Impact of Uncertainties on Resilient Operation of Microgrids: A Data-Driven Approach

Abstract

In this paper, the impact of uncertainties in loads, renewable generation, market price signals, and event occurrence time on the feasible islanding and survivability of microgrids is analyzed. A data-driven approach is proposed for estimating the maximum deviation level of uncertain parameters dynamically based on historical data. Similarly, fragility curves are utilized for determining the preparation time for the potential events based on the estimated event occurrence time and physical constraints of the microgrid components. In addition, a resilience-oriented demand response program is proposed for enhancing the utilization of renewables and other available resources for reducing the load shedding during the emergency period. Finally, a resilience index is proposed for quantifying the benefits of the proposed method for the resilienceoriented operation of microgrids. In normal mode, the impact of event occurrence time and uncertainty level is analyzed via an adaptive robust optimization method. In emergency mode, 10 000 Monte Carlo scenarios of all the uncertain parameters are generated, and their impact on the operation cost, amount of load shed, and the range of the proposed resilience index are analyzed for each case.

Power System Resilience: Current Practices, Challenges, and Future Directions

“…A resilience metric based on the speed of the system response, efficiency of the recovery, and economy of the recovery has been proposed in [48] to quantify system resilience after extreme events. In [49], [50], a resilience metric has been defined as the ratio of recovered loads to the actual loads of AC/DC sides of microgrids. This metric ensures the survivability of at least the most critical loads [49], [50].…”

“…In [49], [50], a resilience metric has been defined as the ratio of recovered loads to the actual loads of AC/DC sides of microgrids. This metric ensures the survivability of at least the most critical loads [49], [50]. Also, it is measured on a scale from zero to one where zero represents the lowest resilient level and one represents the highest level [49], [50].…”

Resilience-Driven Modeling, Operation and Assessment for a Hybrid AC/DC Microgrid

“…However, there is only limited research focusing on the development of resilience-driven operational strategies for AC/DC MGs or DC MGs. In [20]- [22], both feasible islanding and the survivability of critical loads are considered to enhances the resilience of a hybrid MG. Based on above research, a datadriven method is suggested in [23] to estimate the impact of dynamic uncertain bounds on the resilient operation of hybrid MGs and a demand response program is considered to reduce load shedding during emergency period. In [24], a resiliencedriven robust dispatching model is developed to obtain the robust plans in the worst scenario for a hybrid MG with the consideration of uncertain event occurrence time.…”

“…In [30], a preparedness index is developed to calculate the total storage of electrical and thermal before the event onset, which is used to assess the resilience of a distribution system in pre-disturbance phase. In [10], [23], a resilience index is proposed to assess the survivability of loads with different priorities. Similarly, a resilience metric is proposed in [31]- [33] to evaluate the contribution of a optimal strategy on critical load restoration during the restorative phase.…”

“…The optimization problem is posed as a minimization problem, subject to the constraints represented by (3)- (23). Active and reactive power balance equations at each bus b are shown in (3) and (4) and the classical equations pertaining to power flow problems are presented in (5) and (6).…”