• Energy Research

<p>This industry-oriented paper presents an overview and in-depth analysis of previous and current situations of power system frequency response and control in Australia. The evaluation of different services provided by different electricity market players under the supervision of the Australian Energy Market Operator (AEMO) as an independent system operator provides lessons and an understanding of the current operation status with its real challenges and opportunities from frequency stability and security perspectives. Based on the evaluation of the current situation and future national planning, a number of research gaps and industrial technical issues are identified, and some perspectives on future research directions are presented to help move the power system transformation toward almost 100% renewable and more secure energy systems.</p>

This paper proposes a voltage support scheme for traction networks, which compensates for the voltage drop along the catenary line to which locomotives are connected. The proposed method is based on the injection of capacitive reactive power through the current controlled active line-side converter of locomotives. Comparing the catenary voltage with its reference value, the error is fed to a gain-scheduled PI-controller. The controller generates the q-axis reference value of the converter current, which is responsible for reactive power injection. The gain scheduling is carried out through identifying the parameters of the catenary line. The catenary parameters identification is performed by harmonic current injection and analyzing its impact on the catenary voltage. The performance of the proposed control strategy is evaluated in MATLAB/PLECS environment for a traction network consisting of one locomotive and two substations and moreover, for a two-locomotive three-substation traction network.

This paper presents an improved method to estimate the available inertia in an islanded AC microgrid. Inertia estimation is carried out based on measured frequency response for any arbitrary disturbance that occurs in the system. Modifications are made to the conventional swing equation-based curve-fitting method to obtain an accurate estimate for a system with high penetration of renewable generations. A polynomial curve fit over the total power generation is introduced to estimate the size of the disturbance accurately. Additionally, a variable order polynomial fit is carried out over the measured frequency, which not only improves the estimate of inertia but also helps to refrain the influence of network topology and size/location of the disturbance. The test microgrid system considered is a modified Standard IEEE distribution network, which consists of radial feeders and distributed generations. Firstly, the proposed method is tested on a system with only synchronous generations to assess the accuracy of the estimate. This is followed by the integration of Type 3 and Type 4 wind turbines, and a PV array within the microgrid system. Virtual inertia control is then implemented in the wind turbines to obtain inertial support. Estimation study of the microgrid system with virtual inertia is then carried out. The developed estimation method can accurately estimate the inertia provided by the synchronous sources within the generation mix. Finally, from all the results and observations, the inertia estimation process in a microgrid system is segregated into synchronous and nonsynchronous inertia estimation.

<p>The majority of inverter-based resources (IBRs) currently operate as grid-following inverters (GFLIs). These inverters exhibit certain stability issues when integrated in low-strength areas of the grid. To enhance the grid strength in a GFLI-dominant area, virtual synchronous generators (VSGs) are installed. If the VSG and the GFLI are investigated as a paralleled system, despite the benefits brought by the VSG, in some cases, the transient angle instability process, caused by a voltage sag, is accelerated. Therefore, this paper studies the transient angle stability of a paralleled VSG-GFLI system via investigating the voltage at a common bus between the two IBRs. Subsequently, a stable region of the voltage angles of the two IBRs is determined. Based on this region, the stability margin of the paralleled system can be determined and used to quantitatively evaluate the system stability. Moreover, a control loop is proposed to improve the transient stability of the paralleled system. The proposed controller can adaptively reduce the VSG power set-point to avoid a complete failure of the VSG even when no stable equilibrium point exists during a voltage sag. The stability investigation and performance evaluation of the proposed method are conducted in PSCAD/EMTDC and experimentally validated.</p>

