A Review of Uncertainty Modelling Techniques for Probabilistic Stability Analysis of Renewable-Rich Power Systems

In pursuit of identifying the most accurate and efficient uncertainty modelling (UM) techniques, this paper provides an extensive review and classification of the available UM techniques for probabilistic power system stability analysis. The increased penetration of system uncertainties related to renewable energy sources, new types of loads and their fluctuations, and deregulation of the electricity markets necessitates probabilistic power system analysis. The abovementioned factors significantly affect the power system stability, which requires computationally intensive simulation, including frequency, voltage, transient, and small disturbance stability. Altogether 40 UM techniques are collated with their characteristics, advantages, disadvantages, and application areas, particularly highlighting their accuracy and efficiency (as both are crucial for power system stability applications). This review recommends the most accurate and efficient UM techniques that could be used for probabilistic stability analysis of renewable-rich power systems.

Automated summary

In order to find the most accurate and efficient techniques for uncertainty modelling (UM) in power system stability analysis, this paper provides a comprehensive review and classification of the available UM techniques. The increasing uncertainties in power systems resulting from renewable energy sources, new loads, and deregulation of electricity markets make probabilistic power system analysis necessary. These factors significantly impact power system stability, requiring computationally intensive simulations including frequency, voltage, transient, and small disturbance stability. A total of 40 UM techniques are collated, providing their characteristics, advantages, disadvantages, and application areas, with a particular focus on accuracy and efficiency. The review recommends the most accurate and efficient UM techniques for probabilistic stability analysis in power systems with a high penetration of renewable energy.