The increase in renewable power generation leads to the need for more controllability on the demand side. The integration of power electronic devices, such as Smart Transformers, brings more flexibility into the modern grid. Demand-side management has large potential, but the lack of grid information limits the realization of precise control. Thus, there is a renewed interest in investigating the power-to-voltage and power-to-frequency sensitivity of the load in real-time. The exponential load model is a commonly used model to describe the load dependency on voltage and frequency. As a non-linear equation, the load model can be determined by linearization or by using an iterative algorithm. This work compares two load sensitivity identification methods: the online load sensitivity identification method, using the linearization approach, and the Newton method, using an iterative algorithm. The variance in the distribution of the load sensitivity identification results is studied, which is an important feature of precision. The reliability and accuracy of the results are also analyzed by using the calculated parameters to reconstruct the power signals, which are compared with the power measurements.
Methods Comparison for Load Sensitivity Identification / Courcelle, M.; Tao, Q.; Geis-Schroer, J.; Bruno, S.; Leibfried, T.; De Carne, G.. - (2023), pp. 1-6. (Intervento presentato al convegno 2023 IEEE Belgrade PowerTech, PowerTech 2023 tenutosi a srb nel 2023) [10.1109/PowerTech55446.2023.10202677].
Methods Comparison for Load Sensitivity Identification
Bruno S.;
2023-01-01
Abstract
The increase in renewable power generation leads to the need for more controllability on the demand side. The integration of power electronic devices, such as Smart Transformers, brings more flexibility into the modern grid. Demand-side management has large potential, but the lack of grid information limits the realization of precise control. Thus, there is a renewed interest in investigating the power-to-voltage and power-to-frequency sensitivity of the load in real-time. The exponential load model is a commonly used model to describe the load dependency on voltage and frequency. As a non-linear equation, the load model can be determined by linearization or by using an iterative algorithm. This work compares two load sensitivity identification methods: the online load sensitivity identification method, using the linearization approach, and the Newton method, using an iterative algorithm. The variance in the distribution of the load sensitivity identification results is studied, which is an important feature of precision. The reliability and accuracy of the results are also analyzed by using the calculated parameters to reconstruct the power signals, which are compared with the power measurements.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.