CARMA Model-Based Inertia Estimation Method for Power System with Renewable Energy Integration

In the trend of increasing number and capacity of wind power, photovoltaic and other non-synchronous power access, the power grid is gradually showing the characteristics of low inertia with renewable energy sources, and the lack of inertia support capacity will cause serious threats to the safe operation of the power systems. Therefore, it is important to effectively evaluate the inertia level of the power system with renewable energy integration to ensure the stable system operation. In view of this, this paper proposes a Controlled Auto Regressive Moving Average (CARMA) model-based inertia estimation method for renewable energy integrated power systems. The least squares iterative algorithm is applied to identify the unknown parameters in the CARMA model, which can effectively estimate the power system inertia with fast and accurate performance. Finally, the effectiveness and reliability of the method are verified through case analysis.