https://uvadoc.uva.es/handle/10324/1169 45 2026-04-05T04:37:31Z https://uvadoc.uva.es/handle/10324/83244 The fault diagnosis of electrical machines during startup transients has received increasing attention regarding the possibility of detecting faults early. Induction motors are no exception, and motor current signature analysis has become one of the most popular techniques for determining the condition of various motor components. However, in the case of inverter powered systems, the condition of a motor is difficult to determine from the stator current because fault signatures could overlap with other signatures produced by the inverter, low-slip operation, load oscillations, and other non-stationary conditions. This paper presents a speed signature analysis methodology for a reliable broken rotor bar diagnosis in inverter-fed induction motors. The proposed fault detection is based on tracking the speed fault signature in the time-frequency domain. As a result, different fault severity levels and load oscillations can be identified. The promising results show that this technique can be a good complement to the classic analysis of current signature analysis and reveals a high potential to overcome some of its drawbacks. 2021-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83243 Transient motor current signature analysis has become a mature technique for fault detection in induction motors. By using start-up transients, the whole range of slip in the machine is exploited to generate well defined fault-frequency patterns. However, in the inverter-fed motor case, the fault patterns are always close to the supply frequency and often of low amplitude. Therefore, it is difficult to distinguish and localize the fault-patterns. In this paper, a novel method is proposed to create a new fault pattern; the proposed technique can concentrate the fault harmonic in a specific frequency bandwidth and avoid the spectral leakage by reducing the supply frequency amplitude. The methodology has been validated through experimental tests carried out to detect broken rotor bar in an induction motor started through a voltage source inverter. 2019-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83242 Fault detection in inverter-fed induction motors (IMs) is an actual industrial need. Many line-fed machines are being replaced by inverter-fed drives for improving control during startup and also for saving energy. Broken rotor bars (BRBs) in IMs is one of the most difficult faults to be detected, particularly when the motor is fed by an inverter in a soft startup. The difficulty of detecting BRBs is that the characteristic fault-related frequencies are very close to the fundamental frequency, and the amplitude of the fundamental is significantly higher than the fault-related frequency components. This paper proposes an effective method that allows the detection of the BRB fault in inverter-fed IMs during a soft startup transient based on a non-uniform resampling algorithm. The proposed algorithm transforms the nonstationary fundamental frequency into a stationary component by non-uniform resampling, whereas the fault-related components are considerably separated from the fundamental one, making easier to follow their evolution during the startup transient. Simulation and experimental results demonstrate the effectiveness of the proposed method to detect the fault. 2017-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/79218 La iniciación al trabajo práctico en laboratorio presenta dificultades habituales para los estudiantes de ingeniería. Entre las posibles dificultades se encuentran: la inseguridad, el desconocimiento de los equipos, la falta de preparación previa y la comprensión incompleta de los conceptos fundamentales. Para abordar estas limitaciones, se ha diseñado una herramienta de diagnóstico capaz de evaluar de forma rápida y objetiva las competencias del estudiante. Este trabajo muestra los resultados obtenidos con la aplicación de esta herramienta en una prueba piloto realizada durante las prácticas de laboratorio de la asignatura de Electrotecnia, de la Escuela de Ingenierías Industriales, durante el curso 2024-2025. Los resultados mostraron que la herramienta permite detectar deficiencias en conocimientos de seguridad eléctrica y razonamiento analítico en la resolución de problemas, facilitando la autoevaluación y ofreciendo retroalimentación inmediata al estudiante. 