devices and/or the employment of second order generations cost functions, without considering sine components, due to valve point loading effects, and omitting load benefit functions in the objective function.…”

Section: Nomenclaturementioning

confidence: 99%

“…In this paper, the Newton-Raphson (N-R) power flow formulation is used, and TCSC and SSSC are represented using a Power Injection Model (PIM) [13][14][15][16]. This will allow easy integration of FACTS devices into the existing power system software tools, and retain the symmetrical structure of the admittance matrix.…”

Section: Mathematical Model Of Tcsc and Ssscmentioning

confidence: 99%

“…With a TCSC unit connected in line ij, the injected real and reactive power at buses i and j are as follows [13][14][15]: ) can be expressed as [16]:…”

Section: Power Injection Model Of Tcsc and Ssscmentioning

confidence: 99%

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Social welfare maximization with fuzzy based genetic algorithm by TCSC and SSSC in double-sided auction market

2012

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This paper presents a fuzzy-based genetic algorithm to maximize total system social welfare by best the placement and sizing of TCSC and SSSC devices, considering their investment cost in a doublesided auction market. To introduce more accurate modeling, the valve loading effects are incorporated into the conventional quadratic smooth generator cost curves. In addition, quadratic consumer benefit functions are integrated into the objective function to guarantee that locational marginal prices charged at the demand buses are less than, or equal to, the DisCos benefit, earned by selling the power to retail customers. The proposed approach utilizes fuzzy-based genetic algorithms for optimal scheduling of GenCos and DisCos, as well as optimal placement and sizing of SSSC and TCSC units. In addition, the Newton-Raphson approach is used to minimize the mismatch of the power flow equation. Simulation results on the modified IEEE 14-bus and IEEE 30-bus test systems (with/without line flow constraints, before and after the compensation) are used to examine the impact of SSSC and TCSC on total system social welfare improvement versus their cost. To validate the accuracy of the proposed method, several case studies are presented and simulation results are compared with those generated by genetic and Sequential Quadratic Programming (SQP) approaches.

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Section: Nomenclaturementioning

confidence: 99%

Section: Mathematical Model Of Tcsc and Ssscmentioning

confidence: 99%

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Social welfare maximization with fuzzy based genetic algorithm by TCSC and SSSC in double-sided auction market

2012

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“…Different approaches, based on sensitivity methods have also been proposed for optimal locating of FACTS devices in both vertically integrated and unbundled power systems [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Optimal Particle Swarm Based Placement and Sizing of Static Synchronous Series Compensator to Maximize Social Welfare

Hajforoosh¹,

Nabavi²,

Masoum³

2012

Journal of Electrical Engineering and Technology

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-Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

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“…However, as the deregulation progresses among power utilities, the utility operators face new problems and challenges [2]. Furthermore, since the generation investment decision currently is in the hand of private entity, obviously there is a lack of coordination between the generation and transmission investments.…”

Section: Introductionmentioning

confidence: 99%

Optimal Locating and Sizing of SSSC using Genetic Algorithm in Deregulated Power Market

Nabavi¹,

Khafafi²,

Sakhavati³

et al. 2011

IJCA

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The aim of this paper is presenting a genetic algorithm based method for congestion management and to maximize social welfare using one unit Static Synchronous Series Compensator (SSSC) in a double auction pool market based power systems. The aims are achieved by optimal locating and sizing one SSSC unit. In this paper, the GenCos cost functions are considered to be the quadratic form. Simulation outcomes on the modified IEEE 14 bus test system are used to show the impact of SSSC unit on the congestion management and social welfare maximization. Inclusion of the benefit functions of customer in the objective function and the utilization of a GA based algorithm for optimal locating/sizing of SSSC to guarantee fast convergence to the global optimal solution are the main contributions.

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A proposal for investment recovery of FACTS devices in deregulated electricity markets

Cited by 55 publications

References 15 publications

Social welfare maximization with fuzzy based genetic algorithm by TCSC and SSSC in double-sided auction market

Social welfare maximization with fuzzy based genetic algorithm by TCSC and SSSC in double-sided auction market

Optimal Particle Swarm Based Placement and Sizing of Static Synchronous Series Compensator to Maximize Social Welfare

Optimal Locating and Sizing of SSSC using Genetic Algorithm in Deregulated Power Market

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