Dual Output and High Voltage Gain DC-DC Converter for PV and Fuel Cell Generators Connected to DC Bipolar Microgrids

This paper introduces a new topology for a DC-DC converter with bipolar output and high voltage gain. The topology was designed with the aim to use only one active power switch. Besides the bipolar multiport output and high voltage gain this converter has another important feature, namely, it has a continuous input current. Due to the self-balancing bipolar outputs, the proposed topology is suitable for bipolar DC microgrids. Indeed, the topology balancing capability can achieve the two symmetrical voltage poles of bipolar DC microgrids. Furthermore, it is possible to create a midpoint in the output of the converter that can be directly connected to the ground of the DC power supply, avoiding common-mode leakage currents in critical applications such as transformerless grid-connect PV systems. The operating principle of the proposed topology will be supported by mathematical analysis. To validate and verify the characteristics of the presented topology, several experimental results are shown.info:eu-repo/semantics/publishedVersio

Energy router for SC: GC, SA and transition mode controls

UID/EEA/00066/2019 Grant agreement no. 731155 - Storage4Grid project.From the electrical point of view, the concept of smart community (SC) was defined as a distributed system consisting of a set of smart homes, distributed energy resources (DERs) and energy storage systems (ESSs) using SC controllers to enable smart power management. In this context, the SC energy management system (SCEMS) acts as aggregator of these resources, aiming to assure benefits for every SC stakeholder by setting the SC operation. The references given by the SCEMS must be accurately tracked by the energy routers (ERs), intended as one of the key components of the SC, acting as smart interface between the utility grid and the prosumers' DER and ESS. This study proposes a flexible, robust and simple control strategy for a single-phase ER. The ER regulates the active and reactive powers in grid-connected (GC) mode, and the voltage and frequency when operating in stand-alone (SA) mode. A seamless transition between SA and GC is demonstrated, avoiding undesired transients. The design and implementation of the proposed control strategy is progressively explained. Finally, this is tested via simulation (in PSCAD/EMTDC software) and verified with the experimental prototype.publishersversionpublishe

Switched Reluctance Linear Motor Force Ripple Suppression Based on Fixed Frequency Implicit Generalized Predictive Self-Correction Controller

An implicit generalized predictive self-correction controller (IGPC) is proposed in this paper to suppress the force ripple of switched reluctance linear motors (SRLMs). Due to its good robustness and rolling optimization features, the dynamic matrix controller (DMC), a kind of multi-step model predictive controller, is considered an effective method to suppress the force ripple of SRLMs. However, because DMC uses a fixed predictive model, it has high requirements for the accuracy of the predictive model, and the non-linear SRLMs make it difficult to adapt to different loads. To ease this problem, the IGPC proposed in this paper adopts a more flexible predictive model and improves the generalized predictive controller (GPC) to avoid solving the Diophantine equation online, which can adapt to different loads and reduce the system's burden. Besides, the proposed IGPC reduces the computational burden during matrix operations compared to DMC. In the simulation and experimental test based on a 100W 6/4 double-sided SRLM (DSRLM), the proposed IGPC is compared with DMC, and the force distribution function (FDF) adopts the current hysteresis, the results show that the proposed IGPC a better force ripple suppressing performance and has better load capacity compared with DMC

Compensation of Unbalanced Low-Voltage Grids Using a Photovoltaic Generation System with a Dual Four-Leg, Two-Level Inverter

In this paper, a grid-connected photovoltaic (PV) generation system is proposed with the purpose of providing support to low-voltage grids, namely through the elimination or attenuation of the grid imbalances. This compensation must consider the load types, which can be either linear or non-linear, and whether the reactive power and current harmonics generated by the non-linear loads need to be compensated in addition to the unbalanced active power. This must be well considered, since the compensation of all aspects requires oversized PV inverters. Thus, the different unbalanced compensation schemes are addressed. Several schemes for the generation of the inverter current references taking into consideration the compensation and load type are presented. For this PV generation system, a dual four-leg, two-level inverter is proposed. It provides full unbalanced compensation owing to the fourth leg of the inverter and also extends the AC voltage, which is important when this compensation is required. To control this inverter, a control scheme for the inverter that considers several compensation factors is proposed. A vector voltage modulator associated with the controller is another aspect that is addressed in the paper. This modulator considers the balance between the DC voltages of the inverters. Several compensation schemes are verified through computational tests. The results validate the effectiveness of the proposed PV generation system

