Dr. Espinosa-Neira, Eduardo

Smart meters play an important role in energy management systems as they provide essential parameters for real-time monitoring, protection, and control that enable informed decisions for the end-users and the utility grid. However, available systems are high-cost solutions with different hardware and software, which provide limited measuring parameters with certain accuracy. This work aims to develop and implement an innovative smart electricity meter (SEM) system that surpasses conventional designs by incorporating advanced features like noninvasive sensors, manual signal calibration, and flexible communication modes. The developed SEM supports real-time data transmission via IoT and provides superior accuracy in measuring harmonics and frequency, addressing key challenges in energy monitoring. This work contributes to real-time energy monitoring and energy management systems in residential and industrial applications.

The use of advanced modulation and control schemes for power converters, such as a Feedback Quantizer and Predictive Control, is widely studied in the literature. This work focuses on improving the closed-loop modulation scheme called Feedback Quantizer, which is applied to a three-phase voltage source inverter. This scheme has the natural behavior of mitigating harmonics at low frequencies, which are detrimental to electrical equipment such as transformers. This modulation scheme also provides good tracking for the voltage reference at the fundamental frequency. On the other hand, the disadvantage of this scheme is that it has a variable switching frequency, creating a harmonic spectrum in frequency dispersion, and it also needs a small sampling time to obtain good results. The proposed scheme to improve the modulation scheme is based on a Discrete Space Vector with virtual vectors to obtain a better approximation of the optimal vectors for use in the algorithm. The proposal improves the conventional scheme at a high sampling time (200 μs), obtaining a THD less than 2% in the load current, decreases the noise created by the conventional scheme, and provides a fixed switching frequency. Experimental tests demonstrate the correct operation of the proposed scheme.

Small grid-connected inverters are not friendly to the electrical grid, in the sense they do not take any action to support the grid when contingency events occur. For example, because of their relatively low power capacity, small grid-connected inverters are not designed to provide dynamic frequency support to the grid. On the other hand, it is well known that microgrids and weak grids including distributed generation would benefit significantly if all of the grid-connected converters could support and help against grid frequency disturbances. Within the family of small grid-connected converters, single-phase quasi-Z-source inverters (QZSI) have become an attractive topology, because they represent a reliable and economical alternative, and can be very efficient in applications that demand small or medium powers. However, a major disadvantage is that the control strategy must manage both direct current and alternating current variables through the same group of switches. The latter is a challenging task when implementing predictive control schemes. This paper proposes a finite control set model predictive control (FCS-MPC) strategy for a single- phase grid-supporting QZSI. The proposed predictive scheme can be easily integrated with a complementary control block to provide grid frequency support. Experimental results show evidence of the inverter operating under the proposed control strategy and providing grid frequency support, which demonstrates the feasibility of the proposal

Cascaded H-bridge drives require using a significant-size capacitor on each cell to deal with the oscillatory power generated by the H-bridge inverter in the DC-link. This results in a bulky cell with reduced reliability due to the circulating second harmonic current through the DC-link capacitors. In this article, a control strategy based on a finite control set model predictive control and a proportional-resonant controller is proposed to compensate for the oscillatory power required by the H-bridge inverter through the cell’s input rectifier. With the proposed strategy, a DC-link second harmonic free operation is achieved, allowing for the possibility of reducing the capacitor size and, in consequence, the cell dimensions. The feasibility of the proposed control scheme is verified by experimental results in one cell of a cascade H-bridge inverter achieving an operation with a capacitance 141 times smaller than required by conventional control approaches for the same voltage ripple.

The objective of this study is to explore the antecedents of the formation of entrepreneurial intention from a linear, causal and asymmetrical perspective. We have combined the Ajzen model applied to entrepreneurship, including two personality variables (self-confidence and creativity). This study involves a structural equation model based on partial least squares (PLS) and fuzzy set qualitative comparative analysis (fsQCA). All of the hypotheses were supported except for the influence of the variables subjective norms and self-confidence on EI. The PLS model explains 68.7% of the variance of EI. According to the fsQCA results, four models explain 88.1% of the existence of EI. The two models with the greatest degree of coverage are: Self-Confidence × Attitude Towards Entrepreneurial Behaviour × Subjective Norms and Perceived Behaviour Control × Creativity × Subjective Norms.

