Real-Time Contingency Analysis on Massively Parallel Architectures With Compensation Method

Huang, Shengjun; Dinavahi, Venkata

doi:10.1109/access.2018.2864757

Cited by 16 publications

(12 citation statements)

References 22 publications

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“…The recommendation of FERC to TOPs was to "review their realtime monitoring tools, such as state estimator and RTCA, to ensure that such tools represent critical facilities needed for the reliable operation of the BPS (bulk power system)". Now, modeling all "critical facilities" over a large area (across different utilities) could significantly increase the number of contingencies to be evaluated by RTCA, which would then increase the solution time considerably [4], [11]. In this regard, the ability of the proposed algorithm to analyze the effects of any outage on very large systems and provide meaningful quantifiable information in a matter of seconds gives it a distinct advantage.…”

Section: A Practical Utility Of the Proposed Algorithmmentioning

confidence: 99%

“…The traditional approaches for improving situational awareness are based on steady-state contingency analyses techniques that solve AC or DC power flows [7]- [11]. These techniques cannot detect transient/dynamic stability related violations but can identify branch overloads and voltage violations.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, power utilities select a subset of the contingencies for evaluation based on some pre-defined criteria [9], [10]. In [11], Huang et al stated that the size of this subset has considerable impact on RTCA solution: a large subset is computationally burdensome, while a small subset might miss critical scenarios. This can be a problem for real-time operations during extreme exigencies when multiple outages occur in rapid succession [4].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Graph Theoretic Approach to Power System Vulnerability Identification

Biswas

Pal

Werho

et al. 2021

IEEE Trans. Power Syst.

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During major power system disturbances, when multiple component outages occur in rapid succession, it becomes crucial to quickly identify the transmission interconnections that have limited power transfer capability. Understanding the impact of an outage on these critical interconnections (called saturated cut-sets) is important for enhancing situational awareness and taking correct actions. This paper proposes a new graph theoretic approach for analyzing whether a contingency will create a saturated cut-set in a meshed power network. A novel feature of the proposed algorithm is that it lowers the solution time significantly making the approach viable for real-time operations. It also indicates the minimum amount by which the power transfer through the critical interconnections should be reduced so that post-contingency saturation does not occur. Robustness of the proposed algorithm for enhanced situational awareness is demonstrated using the IEEE-118 bus system as well as a 17,000+ bus model of the Western Interconnection (WI). Comparisons made with different approaches for power system vulnerability assessment prove the utility of the proposed scheme for aiding power system operations during extreme exigencies.

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Section: A Practical Utility Of the Proposed Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Graph Theoretic Approach to Power System Vulnerability Identification

Biswas

Pal

Werho

et al. 2021

IEEE Trans. Power Syst.

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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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“…GPU in acceleration single PF [10,11,12,13] as well as many PFs e.g. for static contingency analysis and online PPF [14,15,16,17,18,19].…”

Section: Introductionmentioning

confidence: 99%

Fast Parallel Newton-Raphson Power Flow Solver for Large Number of System Calculations with CPU and GPU

Wang,

Berg,

Braun

2021

Preprint

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To analyze large sets of grid states, e.g. in time series calculations or parameter studies, large number of power flow calculations have to be performed, as well as evaluating the impact from uncertainties of the renewable energy e.g. wind and PV of power systems with Monte-Carlo simulation. For the application in real-time grid operation and in cases when computational time is critical, a novel approach on parallelization of Newton-Raphson power flow for many calculations on CPU and with GPU-acceleration is proposed. The result shows a speed-up of over x100 comparing to the open-source tool pandapower, when performing repetitive power flows of system with admittance matrix of the same sparsity pattern on both CPU and GPU. The speed-up relies on the optimized algorithm and parallelization strategy, which can reduce the repetitive work and saturate the high hardware performance of modern CPUs and GPUs well. This is achieved with the proposed batched sparse matrix operation and batched linear solver based on LU-refactorization. The batched linear solver shows a large performance improvement comparing to the state-of-art linear system solver KLU library and a better saturation of the GPU performance with small problem scale. Finally, the method of integrating the proposed solver into pandapower is presented, thus the parallel power flow solver with outstanding performance can be easily applied in challenging real-life grid operation and innovative researches e.g. data-driven machine learning studies.

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Real-Time Contingency Analysis on Massively Parallel Architectures With Compensation Method

Cited by 16 publications

References 22 publications

A Graph Theoretic Approach to Power System Vulnerability Identification

A Graph Theoretic Approach to Power System Vulnerability Identification

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

Fast Parallel Newton-Raphson Power Flow Solver for Large Number of System Calculations with CPU and GPU

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