Abstract:
In low-inertia power systems, the primary frequency response is of great interest. Based on the frequency nadir, the frequency response can be quickly analyzed to see whe...Show MoreMetadata
Abstract:
In low-inertia power systems, the primary frequency response is of great interest. Based on the frequency nadir, the frequency response can be quickly analyzed to see whether it will disrupt the stable operation of the grid, so this paper proposes an online prediction method for the frequency nadir. Firstly, a detailed frequency response model containing converter-based generation to provide frequency support is established, and the model structure is simplified according to the common features of the complex control loops. The simplified model can easily achieve the analytical expression of the frequency nadir so that the frequency nadir prediction can be performed by parameter calculation. In the derived frequency nadir expression, the system parameters that are strongly frequency-dependent, such as inertia, and the simplified frequency regulation parameters are retained. In order to enhance the fit between the frequency nadir prediction and the actual system, these parameters are obtained through online information, where the system parameters are based on online estimation, and the simplified frequency regulation parameters are obtained through parameter identification. Case tests demonstrate the effectiveness of the proposed method and are easy to implement.
Date of Conference: 22-25 September 2023
Date Added to IEEE Xplore: 20 December 2023
ISBN Information:
ISSN Information:
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- IEEE Keywords
- Index Terms
- Power System ,
- Frequency Response ,
- Primary Response ,
- Point Response ,
- Online Prediction ,
- Primary Frequency Response ,
- Converter-based Generation ,
- Simple Model ,
- Parameter Identification ,
- Online Information ,
- Simple Parameters ,
- Utility Grid ,
- Frequency Regulation ,
- Frequency Support ,
- Prediction Model ,
- Neural Network ,
- Machine Learning ,
- Time Constant ,
- Damping ,
- Power Generation ,
- Synchronous Generator ,
- Mechanical Power ,
- Higher-order Model ,
- Deep Belief Network ,
- System Inertia ,
- Data-driven Methods ,
- Dynamic Frequency ,
- Objective Data ,
- Back Propagation Neural Network ,
- Renewable Power Generation
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Power System ,
- Frequency Response ,
- Primary Response ,
- Point Response ,
- Online Prediction ,
- Primary Frequency Response ,
- Converter-based Generation ,
- Simple Model ,
- Parameter Identification ,
- Online Information ,
- Simple Parameters ,
- Utility Grid ,
- Frequency Regulation ,
- Frequency Support ,
- Prediction Model ,
- Neural Network ,
- Machine Learning ,
- Time Constant ,
- Damping ,
- Power Generation ,
- Synchronous Generator ,
- Mechanical Power ,
- Higher-order Model ,
- Deep Belief Network ,
- System Inertia ,
- Data-driven Methods ,
- Dynamic Frequency ,
- Objective Data ,
- Back Propagation Neural Network ,
- Renewable Power Generation
- Author Keywords