Grid-Forming Power Converters Tuned Through Artificial Intelligence to Damp Subsynchronous Interactions in Electrical Grids

Gregory N Baltas,Pedro Rodriguez,Andres Tarraso,Ngoc Bao Lai,Leonardo Marin

doi:10.1109/access.2020.2995298

Gregory N Baltas, Pedro Rodriguez + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.2995298

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Abstract

The integration of non-synchronous generation units and energy storage through power electronics is introducing new challenges in power system dynamics. Specifically, the rotor angle stability has been identified as one of the major obstacle with regards to power electronics dominated power systems. To date, conventional power system stabilizer (PSS) devices are used for damping electromechanical oscillations, which are only tuned sporadically leading to significant deterioration in performance against the ever-changing operating conditions. In this paper, an intelligent power oscillation damper (iPOD) is proposed for grid-forming converters to attenuate electromechanical inter-area power oscillation. In particular, the iPOD is applied to a synchronous power controller (SPC) based grid-forming power converter to increases gain of the active power control loop at the oscillatory frequency. Predictions regarding the mode frequency, corresponding to the current operating points, are given by an artificial intelligence ensemble model called Random Forests. The performance of the proposed controller is verified using the two area system considering symmetrical fault for random operating points. In addition, a comparison with PSS installed in each generator reveals the individual contribution with respect to the inter-area mode damping.

Highlights

Renewable-based Energy Systems (RES) and Energy Storage Systems (ESS) are widely adopted to reduce green house gas emissions and improve efficiency
Driven from the above, this paper presents an intelligent Power Oscillation Damper that enables the synchronous power controller (SPC) to adapt for maximum -oscillatory- mode attenuation
Power converters controlled through grid-forming techniques, e.g. a SPC augmented by an intelligent power oscillation damper (iPOD) as in this paper, can provide an additional source for damping power oscillations with the use of data and artificial intelligence (AI)

Summary

INTRODUCTION

Renewable-based Energy Systems (RES) and Energy Storage Systems (ESS) are widely adopted to reduce green house gas emissions and improve efficiency. The control system of a grid-forming converter can either be based on droop [9] or on virtual synchronous machine (VSM) [10] In the former case, the contribution of the power converter is usually limited to primary frequency and voltage regulation. The main contribution of the system, presented in the following, is a novel control scheme that incorporates intelligence by exploiting the ability of AI to predict the characteristic values of an oscillatory mode in real time and uses this information to adaptively tune a dedicated loop of the SPC to damp oscillations and enhance the system stability i.e. iPOD. The iPOD adds a significant amplification to the active power control loop at the tuned frequency Such a high gain implies that the proposed PLC with iPOD control structure can provide higher damping to low-frequency inter-area oscillation. In order to predict the oscillation modes in real-time, the AI-based algorithm called Random Forest is employed

ENSEMBLE AI PREDICTOR

7: Store Results

ENSEMBLE AI PREDICTOR TRAINING AND TUNING

VERIFICATION

Findings

CONCLUSION