Description:
•A new reintegration-driven ICI framework, called R-ICI, is proposed.•The proposed R-ICI model improves frequency stability of islands using ESSs.•Transient voltage stability of islands is improved using ESSs and SVCs.•The interaction between frequency and voltage is considered by a linear IFR model.•An active/reactive charging and discharging scheme is introduced for ESSs. In this paper, a reintegration-based multi-objective intentional controlled islanding (ICI) model is proposed to enhance resiliency of electrical power systems under catastrophic events. This remedial measure plan relies on a mixed-integer linear programming model with two objective functions including reintegration risk and total load shedding value. While ensuring that each island includes only coherent generators, the proposed multi-objective model solves the controlled islanding problem using lexicographic optimization approach. To ease the islands’ reintegration, charging reactive power, reliability, capacity, and power flow disruption of transmission lines are considered in the model. After implementation of controlled islanding, each resulted island may face temporary active/reactive load-generation imbalance, which may put the islands at the risk of frequency instability, transient voltage instability or a combination of both. The proposed model reduces these risks by modeling energy storage systems (ESSs) and static VAR compensators (SVCs) as fast corrective control actions. In addition to modeling voltage dependent loads in the controlled islanding problem, a linear island frequency response (IFR) model is proposed for frequency stability assessment. The test results of the proposed ICI model on the IEEE 39-bus and IEEE 118-bus test systems demonstrate its performance.
Description:
Summary 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. 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.