The Anatomy of the 2016 South Australia Blackout: A Catastrophic Event in a High Renewable Network

Yan, Ruifeng; Masood, Nahid‐Al; Bai, Feifei; Gu, Huajie

doi:10.1109/tpwrs.2018.2820150

“…Reactive power capability of converter connected Type 4 WTs can be either converter voltage limited or converter current limited. At WPP level, converter voltage limited reactive power and converter current limited reactive power can be defined by (9) and (10) respectively.…”

Section: A Wind Turbine and Wind Power Plant Modelmentioning

confidence: 99%

Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

Sarkar¹,

Hansen²,

Sørensen³

2020

Preprint

0

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Traditional voltage stability assessment methods do not include temporal variation of renewable power generations like wind. This paper proposes a novel methodology for probabilistic voltage stability assessment methodology which can be used in conjunction with any of the existing traditional voltage stability indices. Historical wind power data are used to determine probabilistic distribution of wind power at future instant based on wind power value at current instant. Based on the probabilistic risk of increase and decrease of wind power at future instant, two probabilistic voltage stability indices are computed. The worse case value among the two indices are used as prediction of voltage stability index at future instant, based on current system parameters. Effectiveness of the proposed methodology in predicting proximity of the system voltage collapse is illustrated through case studies and time-series simulations. Results show that proposed methodology predicts more realistic proximity to voltage collapse than traditional stability assessments.<br>

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“…On 28 September 2016, a once in 50-years storm involving two tornadoes resulted in damage to three electricity transmission lines in South Australia. This triggered a chain of events, with nine wind farms suffering significant power reductions, resulting in the failure of the grid interconnector with the adjacent state [40]. According to the Australian Energy Market Operator (AEMO), the South Australian network became "islanded" and unable to import electricity to make up for power reductions; and electricity supply was lost over a period of hours and days [41].…”

Section: South Australiamentioning

confidence: 99%

Energy Transitions Towards Low Carbon Resilience: Evaluation of Disaster-Triggered Local and Regional Cases

Ko

¹

,

Barrett

²

,

Copping

³

et al. 2019

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Following numerous global scientific studies and major international agreements, the decarbonization of energy systems is an apparent and pressing concern. The consequence of continued emission growth tied to rising global average temperatures is difficult to predict, but against a background of other natural and human-induced disasters, may create a situation, from a positive perspective, where each disaster event triggers "build back better" responses designed to speed the transition toward low carbon, resilience-oriented energy systems. This article examines the potential for disaster-triggered responses in communities, at various local and regional levels, in four industrial economies in the Asia Pacific region: Japan, China, Australia, and the USA. Seven case studies were evaluated against a set of criteria that exemplify the key aspects of resilient energy systems. The research results suggest that a new space of innovation does emerge in post-disaster situations at a range of local and regional scales. The greatest potential benefit and opportunity for significant gains, however, appears to manifest at the small community level, and the ultimate challenge relates to how to mainstream local innovations into state and national level transformation on energy systems so as to enhance resilience and promote rapid decarbonization.

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“…However, with variable renewable energy generations like wind power plants (WPPs) in the power systems there is also temporal variation in power generation. Recent events like black-out in South Australia in 2016 [10] and disturbance in UK grid on August 9, 2019 [11] have been incited by large share of wind power in their respective power systems. Therefore it is important to include wind power in traditional voltage stability assessment methods.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

Sarkar¹,

Hansen²,

Sørensen³

2020

Preprint

View full text Add to dashboard Cite

Traditional voltage stability assessment methods do not include temporal variation of renewable power generations like wind. This paper proposes a novel methodology for probabilistic voltage stability assessment methodology which can be used in conjunction with any of the existing traditional voltage stability indices. Historical wind power data are used to determine probabilistic distribution of wind power at future instant based on wind power value at current instant. Based on the probabilistic risk of increase and decrease of wind power at future instant, two probabilistic voltage stability indices are computed. The worse case value among the two indices are used as prediction of voltage stability index at future instant, based on current system parameters. Effectiveness of the proposed methodology in predicting proximity of the system voltage collapse is illustrated through case studies and time-series simulations. Results show that proposed methodology predicts more realistic proximity to voltage collapse than traditional stability assessments.<br>

show abstract

The Anatomy of the 2016 South Australia Blackout: A Catastrophic Event in a High Renewable Network

Cited by 239 publications

References 21 publications

Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

Energy Transitions Towards Low Carbon Resilience: Evaluation of Disaster-Triggered Local and Regional Cases

Probabilistic Voltage Stability Assessment Considering Variability of Wind Power

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