Amirhossein Moeini

In this paper, a new deep learning-based framework is developed to perform real-time switching of hybrid AC/DC transmission grids under the effect of dynamic line rating (DLR) constraint. The proposed deep learning model is designed to learn the topological patterns of buses/lines according to operational states, e.g., power injections and line impedances, in order to obtain the optimal switchings of transmission power grids. As the load and power generation vary with time, the network switching depends on both the current and the previous status of the load and the generation units. Thus, a deep learning-based time series model that integrates the gated recurrent unit (GRU) and the long short-term memory (LSTM) models is developed, which takes advantage of LSTM’s high accuracy and GRU’s high computational efficiency. The developed learning-based network switching framework is tested on a modified hybrid AC/DC IEEE 39-bus system, a modified hybrid AC/DC 118-bus test system, and a modified hybrid AC/DC 300-bus test system. Results show that the learning-based switching model can achieve both high accuracy and computational efficiency, which is suitable for real-time transmission network switching.

The main objective of an active power filter (APF) is to control the harmonics of nonlinear loads in power systems. In addition, the reactive power (fundamental component of the AC power) at the point of common coupling (PCC) can be compensated by using an APF. This paper investigates a technique for the modulation technique of the active power filters. Using the artificial neural network (ANN) technique, real-time fundamental and harmonic compensations can be achieved for the low-frequency modulation techniques such as asymmetric selective harmonic elimination/mitigation-pulse width modulation (ASHE/ASHM-PWM) and asymmetric selective harmonic current mitigation-PWM (ASHCM-PWM). This means that different phases and magnitudes of the fundamental and harmonics for the voltage of the converter can be obtained in real time by using the proposed technique. Furthermore, in the paper, a guideline is proposed for generating ANN training data for the ASHCM-PWM technique. Simulation and experimental results are conducted on a 7-level (3-cell) cascaded H-bridge (CHB) active power filter to evaluate the advantages and effectiveness of the proposed ANN-based technique.

Grid-tied converters become more popular for electric vehicle, renewable energy, and energy storage systems applications. Different modulation techniques such as low-frequency (e.g., selective harmonic elimination-PWM, selective harmonic mitigation-PWM, and selective harmonic current mitigation-PWM (SHCM-PWM)) and high-frequency modulation techniques (e.g., phase shift-PWM and space vector modulation) are used in the literature for grid-tied converters. Low-frequency modulation techniques have a high-efficiency due to the low-switching power losses. One of the main challenges of low-frequency modulation techniques such as SHCM-PWM is how to implement the proposed technique in real-time, due to the transcendental Fourier equations of SHCM-PWM. In this paper, a deep learning technique (i.e., gated recurrent units) is adopted to implement the SHCM-PWM technique in real-time. To evaluate the effectiveness of the proposed learning-based technique, both simulation and experiments are performed for a single-phase 3-cell 7-level CHB converter.

In this article, a low-frequency hybrid modulation technique which is composed of a phase shift-pulsewidth modulation (PS-PWM) and an asymmetric selective harmonic current mitigation-PWM (ASHCM-PWM) are proposed for cascaded multilevel converters to meet the harmonic limit of IEEE 519 2014. In the proposed technique, the harmonics within the concerned frequency range due to PS-PWM are reduced by the ASHCM-PWM so that the cascaded H-bridge (CHB) converter can meet IEEE 519 harmonic limit. The equation set which helps a grid-tied CHB converter meet both harmonic limit and total demand distortion, is developed. The design technique for critical parameters, such as the inductance and the switching frequency of the proposed hybrid modulation technique, is developed. Simulation and experiments are conducted on a single-phase 3-cell 7-level grid-tied CHB converter to validate the proposed technique.

This paper investigates the critical parameter design technique for a cascaded H-Bridge (CHB) with selective harmonic elimination (SHE) / compensation (SHC) for single phase systems. The critical parameters include the filter inductance, the number of H-bridge cells, the DC bus voltage and the switching frequency. This paper derives the relationship of electrical parameters, topologies, and modulation techniques to the voltage/current harmonic envelopes, and compares the filter inductor design for an H-Bridge with SPWM, an H-Bridge (HB) with SHE/SHC and a CHB with SHE/SHC. Furthermore, a harmonic-envelope-based approach is developed to determine the optimum design parameters. The developed approach designs the harmonic envelope with two proposed criteria: the first one is the capacity criterion, which guarantees that the fundamental and controllable components are within the applicable solution range to avoid over-modulation; the other one is the attenuation criterion, which ensures that the uncontrollable harmonic complies with the grid limit. Simulations and experiments verified that a CHB designed with the proposed technique can simultaneously fulfill the compensation objectives and meet the harmonic limits.

A grid-tied cascaded H-bridge (CHB) converter with low frequency modulation techniques needs to meet power quality standards. At the same time, the effects of grid voltage harmonics on CHB converter's current harmonics must be considered in the modulation techniques. Furthermore, the dc link voltages of grid-tied converters need to be regulated. In this paper, an asymmetric selective harmonic current mitigation-pulse width modulation (PWM) (ASHCM-PWM) technique is used to meet the current harmonic limits of a power quality standard with the effects of grid voltage harmonics considered in the equation set of its optimization process. A voltage balancing technique based on the average power of each cell is derived to regulate the dc link voltages of the CHB converters without using dc voltage sensors. By using the proposed voltage balancing technique, the CHB converters do not need complicated dc link voltage controllers. As a result, the cost and complexity of the grid-tied converters can be significantly reduced. Simulations and experiments were conducted on a 7-level grid-tied CHB converter to validate the proposed voltage balancing technique with ASHCM-PWM modulation technique.

In this paper, a selective harmonic current mitigation pulsewidth modulation (SHCM-PWM) technique with low switching frequencies is proposed for grid-connected cascaded H-bridge multilevel rectifiers to fully meet harmonic requirements within extended harmonic spectrum. In the proposed technique, instead of using the voltage references to calculate switching angles for the rectifier as in conventional selective harmonic elimination-PWM (SHE-PWM) or selective harmonic mitigation-PWM (SHM-PWM), current references are used to compensate the current harmonics due to both grid voltage harmonics and rectifier input voltage harmonics so as to meet the current harmonic requirements and total demand distortion within the whole harmonic spectrum. Furthermore, the techniques to design the critical parameters including switching frequency, the highest harmonic order that can be mitigated using the proposed current-reference-based technique, and the coupling inductance that can attenuate the current harmonic orders above the highest order are investigated. With the same switching frequency, the proposed SHCM-PWM technique uses smaller coupling inductance to meet higher orders of current harmonic requirements than the conventional SHE-PWM technique. Finally, simulations and experiments were conducted to validate the proposed technique.