Accelerating the Gauss-Seidel Power Flow Solver on a High Performance Reconfigurable Computer

Byun, Jong-Ho; Ravindran, Arun; Mukherjee, Arindam; Joshi, Bharat; Chassin, David P.

doi:10.1109/fccm.2009.23

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…However, the convergence of Gauss-Seidel can be considered comparatively slow. In [23] an accelerated Gauss-Seidel implementation using FPGAs is presented. Their approach is not compatible with the requirement for a decentralized power-flow calculation as mentioned above.…”

Section: Computation Of Power-flowmentioning

confidence: 99%

Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent‐Based Modeling and Simulation

et al. 2018

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In future electrical distribution systems, component heterogeneity and their cyber-physical interactions through electrical lines and communication lead to emergent system behavior. As the distribution systems represent the largest part of an energy system with respect to the number of nodes and components, large-scale studies of their emergent behavior are vital for the development of decentralized control strategies. This paper presents and evaluates DistAIX, a novel agent-based modeling and simulation tool to conduct such studies. The major novelty is a parallelization of the entire model—including the power system, communication system, control, and all interactions—using processes instead of threads. Thereby, a distribution of the simulation to multiple computing nodes with a distributed memory architecture becomes possible. This makes DistAIX scalable and allows the inclusion of as many processing units in the simulation as desired. The scalability of DistAIX is demonstrated by simulations of large-scale scenarios. Additionally, the capability of observing emergent behavior is demonstrated for an exemplary distribution grid with a large number of interacting components.

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Section: Computation Of Power-flowmentioning

confidence: 99%

Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent‐Based Modeling and Simulation

et al. 2018

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“…Byun et al [31] showed that a 200 000bus node requires 67.64 s to simulate. They reached a 62× speedup using a field programmable gate array (FPGA) implementation.…”

Section: ) Dependency Graphmentioning

confidence: 99%

A Response Cost Model for Advanced Metering Infrastructures

Fawaz

Berthier

Sanders

2016

IEEE Trans. Smart Grid

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The smart grid is driving the deployment of networked components within the traditional power grid to achieve greater reliability and control. However, those cyber components are creating new security vulnerabilities that could lead to significant disruptions if exploited maliciously. We propose a comprehensive cost model designed to assist in the selection of responses to malicious attacks on an advanced metering infrastructure. The cost model reflects the costs of response actions due to outages in the distribution grid, disruptions of the electricity market, and violations of contractual agreements among stakeholders. We also present a realistic implementation of the cost model using ArcGIS for topology generation and GridLAB-D for grid simulation. The cost model is a step forward toward achievement of automated resilience in the smart grid. It also provides comprehensive modeling for system dynamics and operation costs, while relieving utilities from the burden of manually assigning costs for response actions and modeling attacker steps.

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“…Parallel processing schemes were exploited in [16][17][18][19][20][21] to accelerate the computation of the power flow solution. In [22][23][24], different versions of the generalized minimal residual method equipped with some accelerating schemes were used to speed up the traditional Newton method.…”

Section: Introductionmentioning

confidence: 99%

A novel efficient model for the power flow analysis of power systems

Safdarian¹,

Fotuhi‐Firuzabad²,

Aminifar³

2015

Turk J Elec Eng & Comp Sci

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Abstract:The overall system status calculated by power flow analysis is the most basic information used for all decisions taken by power system operators and planners. While conventional AC power flow solutions are computationally tractable, approximate DC models are employed in many applications, such as optimal power flow studies and unit commitment problems, mainly due to the linear nature of DC models. These models do not provide any information on the reactive power and voltage magnitude quantities and occasionally inaccurate results of the active power values. This paper presents an efficient power flow approach compromising both the conflicting aspects of speed and accuracy.The proposed model adopts bus voltage magnitudes and phase angles as state variables. Given the nonlinear nature of transmission system losses, an iterative method for solving the problem is proposed. Simulation results reveal that the proposed method outperforms conventional methods from an execution time viewpoint, while preserving acceptable accuracy. Different system conditions are also investigated to reveal the robustness and reliability of the proposed model.

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Accelerating the Gauss-Seidel Power Flow Solver on a High Performance Reconfigurable Computer

Cited by 6 publications

References 5 publications

Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent‐Based Modeling and Simulation

Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent‐Based Modeling and Simulation

A Response Cost Model for Advanced Metering Infrastructures

A novel efficient model for the power flow analysis of power systems

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