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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.

This paper analyzes the notion of resilience in power systems from a fundamental viewpoint and thoroughly examines its practical implications. This paper aims to describe and classify different high-impact rare (HR) events, provide a more technical definition of power system resilience, and discuss linkages between resilience and other well-established concepts, such as security and reliability. Most relevant decisions of system operators in the face of HR events involve a significant level of stress and strain. In order to make informed decisions within this context, it is crucial to have an all-inclusive picture of the state of the system. This paper provides an appropriate framework that not only characterizes the various states of the system but also derives informed decisions from a resilience-oriented perspective. It also describes and analyzes diverse resilience improvement strategies. Comprehensive models and classifications are provided to clearly capture various aspects of power system resilience.

This letter proposes a proactive scheduling for resilience enhancement of microgrids (MGs). Just ahead of the flood arrival, the MG is shifted to a state less impacted and stressed by the upcoming event. To do this, vulnerable components are first recognized. Tripping out all vulnerable components, proactive measures are employed to minimize the preventive load curtailment. The solution is then applied as the proactive schedule of MG which is robust against the flood threat. The effectiveness of the proposed method is examined on a real-scale MG.

Public-lighting is a prominent subsector of the electricity distribution network. Removing upcoming challenges of the public-lighting system is an important necessity in network expansion planning. The public-lighting management structure is composed of three main participants: the regulatory unit, lighting managers, and private contractors. Each participant faces challenges in achieving its aims. This study investigates challenges in the areas of human resource management, cost estimation, price assignment, and time scheduling for private-sector contracting. Applying the reliability model of public-lighting lamps, the health status of lamps during the system operation is forecasted. In addition, to give a comprehensive solution for the mentioned challenges, the proposed strategies are optimized in terms of cost and risk. The results of this case study of the public-lighting system demonstrate the efficiency of the proposed method in alleviating the challenges of public-lighting managers, including optimal assignment of price and duration of contracts. In addition, the operating cost of the public-lighting system, an important challenge for lighting contractors, is minimized via a human resource management scheme.

In this paper, an asset-management model is proposed to address challenges facing regulators, managers, and operators of public-lighting systems and suggest optimal performance strategies. A new method is presented to estimate the failure rate of lamps based on the normal distribution function. The impact of technology improvement in lamp manufacturing as well as the growth and extension of lighting systems on the failure rate are investigated. In order to achieve satisfaction of customers and risk reduction, a method for establishing a performance standard for lamp failure rates is presented. Considering technical and economic issues, a procedure for selecting the best lamp in the market and then estimating costs associated with system operation is described. Finally, a methodology is proposed for evaluating performance in public-lighting systems. Results of a case study for the public-lighting system of the newly constructed suburb of the city of Isfahan, Iran, show the efficacy of the proposed method.

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.

This paper evaluates the effect of possible energy policy changes on multi-objective optimal design and planning of a hybrid energy system. The study was performed for a remote area near Esfarjan, a village located in Shahreza, Iran. In the main scenario, the current energy policy is examined, while the sensitivity analysis scenario applies the near future condition that is gradually taking place by reducing the energy subsidies. Simulations have been done on six different system configurations for the both scenarios considering the two mentioned policies for electricity price, fuel price and environmental issues. Results show that in sensitivity scenario, in contrast with the main scenario, the renewable-grid configuration is more economical than the grid-only dependent system, which in turn will result in more interest in investing on renewable resources. Finally, the energy modeling software for hybrid renewable energy systems, HOMER is used in this study.

This paper investigates the optimal management of a renewable based energy supply design for a residential building equipped with smart communication and metering infrastructures, approaching the smart home (SH) concept. The best economically optimal model is selected in each case based on the net present cost (NPC) and the cost of energy (COE) criteria. Mutual effects of the inflation rate uncertainty, project lifetime span and a comparative model to study the use of combined heat and power (CHP) technology on the objective function have been modelled. An economic index related to environmental issues and one related to the thermal load supply have been defined and analysed. Finally a conclusion has been done according to results achieved throughout the study.