Maintaining Electric System Safety Through An Enhanced Network Resilience

Dehghanian, Pooria; Aslan, Semih; Dehghanian, Payman

doi:10.1109/tia.2018.2828389

Cited by 99 publications

(30 citation statements)

References 25 publications

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“…Despite the potential benefits of the Shapley Value approach, it is not a common allocation method for real-sized problems, due to the computational requirements it dictates, and, hence, would be regarded as the benchmark solutions for performance comparisons. Further simplifications of the Shapley Value may be needed for specific classes of problems (such as real-time applications for power grid monitoring, control, and resilience [40]) to enhance the computational efficiency concerns, and this can be a future research direction to pave.…”

Section: Discussionmentioning

confidence: 99%

A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations

Pourahmadi

Dehghanian

2018

Mathematics

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Allocation of the power losses to distributed generators and consumers has been a challenging concern for decades in restructured power systems. This paper proposes a promising approach for loss allocation in power distribution systems based on a cooperative concept of game-theory, named Shapley Value allocation. The proposed solution is a generic approach, applicable to both radial and meshed distribution systems as well as those with high penetration of renewables and DG units. With several different methods for distribution system loss allocation, the suggested method has been shown to be a straight-forward and efficient criterion for performance comparisons. The suggested loss allocation approach is numerically investigated, the results of which are presented for two distribution systems and its performance is compared with those obtained by other methodologies.

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Section: Discussionmentioning

confidence: 99%

A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations

Pourahmadi

Dehghanian

2018

Mathematics

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“…It is assumed that two MEGs can be allocated in this system, and their capacities are bounded in 100~400kW due to the technical limits. The capital cost of MEGs is assumed to be $30/kW/year with 10-year life time [5], and the penalty cost for load curtailments is $14/kWh [41]. Moreover, the travel time between candidate nodes for MEG connection is 2~8h, and the reparation time of damaged components is set as 12h.…”

Section: A Simulations On Ieee 13-node Distribution Systemmentioning

confidence: 99%

Mobile Emergency Generator Planning in Resilient Distribution Systems: A Three-Stage Stochastic Model With Nonanticipativity Constraints

Zhang

et al. 2020

IEEE Trans. Smart Grid

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Mobile emergency generators (MEGs) can effectively restore critical loads as flexible backup resources after power network disturbance from extreme events, thereby boosting the distribution system resilience. Therefore, MEGs are required to be optimally allocated and utilized. For this purpose, a novel threestage stochastic planning model is proposed for MEG allocation of resilient distribution systems in consideration of planning stage (PLS), preventive response stage (PRS) and emergency response stage (ERS). Moreover, the nonanticipativity constraints are proposed to guarantee that the MEG allocation decisions are dependent on the stage-based uncertainties. Specifically, in the PLS, the intensity uncertainty (IU) of disasters and the outage uncertainty (OU) incurred by a given disaster are considered with probabilityweighted scenarios for the effective MEG allocation. Then, with the IU that can be observed in the PRS, the MEGs are pre-positioned in the consideration of OU. It is noted that the preposition decisions should only correspond to the IU realizations, according to nonanticipativity constraints. Last, with the further realization of OU in the ERS, the MEGs are rerouted from the preposition to the target location, so that the provisional microgrids can be formed to restore critical loads. The proposed planning model can be large-scale due to multiple scenarios. Therefore, the progressive hedging algorithm (PHA) is customized to reduce the computational burden. The simulation results in 13 and 123 node distribution systems show the effectiveness and superiority of the proposed three-stage MEG planning model over the traditional two-stage model.

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“…10, respectively. From (18) and (19), the ideal effectiveness can be worked out via assuming POC 0 = Δ(PFW) = 1, i.e. E i j ideal (t) = PTW i j (t).…”

Section: Factitious Effectivenessmentioning

confidence: 99%

“…To mitigate weather impacts, a fuzzy logic system for distribution outage predictions is devised in [1]. A restoration strategy which aims at improving the resilience of the power grid in extreme emergencies is proposed by Dehghanian et al [19]. In [20], the time-varying failure rate of transmission lines is calculated to reflect the time-dependent regulation.…”

Section: Introductionmentioning

confidence: 99%

Early warning system for spatiotemporal prediction of fault events in a power transmission system

Sun

Wang

Zheng

et al. 2019

IET Generation, Transmission & Distribution

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Maintaining Electric System Safety Through An Enhanced Network Resilience

Cited by 99 publications

References 25 publications

A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations

A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations

Mobile Emergency Generator Planning in Resilient Distribution Systems: A Three-Stage Stochastic Model With Nonanticipativity Constraints

Early warning system for spatiotemporal prediction of fault events in a power transmission system

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