Percorrer por autor "Pires, Vitor Fernão"
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- Dual Output and High Voltage Gain DC-DC Converter for PV and Fuel Cell Generators Connected to DC Bipolar MicrogridsPublication . Pires, Vitor Fernão; Cordeiro, Armando; Foito, Daniel José Medronho; Silva, J. Fernando A.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.
- Fault Detection in PV Tracking Systems Using an Image Processing Algorithm Based on PCAPublication . Amaral, Tito G.; Pires, Vitor Fernão; Pires, A. J.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.
- Fault-Tolerant SRM Drive with a Diagnosis Method Based on the Entropy Feature ApproachPublication . Pires, Vitor Fernão; Amaral, Tito G.; Cordeiro, Armando; Foito, Daniel José Medronho; Pires, A. J.; Martins, João F.The power electronic converter design is essential for the operation of the switched reluctance motor (SRM). Thus, a fault-tolerant power converter is fundamental to ensure high reliability and extend the drive operation. To achieve fault tolerance, fault detection and diagnosis methods are critical in order to identify, as soon as possible, the failure mode of the drive. To provide such capability, it is proposed in this paper a new fault-tolerant power converter scheme combined with a fault detection method regarding the most common power semiconductors failures in SRM drives. The fast and reliable proposed diagnosis method is based on the entropy theory. Based on this theory, normalized indexes (diagnostic variables) are created, which are independent from the load and speed of the motor. Through this method, it is possible to identify the faulty leg, as well as the type of power semiconductor fault. To test and evaluate the proposed solution several laboratory experiments were carried out using a 2 kW four-phase 8 / 6 SRM.