Extracting Spatial-Temporal Characteristics of Frequency Dynamic in Large-Scale Power Grids

Ma, Ningning; Wang, Delin

doi:10.1109/tpwrs.2019.2896327

Cited by 40 publications

(7 citation statements)

References 26 publications

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“…Second, it may no longer be reasonable to assume a single frequency throughout the grid (represented by the motion of the CoI with a lumped inertia) in frequency stability studies. The angle swing around the CoI creates spatial distribution of frequencies during transients [41], [42] that may result in very different RoCoF and nadir at different nodes. This may affect the configuration of frequency-based protection schemes.…”

Section: Fast Frequency Dynamicsmentioning

confidence: 99%

Power System Stability With a High Penetration of Inverter-Based Resources

Green

2023

Proc. IEEE

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Inverter-Based Resources (IBR) possess dynamics which are significantly different to those of synchronousgenerator-based sources and as IBR penetrations grow the dynamics of power systems are changing. The paper discusses the characteristics of the new dynamics and examines how they can be accommodated into the long-standing categorisations of power system stability in terms of angle, frequency and voltage stability. It is argued that inverters are causing the frequency range over which angle, frequency and voltage dynamics act to extend such that the previously partitioned categories are now coupled and further coupled to new electromagnetic modes. While grid-forming (GFM) inverters share many characteristics with generators, grid-following (GFL) inverters are different. This is explored in terms of similarities and differences in synchronisation, inertia and voltage control. The concept of duality is used to unify the synchronisation principles of GFM and GFL inverters, and thus is established the generalised angle dynamics. This enables analytical study of GFM-GFL interaction which is particularly important to guide the placement of GFM apparatuses and is even more important if GFM inverters are allowed to fallback to GFL mode during faults to avoid over-sizing to support short-term overload. Both GFL and GFM inverters contribute to voltage strength but with marked differences, which implies new features of voltage stability. Several directions for further research are identified including (i) extensions of nonlinear stability analysis to accommodate new inverter behaviours with cross-coupled time-frames. (ii) establishment of spatialtemporal indices of system strength and stability margin to guide the provision of new stability services and (iii) datadriven approaches to combat increased system complexity and confidentiality of inverter models.

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Section: Fast Frequency Dynamicsmentioning

confidence: 99%

Power System Stability With a High Penetration of Inverter-Based Resources

Green

2023

Proc. IEEE

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“…The test system has 10 generators and 4 areas. It is split into four areas considering the coherency of the generators based on frequency responses [21], [29]. The estimated regional inertia values are verified against the actual inertia of the test system.…”

Section: Reward Mechanismmentioning

confidence: 99%

Continuous Real-Time Estimation of Power System Inertia Using Energy Variations and Q-Learning

Lavanya

2023

IEEE Open J. Instrum. Meas.

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With the growing emphasis on mitigating climate change, the power industry is moving towards renewable energy sources as an alternative to fossil fuel-based power plants. The transition to renewable energy has created numerous challenges, one of which is the low levels of inertia that impact the stability of power systems. Therefore, inertia monitoring has become an integral part of power system operation to dispatch renewable energy sources while maintaining frequency stability. This article presents an online method to continuously estimate the inertia of a power system. The inertia is computed from PMU (Phasor Measurement Unit) data using small variations in frequency and power under ambient conditions. The method uses electrical and kinetic energy variations to compute inertia. In addition, a Q-learning-based method is presented to identify mechanical power changes to discard invalid inertia estimates. The method is demonstrated using the IEEE-39 bus system to monitor the regional inertia of the test system.

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“…en the accident number method and the accident rate method are used to identify the road sections with multiple accidents. Or the accident data can be analysed by building models such as Poisson regression, negative binomial regression, and empirical Bayesian method, and the multiaccident sections can be judged according to the prediction of the accident development trend [28]. is kind of method requires manual segmentation of the road before identification, and the result of segmentation will directly affect the prediction of traffic accident-prone sections.…”

Section: Related Workmentioning

confidence: 99%

STEIM: A Spatiotemporal Event Interaction Model in V2X Systems Based on a Time Period and a Raster Map

Luo

Bao

et al. 2020

Mobile Information Systems

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e Internet of Vehicles (IoV) is an important artificial intelligence research field for intelligent transportation applications. Complex event interactions are important methods for data flow processing in a Vehicle to Everything (V2X) environment. Unlike the classic Internet of ings (IoT) systems, data streams in V2X include both temporal information and spatial information. us, effectively expressing and addressing spatiotemporal data interactions in the IoV is an urgent problem. To solve this problem, we propose a spatiotemporal event interaction model (STEIM). STEIM uses a time period and a raster map for its temporal model and spatial model, respectively. In this paper, first, we provide a spatiotemporal operator and a complete STEIM grammar that effectively expresses the spatiotemporal information of the spatiotemporal event flow in the V2X environment. Second, we describe the design of the operational semantics of the STEIM from the formal semantics. In addition, we provide a spatiotemporal event-stream processing algorithm that is based on the Petri net model. e STEIM establishes a mechanism for V2X event-stream temporal and spatial processing. Finally, the effectiveness of the STEIM-based system is demonstrated experimentally.

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Extracting Spatial-Temporal Characteristics of Frequency Dynamic in Large-Scale Power Grids

Cited by 40 publications

References 26 publications

Power System Stability With a High Penetration of Inverter-Based Resources

Power System Stability With a High Penetration of Inverter-Based Resources

Continuous Real-Time Estimation of Power System Inertia Using Energy Variations and Q-Learning

STEIM: A Spatiotemporal Event Interaction Model in V2X Systems Based on a Time Period and a Raster Map

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