2025-11-21T00:00:00Z https://uvadoc.uva.es/handle/10324/78225 Hydrogen (H2) used as feedstock (i.e., as raw material) in chemicals, refineries, and steel is currently produced from fossil fuels, thus leading to significant carbon dioxide (CO2) emissions. As these hard-to-abate sectors have limited electrification alternatives, H2 produced by electrolysis offers a potential option for decarbonising them. Existing modelling analyses to date provide limited insights due to their predominant use of sector-specific, static, non-recursive, and non-open models. This paper advances research by presenting a dynamic, recursive, open-access energy model using System Dynamics to study long-term systemic and environmental impacts of transitioning from fossil-based methods to electrolytic H2 production for industrial feedstock. The regional model adopts a bottom-up approach and is applied to the EU across five innovative decarbonisation scenarios, including varying technological transition speeds and a paradigm-shift scenario (Degrowth). Our results indicate that, assuming continued H2 demand trends and large-scale electrolytic H2 deployment by 2030, grid decarbonisation in the EU must accelerate to ensure green H2 for industrial feedstock emits less CO2 than fossil fuel methods, doubling the current pace. Otherwise, electrolytic H2 won’t offer clear CO2 reduction benefits until 2040. The most effective CO2 emission mitigation occurs in growth-oriented ambitious decarbonisation ( 91 %) and Degrowth ( 97 %) scenarios. From a sectoral perspective, H2 use in steel industry achieves significantly greater decarbonisation ( 97 %). However, meeting electricity demand for electrolytic H2 (700–1180 TWh in 2050 for 14–22.5 Mtons) in growth-oriented scenarios would require 25 %–42 % of the EU’s current electricity genera- tion, exceeding current renewable capacity and placing significant pressure on future power system development. 2025-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/77253 Robust speed estimation in induction motors (IM) is essential for control systems (espe- cially in sensorless drive applications) and condition monitoring. Traditional model-based techniques for inverter-fed IM provide a high accuracy but rely heavily on precise motor parameter identification, requiring multiple sensors to monitor the necessary variables. In contrast, model-independent methods that use rotor slot harmonics (RSH) in the sta- tor current spectrum offer a better adaptability to various motor types and conditions. However, many of these techniques are dependent on full-band processing, which reduces noise immunity and increases computational cost. This paper introduces a novel subband signal processing approach for rotor speed estimation focused on RSH tracking under both steady and non-steady states. By limiting spectral analysis to relevant content, the method significantly reduces computational demand. The technique employs an advanced time-frequency analysis for high-resolution frequency identification, even in noisy settings. Simulations and experiments show that the proposed approach outperforms conventional RSH-based estimators, offering a robust and cost-effective solution for integrated speed monitoring in practical applications. 2025-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75915 As the utilization of renewable energy continues to grow, microgrids have played a vital role in their generation. Batteries have emerged as the most commonly utilized storage system to effectively store this energy. This paper proposes a novel approach to manage energy consumption at the Centre for the Development of Renewable Energy (CEDER) by leveraging both lithium-ion and lead-acid batteries. This computer-based management system controls the flow of energy that can be charged or discharged in 15-minute intervals. By optimizing the use of both battery types, the energy consumption of CEDER has been reduced by an estimated 90 to 200 kWh, depending on the specific case study 2025-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75914 Simulating microgrids that incorporate electric vehicles and photovoltaic solar energy, along with their penetration levels, is a complex task that requires considering realistic grid parameters. This study presents an integrated simulation method using Python and OpenDSS, enabling researchers to analyze factors such as load curves, communication links, electric vehicle demand, photovoltaic generation, electric vehicle penetration levels, and connection event probability curves. Additionally, the software includes smoothing algorithms for solar radiation to mitigate voltage fluctuations. The simulation tool also allows for the evaluation of communication delays between the system aggregator and charging stations when modifying the charging setpoint at customer connection bars. The results indicate that communication delays significantly impact voltage stability at consumer connection points. Smoothing algorithms, such as the Savitzky-Golay filter, reduce voltage fluctuations by up to 8% in high PV penetration scenarios. Moreover, PV penetration levels around 0.6 were found to create the highest transformer loads, highlighting the need for adaptive control strategies. Voltage deviations at customer loads ranged from +1.5% to −3.2% depending on the delay time and PV penetration. 