Controlled Islanding Demonstrations on the WECC System

Xu, Guangyue; Vittal, Vijay; Meklin, A.; Thalman, J E

doi:10.1109/tpwrs.2010.2047413

Cited by 61 publications

(30 citation statements)

References 12 publications

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“…As the ICI scheme is to be used only during severe disturbances, these case scenarios should ideally reflect electrical events that typically result in a partial or complete blackout. Since the possible number of scenarios that could occur in a real power system is large, the focus of the development of these case scenarios will be on the "worst-case scenarios", similarly to the approach followed in previous works, such as [4]- [6].…”

Section: B Impact Assessmentmentioning

confidence: 99%

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Intentional Controlled Islanding and Risk Assessment: A Unified Framework

Quirós-Tortós

Demetriou

Panteli

et al. 2018

IEEE Systems Journal

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Abstract--Power systems are prone to cascading outages leading to large-area blackouts, and intentional controlled islanding (ICI) can mitigate these catastrophic events by splitting the system into sustainable islands. ICI schemes are used as the last resort to prevent cascading events; thus, it is critical to evaluate the corresponding system risks to ensure their correct operation. This paper proposes a unified framework to assess the risk of ICI schemes. First, a novel ICI method to create islands with minimum power imbalance is presented. Further, a risk assessment methodology is used to assess the probability and impact of the main operational modes of the ICI scheme. The unified framework provides insights on the benefits of implementing ICI, considering the uncertainties related to its reliability. The ICI scheme is demonstrated using the IEEE 9-bus system. The proposed unified framework is then fully deployed on the actual power system of Cyprus. Multiple case studies on the real network are created to demonstrate the adaptability and robustness of the proposed scheme to different system conditions. The adoption of the unified framework highlights that the system risk significantly reduces with the ICI in service, even when the reliability uncertainties associated with the scheme are considered.

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Section: B Impact Assessmentmentioning

confidence: 99%

“…The slow coherency theory is effectively used in [4]- [6] to split the system across weak connections; however, this approach might not account for changes in the topology of the network, which can have an effect in the coherency results. Spectral clustering-based ICI methods are presented in [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

Intentional Controlled Islanding and Risk Assessment: A Unified Framework

Quirós-Tortós

Demetriou

Panteli

et al. 2018

IEEE Systems Journal

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“…The WAMS global information of rotor angles, generator speeds, voltage magnitudes and phase angles can be utilised to develop a blackout mitigation model along with intelligent control, adaptive protection relays and remedial action scheme such as forced line outage, load shedding, and controlled islanding. Load shedding (Ding et al, 2013;Sun et al, 2011) and controlled islanding (Xu et al, 2011) for preventive action against cascade failure is a matured technology among researchers. In power systems, a WAMS-based adaptive strategy for controlled islanding was introduced by Song et al (2014).…”

Section: Introductionmentioning

confidence: 99%

Augmenting WAMPAC with machine learning tools for early warning and mitigation of blackout events

Gupta

Kazi²,

Wagh³

et al. 2018

IJHT

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Abstract:The development of phasor measurement unit (PMU) in the power network and availability of real-time communication in wide area monitoring system has enabled the proactive blackout prediction and possibility of mitigation against blackout events. The objective of this paper is to provide a wide area monitoring protection and control (WAMPAC) model which can predict cascade failure and minimise the risk of massive blackout. The proposed model is a combination of simulation and a measurement-based approach. The key contribution of this paper is a topological analysis of grid using graph theoretic approach, blackout prediction using machine learning technique and the mitigation plan against blackout by combining graph theoretic approach and change in voltage phase angle at different buses. The proposed methodology is validated using IEEE 30 bus system.

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“…Many of traditional and current remedial action schemes protect the power system against particular contingencies. However, under severe multiple contingencies such methods may fail [1]. For example, the 2003 Northeast Blackout involved 10-20 simultaneous contingencies (see [2,3]).…”

Section: Introductionmentioning

confidence: 99%

“…In comparison to uncontrolled islanding, which may happen in a blackout, controlled islanding can help to minimize the disturbance of power supply to a system as early as possible and facilitate the recovery process afterwards. Controlled islanding strategies have been extensively discussed in [1,[4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Large-scale stochastic power grid islanding operations by line switching and controlled load shedding

2016

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Recently, there has been an increasing concern regarding the security and reliability of power systems due to the onerous consequences of cascading failures. Among many emergency control operations, controlled power grid islanding is a last resort yet powerful method to prevent large-scale blackouts. Islanding operations split the power grid into self-sufficient operational subnetworks and avoid cascading failures by isolating the failed elements of the power system into a non-operational island. In this paper, we consider a two-stage stochastic mixed-integer program to seek the optimal islanding operations under severe contingency states. Line switching and controlled load shedding are the main tools for the islanding operations and load shedding is considered as a measurement to gauge system's inability to respond to disruption. The number of possible extreme contingencies grows exponentially as the size of the grid increases, and this results in a large-scale mixed-integer program, which is a computationally challenging problem to solve. We present an efficient decomposition method to solve this problem for large-scale power systems.

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Controlled Islanding Demonstrations on the WECC System

Cited by 61 publications

References 12 publications

Intentional Controlled Islanding and Risk Assessment: A Unified Framework

Intentional Controlled Islanding and Risk Assessment: A Unified Framework

Augmenting WAMPAC with machine learning tools for early warning and mitigation of blackout events

Large-scale stochastic power grid islanding operations by line switching and controlled load shedding

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