A Two-Layered Parallel Static Security Assessment for Large-Scale Grids Based on GPU

Chen, Deyang; Han, Jing; Li, Yalou; Xu, Duo

doi:10.1109/tsg.2016.2600256

Cited by 31 publications

(8 citation statements)

References 22 publications

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“…Other algorithms adopt the dual decomposition or the alternating direction method of multipliers, e.g., applied to the DC OPF problems in [10], [21]. Recently, in addition to classic CPU-based computing, graphical processing units (GPUs) have also been explored for security analysis in [11] or [36]. Alternatively, the SCOPF problem can be decomposed on the linear level.…”

Section: Security Constrained Opfmentioning

confidence: 99%

Reduced-Space Interior Point Methods in Power Grid Problems

Kardos,

Kourounis,

Schenk

2020

Preprint

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Due to critical environmental issues, the power systems have to accommodate a significant level of penetration of renewable generation which requires smart approaches to the power grid control. Associated optimal control problems are large-scale nonlinear optimization problems with up to hundreds of millions of variables and constraints. The interior point methods become computationally intractable, mainly due to the solution of large linear systems. This document addresses the computational bottlenecks of the interior point method during the solution of the security constrained optimal power flow problems by applying reduced space quasi-Newton IPM, which could utilize high-performance computers due to the inherent parallelism in the adjoint method. Reduced space IPM approach and the adjoint method is a novel approach when it comes to solving the (SC)OPF problems. These were previously used in the PDE-constrained optimization. The presented methodology is suitable for high-performance architectures due to inherent parallelism in the adjoint method during the gradient evaluation, since the individual contingency scenarios are modeled by independent set of the constraints. Preliminary evaluation of the performance and convergence is performed to study the reduced space approach.

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Section: Security Constrained Opfmentioning

confidence: 99%

Reduced-Space Interior Point Methods in Power Grid Problems

Kardos,

Kourounis,

Schenk

2020

Preprint

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“…Following smart grids, contingency analysis is the next application where GPU is used to reduce the simulation time of power flow analysis [99][100][101][102][103][104][105][106][107][108]. Depending on the simulation time reduction achieved, hybrid CPU-GPU solutions can evaluate a high number of contingencies and scenarios to find an optimal performance of power systems.…”

Section: Contingency Analysismentioning

confidence: 99%

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

et al. 2021

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The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the analysis of power systems are reaching their operational limit since the complexity and size of modern power systems results in long simulation times and high computational demand. Time reductions in simulation and analysis lead to the better and further optimized performance of power systems. Heterogeneous computing—where different processing units interact—has shown that power system applications can take advantage of the unique strengths of each type of processing unit, such as central processing units, graphics processing units, and field-programmable gate arrays interacting in on-premise or cloud environments. Parallel Heterogeneous Computing appears as an alternative to reduce simulation times by optimizing multitask execution in parallel computing architectures with different processing units working together. This paper presents a review of Parallel Heterogeneous Computing techniques, how these techniques have been applied in a wide variety of power system applications, how they help reduce the computational time of modern power system simulation and analysis, and the current tendency regarding each application. We present a wide variety of approaches classified by technique and application.

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“…In Reference 39, a two‐layer graphic processing unit (GPU)‐based method is proposed for power system SSA, which can analyze several contingencies simultaneously based on the ability of GPU. In the first layer, a hierarchical parallel lower‐upper decomposition method is implemented on GPU for accelerating the power flow computation by parallelization.…”

Section: Categorization Based On Power System Implementationmentioning

confidence: 99%

Static security assessment of power systems: A review

Gholami

Sanjari

Safari

et al. 2020

Int Trans Electr Energ Syst

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Summary The security assessment, based on which determinant decisions should be made for power system design, control and operation, is a challenging issue for utility engineers and network designers, especially in large‐scale power systems. Numerous methods have been proposed and implemented for this purpose, and a variety of indices have been suggested to address the static security condition of power networks. Large‐scale datasets of measurements in continually expanding power systems necessitate advanced knowledge in big data analytics. In this review paper, numerical techniques and machine learning‐based methods are reviewed as two main categories for static security assessment in power systems based on principal features of static security status classification such as type of classifier, the static security index, and feature selection and extraction methods. This paper can be used as a useful reference for static security assessment of power systems.

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A Two-Layered Parallel Static Security Assessment for Large-Scale Grids Based on GPU

Cited by 31 publications

References 22 publications

Reduced-Space Interior Point Methods in Power Grid Problems

Reduced-Space Interior Point Methods in Power Grid Problems

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

Static security assessment of power systems: A review

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