Investigation of Cascading Events in Power Systems with Renewable Generation

Nakas, Georgios A.; Papadopoulos, Panagiotis

doi:10.1109/isgt-europe47291.2020.9248818

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…In addition to this, a basic load shedding scheme to arrest significant frequency drops after loss of generation is modelled. The details related to modelling of dynamic components and their protection devices is present in [22]. Simulations are performed for different operating conditions which include changes in load (in the range of 0.7 -1.2 p.u.…”

Section: A Description Of Datasetmentioning

confidence: 99%

Prediction of Cascading Failures and Simultaneous Learning of Functional Connectivity in Power System

Ahmad

Papadopoulos

2022

2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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The prediction of power system cascading failures is a challenging task, especially with increasing uncertainty and complexity in power system dynamics due to integration of renewable energy sources (RES). Given the spatio-temporal and combinatorial nature of the problem, physics based approaches for characterizing cascading failures are often limited by their scope and/or speed, thereby prompting the use of a spatiotemporal learning technique. This paper proposes prediction of cascading failures using a spatio-temporal Graph Convolution Network (GCN) based machine learning (ML) framework. Additionally, the model also learns an importance matrix to reveal power system interconnections (graph nodes/edges) which are crucial to the prediction. The elements of learnt importance matrix are further projected as power system functional connectivities. Using these connectivities, insights on vulnerable power system interconnections may be derived for enhanced situational awareness. The proposed method has been tested on a modified IEEE 10 machine 39 bus test system, with RES and action of protection devices.

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Section: A Description Of Datasetmentioning

confidence: 99%

Prediction of Cascading Failures and Simultaneous Learning of Functional Connectivity in Power System

Ahmad

Papadopoulos

2022

2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)

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“…An Under-Frequency Load Shedding (UFLS) scheme with four stages is implemented for the disconnection of a percentage of demand at low frequency to restore the active power balance in cases of frequency instability. More details about the protection devices settings can be found in [20].…”

Section: B System Under Studymentioning

confidence: 99%

Investigation of the Impact of Load Tap Changers and Automatic Generation Control on Cascading Events

Nakas

Papadopoulos

2021

2021 IEEE Madrid PowerTech

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This paper presents an assessment of the impact of control mechanisms, specifically load tap changers (LTCs) and automatic generation control (AGC), on cascading events in power systems with renewable generation. In order to identify the impact of these voltage and frequency related mechanisms, a large number of dynamic RMS simulations for various operating conditions is performed taking into consideration renewable generation, system loading and the action of protection devices. The sequences in which the cascading events appear are analysed, and each cascading event is described by the component that trips, the time and the reason for tripping. The number and reason of cascading events, the average load loss and the time between consecutive events are used as metrics to quantify the impact of LTCs and AGC. The study is demonstrated on a modified version of the IEEE-39 bus model with renewable generation and protection devices.

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“…The significant penetration of renewable energy resources and the ambitious carbon targets set out within the next decades, the electrification of heating and transportation, increased integration of power electronic-based devices and decommissioning of large synchronous plants has increased the uncertainty around network stability and security of supply. Power systems are subjected to dynamic variations in their state, which under specific circumstances can lead to cascading outages and precipitate a partial or total blackout [3].…”

Section: Introductionmentioning

confidence: 99%

Multi-Vector Power Island Operation Utilizing Demand Side Response Based on a Cloud- Based Optimization Strategy (CbOS)

Patsidis,

Dyśko,

Booth

et al. 2024

IEEE Access

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Intentional islanding is one of the potential strategies to mitigate risks related to total blackouts by partitioning the network into multiple power islands. This paper focuses on developing a cloud-based strategy for managing the post-islanding power islands operation considering the coupling of the electrified heating vector. At the core, a novel multi-vector cloud-based optimization strategy (CbOS) is utilized to harness the hidden flexibility of heating, ventilation and air-conditioning (HVAC) systems, resulting in reduced load shedding required to balance the power island and decreased operational costs. To maintain the sustainability of the power island, CbOS is further integrated with an additional objective of optimizing a voltage stability index and costs. The architecture upon which CbOS is built, provides the means to deploy the required software tools and its operation is tested in a generalizable power island under representative cases studies with respect to the level of controllability that CbOS is expected to have among the fleet of energy assets. The results reveal that when all energy assets are operated under CbOS, a substantial cost reduction up to 55.6% can be achieved by utilizing the flexibility stemming from the HVAC systems. Concurrently, voltage stability profiles are improved for the lines under stress.INDEX TERMS Cloud-based optimization, demand side response, electrified heating, intentional islanding, multi-vector power island NOMENCLATURE

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Investigation of Cascading Events in Power Systems with Renewable Generation

Cited by 4 publications

References 14 publications

Prediction of Cascading Failures and Simultaneous Learning of Functional Connectivity in Power System

Prediction of Cascading Failures and Simultaneous Learning of Functional Connectivity in Power System

Investigation of the Impact of Load Tap Changers and Automatic Generation Control on Cascading Events

Multi-Vector Power Island Operation Utilizing Demand Side Response Based on a Cloud- Based Optimization Strategy (CbOS)

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