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Proactive preparedness is the key necessity of power systems to successfully cope with high-impact rare (HR) events. A resilience-oriented proactive methodology is proposed in this paper, which aims at enhancing the preparedness of multiple energy carrier microgrids (MECMs) against an approaching hurricane. First, the hurricane-originated contingency chain of MECM is characterized, which is different from that of single energy carrier distribution networks. The contingency chain includes natural gas interruption within the MECM, islanding event, and hurricane landfall on MECM. The pre-event scheduling horizon is then defined from the first alert declaration of hurricane to the worst-case (the earliest instant) of hurricane landfall on MECM. The preparedness index is defined as the sum of electric and thermal energy storage at the end of the scheduling horizon. Enhancing the proposed preparedness index will be at the expense of additional load curtailment during the scheduling horizon. Thus, a compromise is made between the two conflicting objectives (preparedness index and load supply) via a multi-objective optimization problem. An integrated gas and electricity power flow is proposed in a linear computationally efficient fashion capable of modeling gas interruption and islanding event. The effectiveness of the proposed methodology is examined on a real-scale MECM.

Recent extreme weather events have emphasized the need for new methods and metrics to assess the power system resilience in response to high-impact low-probability (HILP) events. Microgrids (MGs) have been instrumental in such occasions for maintaining the power supply continuity to local customers. This paper provides a quantitative framework for assessing the MG resilience in response to HILP windstorms. The proposed framework jointly employs fragility curves of overhead distribution branches and windstorm profile to quantify the degradation in the MG performance (particularly supplied load in this work). The proposed analytical method is simple and computationally efficient which offers a quick means for getting knowledge about adverse impacts of an approaching windstorm and taking preventive measures accordingly. A set of normalized metrics is defined which provides a comparable tool for assessing the resilience in various operating conditions and power systems. The impacts of restorative actions, the system reinforcement, and the event severity on resilience curves and metrics are also investigated. The effectiveness of the proposed approach in response to an extreme windstorm is examined on a real-scale MG test bed.

This paper presents a microgrid (MG) proactive management framework to cope with adverse impacts of extreme windstorms. Upon receiving alerts for the forecasted windstorm, the framework finds a conservative schedule of MG with the minimum number of vulnerable branches in service while total load is served. The schedule ensures the MG normal operation prior to the windstorm while reducing the MG vulnerability at the event onset. The proposed method makes benefit of network reconfiguration, generation reschedule, conservation voltage regulation, optimal parameter settings of droop-controlled units, demand-side resources, and backup generation capacity. A vulnerability index is defined to assess the effectiveness of the proposed proactive management in reducing the MG vulnerability at the event onset. The proposed model is linearized that guarantees simplicity, robustness, and computational efficiency of the solution. The effectiveness of the proposed method is tested on a real-scale MG against a windstorm.

As electric vehicles offer a promising choice to deal with the growing air pollution and the global consumption of fossil fuels in the future smart grids, integrating their full benefit in the power system should be of a high priority. Numerous studies surveyed the possibility of charging/discharging modes of vehicles such as vehicle-to-grid, grid-to vehicle and vehicle-to-building and one introduced a new mode as vehicle-to-vehicle. However, none of them considered all available modes in a study. In the future smart grids, electric vehicles will be integrated with other generation or consumption parts such as distributed energy resources, smart homes and the external grid. As a result, a comprehensive perspective toward the simultaneous scheduling of combined energy exchange modes should be established. In this paper, advantages of 18 energy exchange modes are integrated. The presented model facilitates the participation of sub-aggregators in the aggregation of electric vehicles in a residential complex. The complex consists of a smart building and a smart parking lot. The proposed model promises higher income for sub-aggregators and less energy not charged for vehicles while ensuring the convenience for residents. This will result in more incentive for both sub-aggregators and residents to cooperate.