Grid-forming (GFM) control has emerged as a promising solution to the challenges posed by the increasing reliance on inverter-based resources (IBRs). However, unlike in a battery-based IBR, the implementation of GFM in wind turbine generators (WTGs) introduces challenges due to multiple machine-side converter (MSC) and grid-side converter (GSC) interactions. In this work, a GFM-WTG control structure is adopted in which the MSC primarily regulates the DC-link voltage, while the GSC emulates grid-forming behavior using virtual synchronous generator principles. Accordingly, this paper presents a practical control implementation scheme and a systematic small-signal modeling framework for GFM WTGs using the component connection method, enabling a unified state-space representation that captures key electromechanical, aerodynamic and control interactions inside the GFM-WTG system. The proposed model is validated through electromagnetic transient simulations, and eigenvalue and participation factor analyses reveal strong MSC-GSC inter-dependencies. Sensitivity analysis further confirms model accuracy across varying operating conditions. Additionally, a reduced-order model is derived to balance computational efficiency with dynamic fidelity. The findings provide a robust foundation for stability analysis and control tuning of GFM WTGs, supporting their reliable integration into future power grids.

Islanded microgrids have low real and reactive power generation capacity and low inertia. This makes them susceptible to large frequency and voltage deviations, which deteriorate power quality and can cause frequency or voltage collapse. Grid-supporting battery energy storage systems are a possible solution as they are able to respond quickly to changes of their real and reactive power set-points. In this paper, a data-driven grid-supporting control system for battery energy storage systems, which requires no changes to the inverters inner real and reactive power control loops compared with a conventional grid-supporting inverter, is proposed. Tuning the data-driven controller does not require a dynamic model of the microgrid. Instead, the frequency response of the microgrid is identified and used directly to optimally tune the controller for $H_\infty$ performance and robustness criteria. The performance of the data-driven controller is verified through real-time software-in-the-loop electromagnetic-transient simulation, where it is compared with an inverse-droop controller and is shown to significantly reduce voltage and frequency deviations.

The modular multilevel converter (MMC) is a potential candidate for medium/high-power applications, specifically for high-voltage direct current transmission systems. One of the main challenges in the control of an MMC is to eliminate/minimize the circulating currents while the capacitor voltages are maintained balanced. This paper proposes a control strategy for the MMC using finite control set model predictive control (FCS-MPC). A bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC one step ahead. Within each switching cycle, the best switching state of the MMC is selected based on evaluation and minimization of a defined cost function. The defined cost function is aimed at the elimination of the MMC circulating currents, regulating the arm voltages, and controlling the ac-side currents. To reduce the calculation burden of the MPC, the submodule (SM) capacitor voltage balancing controller based on the conventional sorting method is combined with the proposed FCS-MPC strategy. The proposed FCS-MPC strategy determines the number of inserted/bypassed SMs within each arm of the MMC while the sorting algorithm is used to keep the SM capacitor voltages balanced. Using this strategy, only the summation of SM capacitor voltages of each arm is required for control purposes, which simplifies the communication among the SMs and the central controller. This paper also introduces a modified switching strategy, which not only reduces the calculation burden of the FCS-MPC strategy even more, but also simplifies the SM capacitor voltage balancing algorithm. In addition, this strategy reduces the SM switching frequency and power losses by avoiding the unnecessary switching transitions. The performance of the proposed strategies for a 20-level MMC is evaluated based on the time-domain simulation studies.

The modular multilevel converter (MMC) has attracted significant interest for medium-/high-power energy conversion applications due to its modularity, scalability, and excellent harmonic performance. One of the technical challenges associated with the operation of the MMC is the circulation of double-frequency harmonic currents within its phase legs. This paper proposes a circulating current control strategy in a double-frequency rotating reference frame, which, contrary to the existing solutions that are based on approximate/inaccurate models, relies on an experimentally identified nonparametric model of circulating currents to determine the coefficients of the controller. Minimizing the squared second norm of the error between the open-loop transfer function of the system and a desired one, the coefficients of the controller are determined. To guarantee the stability of the closed-loop system, the minimization problem is subjected to a few constraints. The validity and effectiveness of the proposed control strategy is confirmed, and its dynamic performance is compared with that of an existing solution by experimental results.