2025-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75913 The growth of photovoltaic power plants in both size and number has spurred the development of new approaches in inspection techniques. The most commonly employed methods include visual inspections, current-voltage measurements, infrared thermography, and luminescence imaging. Luminescence, rooted in the electromagnetic radiation capture of semiconductor structures that make up solar cells, proves effective in detecting various failures that may occur throughout the lifespan of a photovoltaic module. This phenomenon can be induced either by injecting current into the photovoltaic module (Electroluminescence) or through optical excitation using an appropriate light source (Photoluminescence). This paper offers an overview of the conventional outdoor luminescence imaging technique, delving into its applications and limitations. Additionally, it provides a comprehensive review of innovative outdoor luminescence technique approaches. These novel techniques aim to address several limitations of conventional methods, such as the considerably lower luminescence emission intensity compared to solar radiation, the need for external energy sources for current injection, the required acquisition time, and the necessity of disconnecting the solar module. 2024-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75758 The aggregate demand flexibility of a set of residential thermostatically controlled loads (TCLs) can be represented by a virtual battery (VB) in order to manage their participation in the electricity markets. For this purpose, it is necessary to know in advance and with a high level of reliability the maximum power that can be supplied by the aggregation of TCLs. A probability function of the power that can be supplied by a VB is introduced in this paper. This probability function is used to predict the demand flexibility using a rigorous experimental probabilistic method based on a combination of Monte Carlo simulation and extremum search by bisection (MC&ESB) algorithm. As a result, the maximum flexibility power that a VB can provide is obtained. MC&ESB performs the demand flexibility prediction with a given confidence level and taking into account TCLs and users? real-time constraints, which is a novel contribution. The performance and validity of the proposed method are demonstrated and discussed in three different case studies where a VB bids its aggregate power in the Spanish electricity balancing markets (SEBMs). 2025-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75757 In recent years, the interest in electric direct current (DC) technologies (such as converters, batteries, and electric vehicles) has increased due to their potential in energy efficiency and sustainability. However, the vast majority of electric systems and networks are based on alternating current (AC) as they also have certain advantages regarding cost-effective transport and robustness. In this paper, an AC/DC optimal power flow method for hybrid microgrids and several key performance indicators (KPIs) for its techno-economic assessment are presented. The combination of both calculations allows users to determine the viability of their hybrid microgrids. AC/DC networks have been modeled considering their most common elements. For the power flow method, polynomial optimization is formulated considering four different objective functions: the minimization of energy losses, voltage deviation, and operational costs and the maximization of the microgrid generation. The power flow method and the techno–economic analysis are implemented in Python and validated in the Centro de Desarrollo de Energías Renovables (CEDER) demonstrator for TIGON. The results show that the calculated power flow variables and those measured at CEDER are practically the same. In addition, the KPIs are obtained and compared for four operating scenarios: baseline, no battery, battery flexibility, and virtual battery (VB) flexibility. The last scenario results in the most profitable option. 2024-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75756 A decarbonized economy implies deep structural changes across industries, including the power system, whose operation needs to balance supply and demand instantaneously. The energy planning community usually work with hourly-resolution tools, while the integrated assessment community do so with the year as the time unit. This article describes a model that integrates both time frames to consider limitations and competition among suppliers of electricity in long-term scenarios, with Spain as the case of study. The calibration was carried out over four historical years (2017-2020, including the impact of Covid) to show both the sensitivity of different meteorological conditions and differences in the ranking of priorities to supply power. The results show values below Spain’s objective of 74% presence of renewables in the electricity mix in 2030; while this objective is reached by our own proposal. 