Investigations of the impact of powerformer on composite power system reliability

Limbu, T.R.; Saha, Tapan Kumar

doi:10.1109/pes.2005.1489510

Cited by 6 publications

(4 citation statements)

References 22 publications

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“…7b shows an equivalent single line diagram to reduce the size of the calculations. It should be noted that the existing elements are the equivalent elements in the network and they are obtained by applying equations (10) to (12) [13].…”

Section: Case Study Network: Simulation Resultsmentioning

confidence: 99%

“…A study has been performed on the evaluation of powerformers TM by SECRC/ABB institution for the estimation of their reliability and indices [11]. In [12], the reliability of the power systems and powerformers TM based on composite reliability is presented through state enumeration. In this reference, composite power system reliability and powerformers TM are offered without a few sample buses.…”

Section: Introductionmentioning

confidence: 99%

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Power system reliability enhancement by using PowerformerTM

Rahmat-Allah¹,

Moazzami²,

Nasiri³

2009

Serb. J. Electr. Eng.

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A high-voltage generator PowerformerTM is a new generation of the AC generators. The most significant advantages of these PowerformerTM are their direct connection to high-voltage grid, higher availability, and more reactive power margin, short term overloading capacity and removing the power transformer from the structure of the power plant. In this paper, the installation effect of these generators on the power system reliability is investigated. The amount of the effects depends on the type and location of the power plant, location of the PowerformerTM, the size of load and network topology. For this purpose, in the 6-bus IEEE RBTS system, the conventional generators are replaced by these new PowerformerTM and then, the reliability indices are evaluated. The simulation results show that the reliability indices such as the expected duration of load curtailment (EDLC) and the expected energy not served (EENS) are improved.

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Section: Case Study Network: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power system reliability enhancement by using PowerformerTM

Rahmat-Allah¹,

Moazzami²,

Nasiri³

2009

Serb. J. Electr. Eng.

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“…To investigate the impact of plant efficiency and FOR, this study has used the technical and economic data of an innovative generator known as Powerformer TM [23][24]. Powerformer TM is a high voltage generator that produces electricity at high voltage (Powerformer TM installations with a terminal voltage of up to155 kV is already in the system) and it can be directly connected to the transmission grid without a step-up transformer.…”

Section: Technology Options For Efficiency and Reliabilitymentioning

confidence: 99%

Generation Investment and Risks Modeling in a Deregulated Electricity Market

Limbu¹,

Saha²,

McDonald³

2010

International Journal of Emerging Electric Power Systems

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A new probabilistic model to simulate generation investment and risks applicable in a deregulated market is proposed. In this process, probabilistic production cost simulation is applied to simulate energy dispatches. Electricity prices are simulated from a modified Black-ScholesMerton (BSM) based price simulation model. In this work, the existing BSM model is enhanced thus making it possible to simulate the demand and supply conditions in price determination. A complete investment analysis model is then developed by integrating the above two simulation processes. Using this model, generator investors can analyze the impacts on the anticipated revenue due to different plant efficiency, availabilities, bilateral contract markets and changes in demand and supply conditions. Simulated results show that the proposed model is able to analyse the viability in generation investment with much simplicity.

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“…Reliability can be interdependent having economics and increased expense is essential to accomplish increased stability or maybe to keep up stability on latest and acceptable levels [8]. Random approaches are now used more broadly within power system operations and planning due to a various uncertainties engaged [9].…”

Section: Introductionmentioning

confidence: 99%

Optimal Location for Fixing Fuel Cells in a Distributed Generation Environment using Hybrid Technique

Subramanyam¹,

Ram²,

Subrahmanyam³

2016

ijeei

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The paper proposes optimal location for fixing fuel cells in a distribution system using an innovative hybrid technique. The novelty of the proposed method is the combined performance of the Genetic Algorithm (GA) and Recurrent Neural Network (RNN) technique, thereby integrating GA first phase, RNN technique and GA second phase. The optimum location for fixing the fuel cell is attained by using the GA first phase. Here, the GA first phase utilizes the load flow data at different loading conditions for determining the optimum location. The RNN is aptly trained by the target fuel cell size and the corresponding inputs such as load variation and bus number. During the testing time, the RNN provides the fuel cell capacity according to the load variation and bus number. By using the attained fuel cell capacities, the GA second phase optimizes the fuel cell capacity to minimize the power loss and the voltage deviation. The objective function mainly helps to improve the bus voltage profile and the power loss reduction. Thus, the proposed hybrid technique is implemented in the MATLAB/simulink platform and its effectiveness is analyzed by comparing it with the GA, PSO and other hybrid PSO techniques. The comparison results unequivocally demonstrate the superiority of the proposed approach and confirm its sterling potential to solve the problem.

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Investigations of the impact of powerformer on composite power system reliability

Cited by 6 publications

References 22 publications

Power system reliability enhancement by using PowerformerTM

Power system reliability enhancement by using PowerformerTM

Generation Investment and Risks Modeling in a Deregulated Electricity Market

Optimal Location for Fixing Fuel Cells in a Distributed Generation Environment using Hybrid Technique

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