Networked microgrids for service restoration in resilient distribution systems

Arif, Anmar; Wang, Zhaoyu

doi:10.1049/iet-gtd.2017.0380

Cited by 130 publications

(88 citation statements)

References 22 publications

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“…The dynamic constraints are considered in [12]. In [15]- [19], the restoration strategies are based on sectionalizing the outage area of a distribution system into several MGs. In [16], a framework is developed to dynamically change the boundaries of MGs for fault isolation and load restoration.…”

Section: Set Of Phases Of Busmentioning

confidence: 99%

Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Wang

et al. 2019

IEEE Trans. Smart Grid

212

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When a major outage occurs on a distribution system due to extreme events, microgrids, distributed generators, and other local resources can be used to restore critical loads and enhance resiliency. This paper proposes a decision-making method to determine the optimal restoration strategy coordinating multiple sources to serve critical loads after blackouts. The critical load restoration problem is solved by a two-stage method with the first stage deciding the post-restoration topology and the second stage determining the set of loads to be restored and the outputs of sources. In the second stage, the problem is formulated as a mixed-integer semidefinite program. The objective is maximizing the number of loads restored, weighted by their priority. The unbalanced three-phase power flow constraint and other operational constraints are considered. An iterative algorithm is proposed to deal with integer variables and can attain the global optimum of the critical load restoration problem by solving a few semidefinite programs in most cases. The effectiveness of the proposed method is validated by numerical simulation with the modified IEEE 13-node test feeder and the modified IEEE 123-node test feeder under plenty of scenarios. The results indicate that the optimal restoration strategy can be determined efficiently in most scenarios.

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Section: Set Of Phases Of Busmentioning

confidence: 99%

Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Wang

et al. 2019

IEEE Trans. Smart Grid

212

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“…Therefore, DG is an important guarantee for both aspects. 2,3,23 By optimizing the allocation and size of DG and post-disaster network reconfiguration, structure resilience and the restoration of loads can be enhanced. To estimate the three abilities of resilience on prevention, defence, and restoration, eight quantitative evaluation indicators of resilience are presented from two levels on power sources and loads, including the node degree of DG buses, survival rate, and recovery ability.…”

Section: The Resilience Evaluation Indicators Of Distribution Systemsmentioning

confidence: 99%

A novel planning‐attack‐reconfiguration method for enhancing resilience of distribution systems considering the whole process of resiliency

Wang

et al. 2019

Int Trans Electr Energ Syst

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Summary To enhance the resilience of distribution systems and fight against extreme disasters, a novel planning‐attack‐reconfiguration optimization method is proposed in this paper. Firstly, according to the processes of prevention, defence, and restoration for a resilient distribution system through disruption, the novel resilience evaluation indicators are presented, which include the node degree of distributed generation (DG) bus, survival rate, and recovery ability. Secondly, a novel planning‐attack‐reconfiguration optimization model is developed to improve the resilience of distribution systems. In DG planning stage, the multi‐objective planning model is formulated, which includes the minimization of the total cost of investment and operation, and the maximization of the node degree of DG buses for critical loads. In the attack stage, a clear worst case of N‐k contingencies on the basis of generalized nodes is presented to reduce the computational complexity. Then, the post‐disaster network reconfiguration model is formulated to maximize the restoration rate of critical loads (RRCL). Finally, the proposed method is illustrated by the case study on PG&E 69‐bus distribution system. The simulation results indicate that all the RRCL can reach about 90% in the four multipoint fault scenarios. Meanwhile, other evaluation indicators are greatly improved. It is shown that the resilience of distribution systems can be dramatically enhanced by the proposed method.

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“…Once a contingency occurs, ESS aggregator passes an alarm message to the ESSs located in the interrupted zones and the backup feeders of the faulted feeder, requesting their available power for participating in the service restoration process. Afterwards, the microcontrollers of each ESS calculates the amount of exploitable power for service restoration considering the maximum and minimum allowable state of charge of batteries and the amount of required power for local demands . Subsequently, the ESSs respond to the aggregator's message declaring their available power for the service restoration process.…”

Section: Ess Incorporation In Service Restoration Processmentioning

confidence: 99%

“…Afterwards, the microcontrollers of each ESS calculates the amount of exploitable power for service restoration considering the maximum and minimum allowable state of charge of batteries and the amount of required power for local demands. 30 Subsequently, the ESSs respond to the aggregator's message declaring their available power for the service restoration process. Then, the outage management system (OMS) receives the participation data of ESSs from the aggregator and determines the optimal dispatch of the ESSs during the repair time of the faulted section.…”

Section: Ess Incorporation In Service Restoration Processmentioning

confidence: 99%

“…In addition, some load points might not be energized fully or partially in restoration process because of several problems including voltage drop in restored busses and the backup feeder overloading. Thus, an auxiliary variable that indicates interruption status of load points (Int ijt ) should be used to determine the restored load points (29) and (30). As explained in Section 4.1, Int ijt indicates the interruption status of ith load point, in tth hour of repair time of the jth contingency.…”

Section: Power Balance Equationsmentioning

confidence: 99%

See 1 more Smart Citation

Reliability improvement in smart grid through incorporating energy storage systems in service restoration

Abniki

Taghvaei²,

Mohammadi‐Hosseininejad

2018

Int Trans Electr Energ Syst

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Summary Smart grid has been developing nowadays as an initiative to operate modern electric distribution systems (EDSs) in a more reliable and efficient manner. With the decreasing price of the energy storage systems (ESSs), ESSs are highly recommended to be exploited in the operation of EDSs. In this manuscript, a comprehensive framework is introduced for ESS incorporation in service restoration process which proposes 2 roles for ESSs in the service restoration. As the first role, ESSs are exploited in the service restoration to re‐energize customers in interrupted zones, as their backup units. As the second role, ESSs are used in the service restoration to increase the number of interrupted customers which transferred to the backup feeders through acting as storage units. The proposed objective function of service restoration consists of customer interruption cost, energy not sold cost, cost of electricity production in combined heat and power units, and cost of ESS incorporation in service restoration. Moreover, the stochastic characteristics of ESS contribution in service restoration are considered in the proposed problem formulation. Further, the impacts of the uncertainties of the service restoration on the proposed approach for ESS incorporation are investigated. The effectiveness of the proposed methodology is deliberated using a standard reliability test system (RBTS‐4). The obtained results show that the incorporating ESSs as storage units will lead to substantially improve the reliability level of EDS through increasing the adequacy of the EDS during service restoration process.

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Networked microgrids for service restoration in resilient distribution systems

Cited by 130 publications

References 22 publications

Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

Coordinating Multiple Sources for Service Restoration to Enhance Resilience of Distribution Systems

A novel planning‐attack‐reconfiguration method for enhancing resilience of distribution systems considering the whole process of resiliency

Reliability improvement in smart grid through incorporating energy storage systems in service restoration

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