Browsing by Author "Pouresmaeil, Edris, Assoc. Prof., Aalto University, Department of Electrical Engineering and Automation, Finland"

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  • Artificial Intelligence-based Control Methods for Optimal and Stable Operation of Converter-dominated Microgrids
    (2023) Pournazarian, Bahram
     School of Electrical Engineering | Doctoral dissertation (article-based)
    The microgrid as a major player in future smart grids includes power-electronic-based distributed generation (DG) units, loads, energy storage system (ESS), and lines. The microgrid can operate either island or connected to the main grid. The voltage and frequency references in island microgrid are adjusted by individual DGs while in grid-connected mode these references are dictated to the DGs by the upstream grid. The droop control and virtual synchronous generator (VSG) control are well-known methodologies to control several converters in an island microgrid. The small-signal stability of a microgrid is defined as its ability to move from one permissible operating point to another permissible operating point after being subjected to a small-signal disturbance. The droop control coefficients, virtual impedances, and VSG parameters should be tuned in a feasible range to maintain the stability of microgrid. Despite the remarkable achievements, the state-of-the-art microgrid control methods face three major challenges: (1) These methods have not optimized the virtual impedances by considering the microgrid small-signal stability and power sharing in all operating points, inappropriate application of virtual impedances can jeopardize the microgrid stability; (2) VSG provides virtual inertia and damping in the microgrid including static and dynamic loads, however, inappropriate tuning of these parameters can threaten the microgrid stability, microgrid frequency, voltage, and reactive power sharing; (3) The application of artificial neural networks in online control of converters and VSGs is necessary to fulfil the stability and dynamic performance requirements in future microgrids. First and foremost, this thesis introduces a new perspective on microgrid control methods, which suggests to analyse the stability of all operating points and define an optimization problem according to the dynamics and stability preferences of microgrid. This optimization method concludes the stable operation of microgrid in all operating points and a desirable dynamic performance, simultaneously.Secondly, the thesis reports a novel method to optimize the virtual inertia, virtual damping, current state-feedback factor, and virtual impedances to enhance the microgrid small-signal stability. Moreover, the reactive power sharing, frequency Nadir, and voltage of buses are enhanced. Finally, the thesis introduces an online optimal control method based on adaptive network-based fuzzy inference system (ANFIS). In this method, the controller learns the optimal control policy for each value of active and reactive power and generates the optimal value of virtual inductance accordingly. The reactive power circulation among converters is minimized and the voltage drops on virtual inductances are negligible. Moreover, the small signal stability of microgrid is enhanced by the proposed control method.
  • Integration of Renewable Energy Sources into Power Grids Applying Distributed Virtual Inertia and Model Predictive Controls
    (2022) Saeedian, Meysam
     School of Electrical Engineering | Doctoral dissertation (article-based)
    The current energy arena is changing, from fossil fuel-based generation to power electronic converter-interfaced renewable generation. Hence, the power system inertia and short-circuit current gradually reduce, making low-inertia grids more sensitive to frequency disturbances (i.e., power mismatch between generation and demand) and jeopardizes system stability. This thesis develops control methods for grid-following and grid-forming converters employed toward more power electronic-based generators. The thesis contributions are divided into two main approaches.  First, the distributed virtual inertia method, a grid-following converter solution aimed at synthetic inertia provision, is studied in detail. It is depicted that this method has two drawbacks: (1) small-signal stability analyses affirm that a local mode associated with the controller is prone to become unstable when the converter operates in weak grids, and (2) the DC-link voltage is not reverted to its reference value after the power mismatch between generation and demand occurred in the host grid. Herein, the aforesaid problems are addressed properly; efficient compensators are proposed which eliminate the adverse impact of distributed virtual inertia gain on the converter stability in weak grid connections. Moreover, the distributed virtual inertia controller is modified so as not to affect the outer-loop voltage regulator after transients. Then, the DC voltage restoration is possible.  Second, the conventional primary control, i.e., inner-loop cascaded linear controller and outer-loop droop, used in islanded AC microgrids is discussed. In sum, this approach has inferior dynamic response and rapid rate of change of frequency following perturbations. Accordingly, the thesis addresses these issues by introducing a modified virtual synchronous generator control. A Laguerre functions-based discrete-time model predictive controller with a multiobjective cost function is incorporated as the heart of the control system which supersedes the inner loop for hierarchical linear controllers of grid-forming converters. This yields realizing large prediction horizons, improved dynamic performance (very short rise time and slight overshoot), and inherent overcurrent protection in the case of fault or overloading without sacrificing the controller robustness. Finally, the merits of proposed techniques are verified by comparisons with corresponding primary methods. And, detailed model simulations are conducted in MATLAB/Simulink to show the efficacy of the proposed controllers.
  • Machine Learning Approaches to Improving the Transient Stability of Voltage-Source Converters in Weak Grids
    (2023) Sepehr, Amir
     School of Electrical Engineering | Doctoral dissertation (article-based)
    With the proliferation of converter-interfaced generation in modern power systems, grid-forming converters are viewed as a solution to improve system stability and resilience in weak power grids. However, the dynamic behaviour of the grid-converter systems is strongly influenced by inevitable disturbances and transients in weak power grids (e.g. short circuit faults). Moreover, grid-converter systems are prone to harmonic instability due to the interactions between the converters and passive elements. These issues pose security risks and limit the further integration of renewable generation into the modern power system. Therefore, this thesis aims to improve the transient stability and harmonic stability of grid-converter systems by employing deep-learning and analytic methods for developing power synchronization control (PSC) in weak power grids. First, the internal structure of the synchronization loop in PSC is modified to reduce vulnerability to grid transients by utilizing a back-calculation scheme. Also, the damping characteristics of PSC are enhanced to mitigate the decaying DC offset current of the converter. Second, the internal reference calculation is developed by embedding a long short-term memory (LSTM) neural network into PSC. The LSTM neural network is trained to extract and predict the grid voltage trajectory based on the converter dynamics and grid strength. Thus, the control system updates the internal references dynamically to meet the low-voltage ride-through (LVRT) requirements and prevent synchronization loss. Third, by employing deep learning methods and neural networks, an encoder-stacked classifier is introduced for early detection of synchronization instability. This allows time for corrective control actions to be taken and prevents synchronization loss in the grid-converter system. The applied neural networks are trained to be robust against data corruption and added noise. Finally, the admittance characteristics of converters are studied and necessary conditions are outlined for achieving harmonic stability with PSC in weak grids. Moreover, a 12.5-kVA three-phase back-to-back converter system is implemented under weak grid conditions for the experimental evaluation of the results and future works.