Integrated Battery Charger for Electric Vehicles Based on a Dual-Inverter Drive and a Three-Phase Current Rectifier

This paper presents a new three-phase battery charger integrated with the propulsion system of an electric vehicle. The propulsion system consists of a dual-inverter topology connected to an induction motor via open windings. The electrical vehicles (EV) batteries are divided by two inverters. This will result in a drive with multilevel characteristics reducing the total harmonic distortion (THD) of the voltage applied to the motor. The modularity of the multilevel inverter will be maintained since two classical three-phase inverters are used. The charger will be fed by a three-phase high power factor current source rectifier. The motor windings will take the role of the DC-inductor required by the rectifier. In this way, an intermediate storage element between the grid and the batteries of the vehicle exist. For the control system of the battery charger, we propose the use of the instantaneous power theory and a sliding mode controller for the three-phase charger input currents. Finally, to verify the behavior and characteristics of the proposed integrated battery charger and control system, several tests are be presented

Smart Grid as a Key Tool for the Future of Electrical Distribution Networks

A new paradigm has appeared in the electricity sector with the rapid development of new renewable energy sources, storage systems, information and communication technologies, and ways of integrating distributed energy sources [...

Welcome to CPE-POWERENG 2020

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Magnetic Material Modelling of Electrical Machines

As Guest Editors of this Special Issue, it was our responsibility to ensure that the contributions to the issue related to the extensive field of electromechanical energy conversion, with a special focus on the design, materials, and modeling of electrical machines [...

Smart Grid as a Key Tool for the Future of Electrical Distribution Networks

A new paradigm has appeared in the electricity sector with the rapid development of new renewable energy sources, storage systems, information and communication technologies, and ways of integrating distributed energy sources [...

Fault detection in pv tracking systems using an image processing algorithm based on pca

Funding Information: Funding: This research was funded by national funds through FCT-Fundação para a Ciência e a Tecnologia, under projects UIDB/50021/2020 and UIDB/00066/2020. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Photovoltaic power plants nowadays play an important role in the context of energy generation based on renewable sources. With the purpose of obtaining maximum efficiency, the PV modules of these power plants are installed in trackers. However, the mobile structure of the trackers is subject to faults, which can compromise the desired perpendicular position between the PV modules and the brightest point in the sky. So, the diagnosis of a fault in the trackers is fundamental to ensure the maximum energy production. Approaches based on sensors and statistical methods have been researched but they are expensive and time consuming. To overcome these problems, a new method is proposed for the fault diagnosis in the trackers of the PV systems based on a machine learning approach. In this type of approach the developed method can be classified into two major categories: supervised and unsupervised. In accordance with this, to implement the desired fault diagnosis, an unsupervised method based on a new image processing algorithm to determine the PV slopes is proposed. The fault detection is obtained comparing the slopes of several modules. This algorithm is based on a new image processing approach in which principal component analysis (PCA) is used. Instead of using the PCA to reduce the data dimension, as is usual, it is proposed to use it to determine the slope of an object. The use of the proposed approach presents several benefits, namely, avoiding the use of a wide range of data and specific sensors, fast detection and reliability even with incomplete images due to reflections and other problems. Based on this algorithm, a deviation index is also proposed that will be used to discriminate the panel(s) under fault. Several test cases are used to test and validate the proposed approach. From the obtained results, it is possible to verify that the PCA can successfully be adapted and used in image processing algorithms to determine the slope of the PV modules and so effectively detect a fault in the tracker, even when there are incomplete parts of an object in the image.publishersversionpublishe