A Novel IoT-Based Controlled Islanding Strategy for Enhanced Power System Stability and Resilience

Highlights: What are the main findings? A novel IoT-based intentional controlled islanding strategy was developed as a defensive action against blackout events, enhancing grid resilience by detecting post-disturbance changes in the network. An adaptive coherency index was developed to assess the coherency between generator pairs using real-time PMU measurements, followed by a clustering technique to identify islands and associated generators. A Mixed-Integer Linear Programming (MILP) model was proposed to identify optimal transmission lines for disconnection with minimal power disruption, aiming to create stable islands. Optimal generation rescheduling and/or load shedding were implemented to improve voltage and frequency stability within subsystems. What is the implication of the main finding? The integration of IoT technology in the islanding strategy significantly increases the effectiveness of grid management during disturbances, potentially reducing the likelihood of widespread blackouts. The adaptive coherency index enhances real-time monitoring capabilities, allowing for better decision-making in dynamic grid conditions. The MILP model provides a systematic approach to controlled islanding, which can be applied to real-world scenarios, ensuring stable operations with minimal service interruption. Improved voltage and frequency stability through strategic rescheduling and load shedding contributes to the overall reliability and performance of the power grid. Intentional controlled islanding (ICI) is a crucial strategy to avert power system collapse and blackouts caused by severe disturbances. This paper introduces an innovative IoT-based ICI strategy that identifies the optimal location for system segmentation during emergencies. Initially, the algorithm transmits essential data from phasor measurement units (PMUs) to the IoT cloud. Subsequently, it calculates the coherency index among all pairs of generators. Leveraging IoT technology increases system accessibility, enabling the real-time detection of changes in network topology post-disturbance and allowing the coherency index to adapt accordingly. A novel algorithm is then employed to group coherent generators based on relative coherency index values, eliminating the need to transfer data points elsewhere. The “where to island” subproblem is formulated as a mixed integer linear programming (MILP) model that aims to boost system transient stability by minimizing power flow interruptions in disconnected lines. The model incorporates constraints on generators’ coherency, island connectivity, and node exclusivity. The subsequent layer determines the optimal generation/load actions for each island to prevent system collapse post-separation. Signals from the IoT cloud are relayed to the circuit breakers at the terminals of the optimal cut-set to establish stable isolated islands. Additionally, controllable loads and generation controllers receive signals from the cloud to execute load and/or generation adjustments. The proposed system’s performance is assessed on the IEEE 39-bus system through time-domain simulations on DIgSILENT PowerFactory connected to the ThingSpeak cloud platform. The simulation results demonstrate the effectiveness of the proposed ICI strategy in boosting power system stability.