2024-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75728 Partiendo del concepto de la energía como base civilizatoria y como recurso fundamental para cualquier actividad humana, llegamos al concepto de metabolismo que nos acerca al hecho de que el uso de un recurso provoca la aparición de un residuo, residuos que tienen una serie de consecuencias ecológicas que no están resueltas y que amenazan a esa misma civilización. Desde los años 70, pensadores como Georgescu-Roegen, Meadows, y Daly alertaron sobre el agotamiento de recursos y el cambio climático. La revolución industrial, basada en combustibles fósiles, permitió un excedente energético sin precedentes, pero también generó dependencia de los recursos no renovables. El concepto de "desarrollo sostenible" (Informe Brundtland, 1988) no se ha cumplido, ya que el consumo de combustibles fósiles y las emisiones han seguido aumentando. La extracción de petroleo convencional ya llegó a su pico, lo que implica escasez futura y fin de la energía barata. La transición energética basada en el coche eléctrico y en la infraestructura de generación renovable continua dependiendo de los combustibles fósiles para su producción y mantenimiento, creando una "trampa energética" y, además, exige un aumento de la extracción de minerales que ya padecen riesgos de escasez y conflictos geopolíticos. Además, la minería de estos materiales se concentra en América Latina, África y Asia, exacerbando desigualdades ambientales y sociales. Se necesitan estrategias que combinen reducción de consumo, equidad y tecnologías viables, reduciendo presión sobre los límites planetarios. 2023-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75727 The Spanish national energy and climate plan (PNIEC) has recently been published, leading the worldwide task of climate change mitigation towards a net zero-carbon economy by 2050. The objective scenario of the PNIEC expects to reach a renewable share in the power system of 74% by 2030. In this context, three contributions are developed: i) providing an analysis of how Spain is facing the energy transition; ii) conceptualizing the link between an hourly energy model (EnergyPLAN) and a yearly integrated assessment model (MEDEAS); and iii) proposing a transparent policy agenda for the Spanish benchmarking in line with the official report. The results clarify the decreasing role such technologies as the combined heat and power facilities, as well as the pressure of biomass in Spain. Coherency in translating common variables in the energy chain of IAMs to the energy model is effectively reflected in the tables as an output of the research. Positive conclusions are found for Spain. The commitment of 74% might well be completed and the Spanish economy could run with a 100% renewable energy system by 2050, with requirements of sixteen and six times more installed capacity of solar-PV and wind onshore, respectively, by 2050 related to 2017. 2022-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75726 Long term-energy planning has gradually moved towards finer temporal and spatial resolutions of the energy system to design the decarbonization of the society. However, integrated assessment models (IAMs), focusing on a broader concept of sustainability transition, are typically yearly-resolution models which complicates capturing the specific supply-demand dynamics, relevant in the transition towards renewable energy sources (RES). Different methods for introducing sub-annual information are being used in IAMs, but the hourly representation of variable RES remains challenging. This article presents a method to translate the main dynamics of an hourly-resolution energy model into a yearly-resolution model. Here we test our method with the current European Union region (EU-27) by configuring and applying the hourly-resolution EnergyPLAN. Multiple linear regression analysis is applied to 174960 simulations (set by varying 39 inputs by clusters and reaching 100% renewable systems), relating the adjusted capacity factors of the technologies as well as the variation of electricity demand and natural gas consumption as a function of the options installed to manage the variable RES. The obtained results allow validation of the developed approach, which shows to be flexible and easily generalizable enough to be applied to any couple of hourly and annual-resolution models and/or country. 2022-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/75628 Electroluminescence imaging is increasingly used in photovoltaic power plant inspections due to its effectiveness in detecting various types of failures in solar cells. This article presents a novel technique that enables the modulation of an arbitrary electroluminescence signal in PV modules using an electronic device that controls the signal by modulating an arbitrary current waveform in a photovoltaic module, utilizing the string current as its energy source. As a result, measurements do not require a power supply and can be performed during the normal operation of a PV string. Throughout the paper, this method is compared to a more conventional approach that relies solely on a power supply to generate the current signal. Capturing a sequence of images while modulating the current with different waveforms allows the application of the Fast Fourier Transform to suppress background signals caused by sunlight, resulting in high-quality EL images. Experimental results demonstrate that the proposed method delivers imaging quality comparable to that achieved with a power supply, while effectively detecting a broad range of solar cell failures. Furthermore, the calculated signal-to-noise ratio for both approaches yields similar values, indicating comparable quality in quantitative terms. Finally, square wave modulation has shown slightly better performance than other waveforms, such as sinusoidal and half-sinusoidal modulation. 2025-01-01T00:00:00Z