Hierarchical control is a widely used strategy that can increase resilience and improve the reliability of the electrical network based on microgrid global variables. The large amounts of data required during transitions prompt the use of more reliable and flexible communications to achieve the control objectives. Such communications can involve potential cyber vulnerabilities and latency restrictions, which cannot be always addressed in real-time. To accurately capture the system’s overall operation, this paper proposes a co-simulation framework driven by flexible communications and a resilient control algorithm to regulate the frequency and voltage deviations in a networked microgrid. Model-based predictive control has been implemented, to avoid slow transient response associated with linear hierarchical control. Software-Defined Networking (SDN) is responsible for increasing the communication intelligence during the power-sharing process. The effects of critical communications and overall system performance are reviewed and compared for different co-simulation scenarios. Graphical Network Simulator (GNS3) is used in combination with model-based predictive control and SDN, to provide latency below 100 ms, as defined in IEC 61850. Testing of the proposed system under different cyber attack scenarios demonstrate its excellent performance. The novel control architecture presented in the paper provides a reference framework for future cloud computing-based microgrids.

There is a need to ensure comfortable conditions for hospital staff and patients from the point of view of thermal comfort and air quality so that they do not affect their performance. We consider the need for hospital employees and patients to enjoy conditions of greater well-being during their stay. This is understood as a comfortable thermal sensation and adequate air quality, depending on the task they are performing. The contribution of this article is the formulation of the fundamentals of a system and platform for monitoring thermal comfort and Indoor Air Quality (IAQ) in hospitals, based on an Internet of Things platform composed of a low-cost sensor node network that is capable of measuring critical variables such as humidity, temperature, and Carbon Dioxide (CO2). As part of the platform, a multidimensional data model with an On-Line Analytical Processing (OLAP) approach is presented that offers query flexibility, data volume reduction, as well as a significant reduction in query response times. The experimental results confirm the suitability of the platform’s data model, which facilitates operational and strategic decision making in complex hospitals.

This work deals with the study of the open-source Arduino DUE board as a digital control platform for three-phase two-level Voltage-Source Converters (VSC) and Current-Source Converters (CSC), including (i) the description of the power topologies, its connection to the load or the ac grid, and the electrical signals required for sensors and power valves, (ii) the description of the Arduino Due board, its features, and its connection with the sensors and power valves in the converter, and (iii) evaluation of the Arduino DUE’s processing time required for typical power converter algorithms, such as modulation, mathematical transforms, and linear controllers typically used in these converters. Experimental results are presented to validate the study, showing that the Arduino DUE is a feasible digital control platform for this type of power converter.

The main drawback of the Cascaded-H Bridge converter based on three-phase/single-phase current-source inverters is the large DC inductors needed to limit the variation of the DC current caused by the single-phase inverter oscillating power. If the oscillating power is some-how compensated, then the DC inductor can be designed just as a function of the semiconductors’ switching frequency, reducing its value. This work explores the use of three-phase/single-phase cells magnetically coupled through their DC links to compensate for the oscillating power among them and, therefore, reduce the DC inductor value. At the same time, front ends controlled by a non-linear control strategy equalize the DC currents among coupled cells to avoid saturating the magnetic core. The effectiveness of the proposal is demonstrated using mathematical analysis and corroborated by computational simulation for a 110 kVA load per phase and experimental tests in a 2 kVA laboratory prototype. The outcomes show that for the tested cases, coupling the DC links by a 1:1 ratio transformer allows reducing the DC inductor value below 20% of the original DC inductor required. The above leads to reducing by 50% the amount of magnetic energy required in the DC link compared to the original topology without oscillating power compensation, keeping the quality of the cell input currents and the load voltage. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

The use of controlled power converters has been extended for high power applications, stacking off-the-shelve semiconductors, and allowing the implementation of, among others, AC drives for medium voltages of 2.3 kV to 13.8 kV. For AC drives based on power cells assembled with three-phase diode rectifiers and cascaded H-bridge inverters, a sophisticated input multipulse transformer is required to reduce the grid voltage, provide isolation among the power cells, and compensate for low-frequency current harmonics generated by the diode-based rectifiers. However, this input multipulse transformer is bulky, heavy, and expensive and must be designed according to the number of power cells, not allowing total modularity of the AC drives based on cascade H-bridges. This study proposes and evaluates a control strategy based on a finite control set-model predictive control that emulates the harmonic cancellation performed by an input multipulse transformer in a cascade H-bridge topology. Hence, the proposed method requires conventional input transformers and replaces the three-phase diode rectifiers. As a result, greater modularity than the conventional multicell converter and improved AC overall input current with a THD as low as 2% with a unitary displacement power factor are achieved. In this case, each power cell manages its own DC voltage using a nonlinear control strategy, ensuring stable system operation for passive and regenerative loads. The experimental tests demonstrated the correct performance of the proposed scheme.