Resilience-Oriented Pre-Hurricane Resource Allocation in Distribution Systems Considering Electric Buses

Gao, Haixiang; Chen, Ying; Mei, Shengwei; Huang, Shaowei; Xu, Yin

doi:10.1109/jproc.2017.2666548

Cited by 190 publications

(100 citation statements)

References 61 publications

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“…Prior work is done in [5], where microgrids are used to restore loads based on the analysis of their ability to supply loads. In [34], pre-hurricane resource allocation is considered which helps to improve the effectiveness of load restoration after a hurricane occurs. In these prior works, the uncertainty of sustainable sources is carefully considered and modeled.…”

Section: Discussionmentioning

confidence: 99%

An Input-to-State Stability-Based Load Restoration Approach for Isolated Power Systems

Qin

Gao

et al. 2018

Energies

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An isolated power system (IPS) is usually operated under a bad environment and is influenced by external disturbances. Advanced load restoration technology is an important way to enhance the survivability and reliability of IPS. This paper proposes a fast load restoration approach based on Input-to-State Stability (ISS) theory for IPS. The method can recover load after an outage happens in an IPS under severe perturbations. In the proposed restoration approach, both stability and security constraints are considered based on the ISS theory, which can guarantee the stable and secure operation of IPS during the restoration dynamic process. These constraints have good adaptability for topology transformation and operation status transition of IPS. A heuristic approach to efficiently solve the load restoration problem is proposed, where bisection search is used to check the feasibility of the loads to be restored. Case studies on a typical IPS are used to verify the proposed method.

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Section: Discussionmentioning

confidence: 99%

An Input-to-State Stability-Based Load Restoration Approach for Isolated Power Systems

Qin

Gao

et al. 2018

Energies

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“…Equation (19) guarantees the necessary condition for radiality. Equation (20) represents the damaged branch status. Constraints (21) and (22) describe the active and reactive power balance at bus i.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…10-(a). At t = 6, new damage to branch (19,20) occurs, and the distribution system #3 is reconfigured to new topology with opening switches (4, 5), (6,7), (13,14), as shown in Fig. 10-(b).…”

Section: (B) Impact Of Damage and Repair To Branchesmentioning

confidence: 99%

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Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration

Yao

Wang

Liu

et al. 2020

IEEE Trans. Smart Grid

149

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in scenario s, otherwise set to 0. P t,s G,i , Q t,s G,i Real/reactive power generation at bus i in interval t in scenario s. P t,s r,i , Q t,s r,i Load restoration at bus i in interval t in scenario s. P t,s ij , Q t,s ij Real/reactive power of branch (i, j) in scenario s. v t,s i Voltage magnitude at bus i in interval t in scenario s. P t,s G,m , Q t,s G,m Aggregated active/reactive power in microgrid m in scenario s. P t,s DG,m , Q t,s DG,m Active/reactive power generation of equivalent dispatchable DG in microgrid m in scenario s. P t,s d,m and Q t,s d,m Active/reactive load in microgrid m in scenario s. E t,s DG,m Energy of equivalent dispatchable DG by the end of interval t in scenario s.

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“…Only several publications, e.g., [9], co-optimize RC dispatch with DS restoration. As for MPSs, in [10], [11] and [12], MESSs are dispatched to reduce DS operation cost, improve reliability, and enhance preparedness against natural disasters, respectively. Review on MEGs can be found in [13].…”

mentioning

confidence: 99%

Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration With Repair Crew and Mobile Power Source Dispatch

Lei

Chen

et al. 2019

IEEE Trans. Smart Grid

238

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Repair crews(RCs) and mobile power sources(MPSs) are critical resources for distribution system (DS) outage management after a natural disaster. However, their logistics is not well investigated. We propose a resilient scheme for disaster recovery logistics to co-optimize DS restoration with dispatch of RCs and MPSs. A novel co-optimization model is formulated to route RCs and MPSs in the transportation network, schedule them in the DS, and reconfigure the DS for microgrid formation coordinately, etc. The model incorporates different timescales of DS restoration and RC/MPS dispatch, the coupling of transportation and power networks, etc. To ensure radiality of the DS with variable physical structure and MPS allocation, we also model topology constraints based on the concept of spanning forest. The model is convexified equivalently and linearized into a mixed-integer linear programming. To reduce its computation time, preprocessing methods are proposed to pre-assign a minimal set of repair tasks to depots and reduce the number of candidate nodes for MPS connection. Resilient recovery strategies thus are generated to enhance service restoration, especially by dynamic formation of microgrids that are powered by MPSs and topologized by repair actions of RCs and network reconfiguration of the DS. Case studies demonstrate the proposed methodology.

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Resilience-Oriented Pre-Hurricane Resource Allocation in Distribution Systems Considering Electric Buses

Cited by 190 publications

References 61 publications

An Input-to-State Stability-Based Load Restoration Approach for Isolated Power Systems

An Input-to-State Stability-Based Load Restoration Approach for Isolated Power Systems

Rolling Optimization of Mobile Energy Storage Fleets for Resilient Service Restoration

Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration With Repair Crew and Mobile Power Source Dispatch

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