Islanding Detection Methods for Distributed Generation Systems

Islanding occurs when a segment of the distribution network, powered by one or more distributed generators (DGs), becomes electrically isolated from the main grid while still energising local loads. Accurate and rapid detection of this condition is essential to prevent equipment damage, ensure personnel safety and maintain power quality. Detection techniques fall into passive schemes, which monitor local voltage or frequency deviations but often suffer from sizeable non-detection zones (NDZs), and active schemes, which inject deliberate disturbances—such as small power curtailments or frequency shifts—to provoke detectable changes during islanding. Hybrid approaches combine passive and active elements to balance detection speed, reliability and power quality. Recent advances exploit high‐resolution measurements from phasor measurement units, advanced signal‐processing (for example wavelet transforms) and computational intelligence methods, including neural networks and deep-learning architectures. These methods aim to achieve zero NDZ, sub-second detection times and minimal impact on normal operation. The proliferation of microgrids and inverter-based renewables has driven global research towards decentralised, communication-efficient detection frameworks that integrate Internet-of-Things platforms and cloud-based analytics to bolster resilience and scalability.

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Islanding Detection Methods for Distributed Generation Systems publication trend

The graph below shows the total number of articles in islanding detection methods for distributed generation systems across all publications each year (not limited to Nature Index journals).

Technical terms

Distributed generation: Small-scale electricity generation located close to load centres, often from renewable sources.

Islanding: Condition where a portion of the grid containing DGs becomes electrically isolated yet remains energised.

Non-detection zone (NDZ): Range of operating conditions in which an islanding event may not be detected.

Maximum power point tracking (MPPT): Algorithm regulating the operating point of photovoltaic inverters to extract maximal power.

Phasor measurement unit (PMU): Device providing time-synchronised measurements of voltage and current phasors.

Artificial neural network (ANN): Computational model inspired by biological neural networks, used for classification tasks.

Long short-term memory (LSTM) network: Recurrent neural network architecture designed to capture long-term temporal dependencies.

Droop control: Decentralised control strategy adjusting inverter output frequency and voltage based on active and reactive power.

References

1. Two-stage active power curtailment-based islanding detection technique for photovoltaic-based microgrids with zero non-detection zone. Sustainable Energy Technologies and Assessments (2024).
2. Comprehensive Review of Islanding Detection Methods for Distributed Generation Systems. Energies (2019).
3. Islanding Detection of Microgrid Incorporating Inverter Based DGs Using Long Short-Term Memory Network. IEEE Access (2020).
4. Hierarchical Control of Microgrid Using IoT and Machine Learning Based Islanding Detection. IEEE Access (2021).