On the Evaluation of Customers Interruption Costs due to Unexpected Power Outages

Lehtonen, Matti; Gündüz, Niyazi; Küfeoğlu, Sinan

doi:10.1109/rtucon.2018.8659847

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…Moreover, the A customized PHA is proposed to decompose the large-scale nonlinear MEG model to multiple sub-problems with respect to various outage scenarios, which can significantly improve the computational efficiency of the solution method. (42)…”

Section: Discussionmentioning

confidence: 99%

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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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Section: Discussionmentioning

confidence: 99%

“…In this paper, the penalty costs for load interruption are set to be $14/kWh. However, load interruption costs can be up to $57/kWh for some commercial customers in EU countries [42]. Hence, the sensitivity of the MEG planning decision to the load interruption cost is further investigated.…”

Section: ) Demonstration Of the Three-stage Modelmentioning

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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Service Restoration Based on Interruption Loss for Resilient Distribution System Considering Distributed Generations

Han

Zhang

et al. 2020

2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2)

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A Business Model Using Salt Water Battery and PV Panels for Continuity of Supply

Yukselen

Ozbasaran

Tuncer

et al. 2020

2020 International Conference on Smart Grids and Energy Systems (SGES)

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On the Evaluation of Customers Interruption Costs due to Unexpected Power Outages

Cited by 3 publications

References 3 publications

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

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

Service Restoration Based on Interruption Loss for Resilient Distribution System Considering Distributed Generations

A Business Model Using Salt Water Battery and PV Panels for Continuity of Supply

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