Abstract
The proliferation of grid-connected converter interfaced energy sources in Smart Grids, enhance sustainability and efficiency as well as minimizing power losses and costs. However, concerns arise regarding the stability and reliability of future smart grids due to this wide integration of power electronic devices, which are recognized to affect the dynamic response of the system, especially during disturbances. For instance, apart from the lower damping of existing electromechanical modes, new low-frequency oscillations begin to appear. Yet, the ability of grid-connected converters to provide grid support functionalities can alleviate the aforementioned challenges. Relevant studies show that these functionalities can be enhanced even further, if information regarding the oscillation characteristics are available. Traditional methods for extracting modal information are very well suited for monitoring purposes, however, they pose certain limitations when considered for control applications. Therefore, this paper proposes a multi-band intelligent power oscillation damper (MiPOD) that exploits 1) the inherent characteristics of grid-connected converters to damp multiple power oscillations and 2) the modeling capabilities of Artificial Intelligence (AI) for predicting the frequency of electromechanical oscillations in the system, as operating conditions change. Essentially, the MiPOD integrates the AI model in the control loop of the converter to attenuate multiple modes of oscillation. The proposed controller is validated for different disturbances and randomly generated operating points in the two area system. Specifically, in this case the AI model is a Random Forest ensemble regressor that is developed for tracking two electromechanical modes. As it is shown, the MiPOD can improve the overall performance of the system under various contingency scenarios with only 6% of the corresponding total nominal capacity of synchronous generators. In addition, the monitoring and damping abilities of the MiPOD are demonstrated for a vast range of operating points just by tuning two parameters; the predicted oscillation frequencies of the local and inter-area mode.
Highlights
The modernization of power systems into Smart Grids (SG) aims to integrate information and communications technologies with the electricity network, forming a cyber-physical system (Aleem et al, 2020)
Demand changes constantly and the damping and frequency of the oscillatory modes in the system change. To emulate this behavior and demonstrate the ability of the multi-band intelligent power oscillation damper (MiPOD) to adapt and damp electromechanical oscillations as system conditions change, the active and reactive power of loads L7 and L9 are varied randomly using scaling factors drawn from a Gaussian distribution with a mean of 1 and a standard deviation of 0.1
The inter-area and local mode characteristics are calculated through modal analysis for three study cases: Base case, SPC only, and MiPOD
Summary
The modernization of power systems into Smart Grids (SG) aims to integrate information and communications technologies with the electricity network, forming a cyber-physical system (Aleem et al, 2020). In contrast to the conventional operation scheme, SG reinforce the integration of grid-connected converter (GCC), which are usually based on (but not limited to) Renewable Energy Systems (RES) and Energy Storage Systems (ESS) (Kempener et al, 2013) This paradigm shift i.e., from a centralized to a decentralized structure can increase the sustainability and efficiency of power systems while reducing costs and power losses (Howell et al, 2017; Aleem et al, 2020). Recent studies suggest that higher penetration of power electronics is linked with 1) the appearance of additional low frequency electromechanical oscillations and 2) the reduced damping of the existing ones (ENTSO-E, 2019).
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