Rare and extreme climate events may result in wide power outages or blackouts. The concept of power system resilience has been introduced for focusing on high-impact and low-probability (HILP) events such as a hurricane, heavy snow, and floods. Power system resilience is the ability of a system to reduce the likelihood of blackout or wide power outages due to HILP events. Indeed, in a resilient power system, as the severity of HILP events increases, the rate (but not the amount) of unserved loads diminishes. Suitable measures for managing power system resilience can be classified into three categories in terms of time, known as “resilience-based planning,” “resilience-based response,” and “resilience-based restoration.” The most widely used approaches, methods, and techniques in each of these categories, as well as the future trends for improving the power system resilience are reviewed in this article. The challenges of resilience in power systems with high penetration of renewable energy sources are also discussed in each of these categories.

Hybrid AC–DC microgrid is introduced as the future distribution network to utilise both benefits of alternative and direct currents. In such hybrid microgrid, AC and DC loads, renewable‐based distributed generators (DGs), controllable DGs and energy storage systems are connected through separate AC and DC links. An up–down operation model of such hybrid microgrid is proposed which consists of system‐ and device‐level. In the system‐level, a mixed integer linear model is suggested to balance the generation and load considering the interconnection of AC and DC subgrids for minimising total operating cost of the system in a 24‐hour period. In the device‐level, a controller is suggested for power converter‐based resources (i.e. intergrid inverter and battery) for controlling the voltage variations in AC and DC subgrids. The effectiveness of the proposed up–down operation model is demonstrated through simulation studies on a test hybrid microgrid.

An important benefit of demand response (DR) is avoided need to build power plants to serve heightened demand that occurs in just a few hours per year. There are two basic categories of DR options: price-based and incentive-based DR programs. In this paper, both categories of DR measures are modeled based on the demand-price elasticity concept. It has been shown that customers' reaction against implementing price-based or incentive-based DR programs are not similar, so that incentive-based programs have key impact on customer habit formation in response to DR programs. An improved DR model is developed which considers the customer's behavior. The proposed model extinguishes between customers' behavior with respect to electricity price change and his/her behavior against variation of incentive. The performance of the model has been justified by implementation on the IEEE reliability test system.

Demand response (DR) programs enable the demand side to actively optimize its consumption in response to the dynamic prices. The flexibility of consumption can be a useful tool for the electricity market to resolve many of its operation and reliability issues. Several models have been proposed in the literature to explain the human behavior aspect of the customers. These models are based on the classical utility function, but some studies have shown that the price effect on the customer's decision in areas like energy efficiency and consumption reduction depends upon many behavioral characteristics and without considering such characteristics, the results are unrealistic. Thus, loss aversion plays a crucial role in the decision making. So, in this paper, the impact of two time based rate DR programs have been investigated on the peak reduction considering the loss-aversion and its impact on the perception of the customers. Real time pricing and peak time rebate are two competing alternatives for peak reduction. A modified price elasticity based DR model is proposed to simulate the price response of the customers in the presence of both DR programs. MATLAB software is used to implement the DR models. The models are examined on one of the summer days of 2014 in Connecticut. The data is reported by New England ISO. Two PTR cases are generated for this study, with and without considering the loss aversion. Under both scenarios, without considering the loss aversion, PTR has advantages over RTP, but considering the loss-aversion, RTP showed a superior performance. It is shown that the behavioral characteristics of the customers, loss-aversion in this case, is indispensable in the selection of the proper program.

AC-DC hybrid microgrid (HMG) is introduced as the future distribution network to utilize both benefits of alternative and direct currents. Generally, HMG is consisted of ac and dc loads, renewable energy-based distributed generators (DGs), controllable DGs and energy storage systems, and a utility interactive inverter (UII), which provides a bi-directional connection between ac and dc subsystems. In this paper, a inductor, transformer, capacitor, and inductor (LTC-L) topology for the UII has been proposed for managing the power quality of ac subsystem of the HMG. The control strategy of the UII is flexibly changed based on the operating-mode of the HMG. Using the proposed control strategy of the UII in grid-connected mode, not only the voltage quality of the ac-subsystem will be improved, but also the quality of the grid current will be enhanced, considerably. In standalone mode, UII acts as an uninterruptable power supply to minimize the shedding of ac or dc loads. A voltage-current cascaded control structure is used for employing the proposed control strategies. Moreover, two control approaches are investigated on the proposed LTC-L topology of UII, sinusoidal voltage reference (supplying load with pure sinusoidal voltage) and nonsinusoidal voltage reference (supplying load with nonsinusoidal voltage for mitigating grid current harmonics). Effectiveness of the proposed topology and the control strategies are evaluated through a numerical study and discussing the results.