Incorporating energy storage and demand response into intentional controlled islanding using time decomposition

Abstract

To improve electrical energy system resilience under catastrophic events, an efficient intentional controlled islanding (ICI) model is proposed in this article. The proposed remedial action relies on a new mixed integer linear programming (MILP) model which aims at minimizing the overall energy curtailment, power flow disruption, and generation and demand re-dispatches through a cost-based objective function. Another innovative characteristic of this model is demand response (DR) inclusion in the proposed ICI. To improve the balance between demand and supply of electricity, DR can be employed as an effective strategy in the ICI problem. In addition, another main original feature of the proposed model is considering energy storage units (ESUs) in each resulted island after the splitting process. To provide enough time for the system operator to re-dispatch the islands and to improve frequency stability of islands, a charging/discharging scheme is proposed for ESUs during ICI. Moreover, a new time decomposition is proposed to accurately model the fast and slow corrective actions considering their interactions. Using this time decomposition, energy curtailments, considering their period durations, are treated as decision variables in the ICI problem to minimize involuntary load shedding as the most expensive corrective action. The results of scrutinizing the proposed ICI framework on the IEEE 118-bus test system illustrate its performance. In addition, the results of the proposed ICI approach are compared with the results of other ICI models to illustrate the effectiveness of the new features of the proposed approach.