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This paper deals with the challenge of short-circuit calculation for power systems dominated by power electronics converters. A novel methodology has been presented to identify short-circuit equilibrium point of the studied system considering the operation and limitations of power converters. The studied system has been modeled with an element-based steady-state formulation. In particular, the governing equations implemented on converter control, which involve a specific control mode and various potential current-saturation states, are included. Then, an effective and efficient approach has been proposed to identify the short-circuit equilibrium points that satisfies converters limitations. Numerical case studies with VSCs show that the proposed methodology can identify the short-circuit equilibrium point efficiently and accurately with different types and depths of short-circuit fault. The short-circuit calculation results have been validated with dynamic simulations.

We consider a grid-connected voltage source converter (VSC) and address the problem of estimating the grid angle and frequency, information that is essential for an appropriate operation of the converter. We design phase-locked loop (PLL) algorithms with guaranteed stability properties, under the assumption that the grid is characterized by relatively high short-circuit-ratio (SCR) and inertia. In particular we derive, using passivity arguments, generalization of the conventional synchronous reference frame (SRF) and arctangent (ATAN) PLL, which are the standard solutions in power applications. The analysis is further extended to the case of connection of the VSC to a low-inertia grid, ensuring robustness of the algorithms in case of frequency variations. The results are validated on a benchmark including the grid, the VSC and related controllers., Comment: 7 pages

Recent environmental policies have led many academic, industrial and governmental stakeholders to design and plan scenarios with very high share of renewable energy sources (RES). New system elements such as High-voltage Direct Current (HVDC) transmission, Microgrids, Virtual Power Plants (VPP) and Dynamic Virtual Power Plants (DVPP) are being increasingly studied with respect to their contribution to integrate future RES plants in the main grid. Several future scenarios are being analysed for each system and region, to ensure that the future energy systems, composed mostly of RES, can remain stable, match the demand during the seasonal variations across the year and are economically feasible. In this article, different types of energy scenarios are considered to obtain a range of options in terms of size, renewable generation technologies, and electrical network configuration. The scenarios were studied in the context of the POSYTYF project and were quantified through an optimization-based algorithm, using specific locations in Europe, and real data related to the availability of different RES, as well as the demand. It has been shown that photovoltaic (PV) and wind generation can provide the renewable backbone but they lack the flexibility needed to achieve a very high share in the energy mix. Other technologies, such as solar thermal and pumped hydro, become important to cover the last range of integration, as they provide a high flexibility, which is crucial for high share.

This paper reviews Voltage-Source Converters (VSCs) EMT and Phasor models currently used to simulate converter-interfaced generation (CIG) and renewable energy resources integration to power systems. Several modelling guidelines and suitability analyses were provided based on a comprehensive comparative study among the models. Various studies were performed in a small system and a large system, modelled in Simulink. We address a gap related to the suitability of CIGs phasor models in studies where the boundary between electromagnetic and electromechanical transients overlap. An insightful analysis of the adequate simulation time step for each model and study is also provided, along with several simulation guidelines.

This article details a complete procedure to derive a data-driven small-signal-based model useful to perform converter-based power system related studies. To compute the model, Decision Tree (DT) regression, both using single DT and ensemble DT, and Spline regression have been employed and their performances have been compared, in terms of accuracy, training and computing time. The methodology includes a comprehensive step-by-step procedure to develop the model: data generation by conventional simulation and mathematical models, databases (DBs) arrangement, regression training and testing, realizing prediction for new instances. The methodology has been developed using an essential network and then tested on a more complex system, to show the validity and usefulness of the suggested approach. Both power systems test cases have the essential characteristics of converter-based power systems, simulating high penetration of converter interfaced generation and the presence of HVDC links. Moreover, it is proposed how to represent in a visual manner the results of the small-signal stability analysis for a wide range of system operating conditions, exploiting DT regressions. Finally, the possible applications of the model are discussed, highlighting the potential of the developed model in further power system small-signal related studies.