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Blackout

About: Blackout is a research topic. Over the lifetime, 2088 publications have been published within this topic receiving 30433 citations.


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Journal ArticleDOI
01 Mar 2022-iEnergy
TL;DR: In this paper , a review of self-adaptive, self-reporting, and self-healing dielectrics in the field of electrical insulation, and illuminating studies on smart polymers with autonomous functions in other fields are both introduced.
Abstract: Smart dielectric materials with bioinspired and autonomous functions are expected to be designed and fabricated for next-generation electrical insulation. Similar to organisms, such dielectrics with self-adaptive, self-reporting, and self-healing capabilities can be employed to avoid, diagnose, and repair electrical damage to prevent catastrophic failure and even a blackout. Compared with traditional dielectrics, the utilization of smart materials not only increases the stability and durability of power apparatus but also reduces the costs of production and manufacturing. In this review, researches on self-adaptive, self-reporting, and self-healing dielectrics in the field of electrical insulation, and illuminating studies on smart polymers with autonomous functions in other fields are both introduced. The principles, methods, mechanisms, applications, and challenges of these materials are also briefly presented.

17 citations

Proceedings ArticleDOI
27 Jul 2014
TL;DR: In this paper, the authors present a computationally efficient approach to estimate cascading failure risk in power systems using the previously published Random Chemistry algorithm to find combinations of branch outages that lead to large blackouts, and then estimates risk by computing the expected blackout size based on the probabilities of various contingencies.
Abstract: This paper presents a computationally efficient approach to estimate cascading failure risk in power systems. The method uses the previously published Random Chemistry algorithm [1] to find combinations of branch outages that lead to large blackouts, and then estimates risk by computing the expected blackout size based on the probabilities of various contingencies. We compare this method with Monte Carlo simulation, and show that the method is at least an order of magnitude faster than Monte Carlo simulation. Results from the IEEE RTS-96 and the 2383-bus Polish grid are presented in the paper.

17 citations

Proceedings ArticleDOI
10 Jun 2013
TL;DR: In this paper, a controller is suggested which explicitly handles the requirements for the failure scenarios, in addition to existing load reduction, which will reduce the fuel consumption and reduce the overload and recover the plant.
Abstract: Diesel-electric propulsion is often used for vessels with dynamic positioning systems. For such vessels any single point failure should not lead to loss of position. One failure case is that a generator set is suddenly disconnected. This loss of a power producer gives a drop of the power bus frequency. A blackout will occur if the frequency drops too much, it is therefore required to keep the frequency high enough to withstand such a failure. Load reduction is often used to avoid blackouts due to such faults. The power management system will detect that a fault has occurred, and will reduce the load of some consumers to reduce the overload and recover the plant. In this paper, a controller is suggested which explicitly handle the requirements for the failure scenarios. This method is a practical approach to handle the safety requirements, in addition to existing load reduction. The plant can run with fewer connected generator sets by better control of the safety requirements, which will reduce the fuel consumption.

17 citations

Proceedings ArticleDOI
16 Jul 2007
TL;DR: In this paper, the computational efficiency property of angle modulated particle swarm optimization is utilized to find some efficient islanding solutions for large-scale power systems, which are referred to as optimal according to a fitness function considering the real power balance between generations and loads in islands, the relative importance of customers, and the desired number of islands.
Abstract: Power system defensive islanding is an efficient way to avoid catastrophic wide area blackouts, such as the 2003 North American blackout. Finding defensive islands of large scale power systems is a combinatorial explosion problem. Thus, it is very difficult to find an optimal solution, if it exists, within reasonable time using analytical methods. This paper proposes utilizing the computational efficiency property of an angle modulated particle swarm optimization to find some efficient islanding solutions for large scale power systems. The solutions are referred to as optimal according to a fitness function considering the real power balance between generations and loads in islands, the relative importance of customers, and the desired number of islands. The algorithm can also provide necessary load shedding information. Furthermore, the algorithm can provide a number of candidate solutions for the check of transmission system capacity constraint. Simulations with power systems of different scales demonstrate the accuracy and effectiveness of the proposed algorithm.

17 citations

Proceedings ArticleDOI
01 Jun 2015
TL;DR: This paper presents an on-line voltage security assessment scheme using periodically updated random forest-based decision trees and demonstrated the proposed method on the modified 53-bus IEEE power system.
Abstract: Voltage collapse is a critical problem that impacts power system operational security. Timely and accurate assessment of voltage security is necessary to detect alarm states in order to prevent a large-scale blackout. This paper presents an on-line voltage security assessment scheme using periodically updated random forest-based decision trees. We demonstrated the proposed method on the modified 53-bus IEEE power system. Results are presented and discussed.

17 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023178
2022355
202191
2020120
2019121
2018132