Proactive Resilience of Power Systems Against Natural Disasters: A Literature Review

Mohamed, Mohamed A.; Chen, Tao; Su, Wencong; Jin, Tao

doi:10.1109/access.2019.2952362

Cited by 114 publications

(80 citation statements)

References 137 publications

(109 reference statements)

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“…These power outages occur for a variety of reasons, that range from natural events to intentional attacks on the power supply. A recent paper found that between 2012 and 2016, over 96.2% of power outages occurred due to the impact of severe weather [2] on transmission, and to a greater extent, on distribution networks [3]. Storms and hurricanes account for the vast majority of these outages.…”

Section: Indices Tmentioning

confidence: 99%

“…Storms and hurricanes account for the vast majority of these outages. Resilience of a system can be defined as its ability to prepare, predict, sustain and recover from an outage [3]. This definition is applicable to the power system as a whole or one of its components, such as a household.…”

Section: Indices Tmentioning

confidence: 99%

“…There is a growing literature on system level power sector resilience as the frequency and intensity of major storms are on the rise, e.g., [3]. Still, the role of BESS and solar PV is relatively unexplored compared to that of fossil fuel-based generators in providing backup power during storms [3]. As an example, none of the commercially available tools for PV/BESS sizing analysis consider these aspects.…”

Section: Motivation For This Studymentioning

confidence: 99%

“…Duque et al [33] has estimated the coefficients as: β=0.0889 and β0=-6.388 which we have adopted for our case studies. Duque et al [33] have also considered a number of other explanatory variables to power losses including flooding and concluded that gust speed is the only significant one, albeit it is quite possible that power outages in other jurisdictions may require additional considerations [3]. We have represented unusually stormy day power outage probabilities as shown in Figure 1.…”

Section: A Overview Of the Modelmentioning

confidence: 99%

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Battery Storage for Resilient Homes

Chatterji

Bazilian

2020

IEEE Access

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Small-scale battery energy storage systems (BESS), especially for behind-the-meter applications, are still relatively expensive, but we show that it can be a potent solution to render homes resilient to storm related power outages. We present a stochastic programming model formulation to optimize PV/BESS explicitly accounting for resilience benefits these investments entail, over and above their ability to reduce cost of supply. The stochastic optimization considers uncertainties around storm related grid supply failures as well as variability of solar PV. The model includes an embedded Monte Carlo simulation module that considers storm related outage risks using climate model reanalysis data. It is a least-cost planning framework that optimizes selection of BESS, solar PV, grid supply, and diesel generator, from a homeowner's perspective. We present two case studies with low and high storm risks that demonstrate how different risk exposures can impact on the selection of alternative options to build resilience. Duals, or shadow prices, of demand-supply constraints from the model for both normal days and for storm related contingencies, provide interesting insights into the marginal cost of supply that can inform innovative pricing schemes to promote customer level resilience measures. The case study results reveal significant merits of BESS, in combination with PV, to enhance resilience. We find that in low-risk areas like Bethesda, MD, incremental PV and BESS required for a more resilient system can add $79 (4%) to expected annual electricity costs for a typical household, and a considerably higher $208 (10.6%) in Miami, FL which is at a much greater risk. These options are, however, 27% (in Bethesda) and 20% (in Florida) less expensive than the conventional solution of installing a diesel generator. These results provide insights into the value of BESS as part of a resilient and clean energy solution for households.

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Section: Indices Tmentioning

confidence: 99%

Section: Indices Tmentioning

confidence: 99%

Section: Motivation For This Studymentioning

confidence: 99%

Section: A Overview Of the Modelmentioning

confidence: 99%

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Battery Storage for Resilient Homes

Chatterji

Bazilian

2020

IEEE Access

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“…The uncertainty at different stages of PLS, PRS and ERS is another critical factor affecting the MEG planning strategies [22]. Generally, based on the stage of uncertainty realization, the uncertainty to be considered in the resilience-oriented planning can be categorized to intensity uncertainty (IU) of different natural disasters and outage uncertainty (OU) incurred by a given natural disaster [23].…”

Section: Introductionmentioning

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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Novel trends in resilience assessment of a distribution system using synchrophasor application: A literature review

Sonal

Ghosh

2021

Int Trans Electr Energ Syst

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Summary The gradual sprawl of power system toward smart grid and enhanced integration of distributed energy resources at the distribution end is transforming the conventional distribution system and is eventually making it self‐sustained. The distribution system is thus continuously evolving to prepare itself for any unforeseen natural, man‐made, and complex events. These events may impact the distribution system as high‐impact low‐frequency (HILF) scenarios. The high intensity and widespread damage of the power system due to HILF scenarios necessitate resilience. Resilience analysis aims to identify these region‐specific vulnerabilities of the electricity network and implement appropriate methods to quickly restore the system to its predisturbance state. Further to enhance the network visibility and situational awareness, integration of synchrophasor to resilience is significant. Therefore, synchrophasor technology integrated with resilience provides online wide area visibility of the distribution system. Using synchrophasor for resilience assessment propels an agile network for coordinating accurate and timely analysis of the system parameters. Therefore, understanding the concept of resilience, its evolution, detailed overview, synchrophasor‐based resilience (SBR) methods as well as its applications are necessary. This article outlines the key points of the synchrophasor technology based resilience technique, its significance, and lays a foundation for continuing research in this area. It offers detailed insight into the comprehensive review of this evolving concept. The article majorly focuses on all the aspects of SBR, its necessity in performance evaluation, synchrophasor measurement based resilience enhancement methods, and application of different SBR techniques in the distribution system. A detailed comparative analysis of SBR features, sample efficiency, result accuracy, merits, and demerits based on available literature is provided. Finally, future perspectives are discussed for implementing resilience assessment using synchrophasor technology in the distribution system.

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Proactive Resilience of Power Systems Against Natural Disasters: A Literature Review

Cited by 114 publications

References 137 publications

Battery Storage for Resilient Homes

Battery Storage for Resilient Homes

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

Novel trends in resilience assessment of a distribution system using synchrophasor application: A literature review

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