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SMEs are asked to incorporate sustainable energy solutions into their organizations' processes to be environmentally friendly and operate more effectively. In this regard, IoT-based technologies seem to have the potential to monitor and optimize energy use. However, more extensive research is required to assess the efficacy of such solutions in the context of SMEs. Despite the growing interest in the Internet of Things (IoT) for renewable energy, there is a lack of information on how well these solutions work for small and medium-sized enterprises (SMEs). While much of the existing literature addresses the application of new technologies in SMEs, the social background underlying their transformation received relatively little attention in previous years. The present research adopts a quantitative approach, employing time series forecasting, specifically long short-term memory networks (LSTM). This paper uses IoT-based approaches to collect and preprocess an energy consumption dataset from various SMEs. The LSTM model is intended to forecast energy consumption in the future based on experience. In terms of analysis, the study adopts Python for data preprocessing, constructing, and assessing models. The main findings reveal a strong positive correlation (r = 0.85) between base energy consumption and overall energy usage, suggesting that optimizing base consumption is crucial for energy efficiency. In contrast, investment in RETs and staff training demonstrate weak correlations (r = 0.25 and r = 0.30, respectively) with energy consumption, indicating that these factors alone are insufficient for significant energy savings. The long short-term memory model used in the study accurately predicted future energy consumption trends with a mean absolute error of 5%. However, it struggled with high-frequency variations, showing up to 15% of mistakes. This research contributes to the literature in line with IoT-based sustainable energy solutions in SMEs, which has not been widely addressed. The findings highlight the critical role of integrating renewable energy technologies (RETs) and fostering a culture of energy efficiency, offering actionable insights for policymakers and business owners. With the application of Python in data analysis and model creation, this research shows a real-world approach to handling issues in sustainable energy management for SMEs. [ABSTRACT FROM AUTHOR]

Induction motors dominate industrial applications due to their unwavering reliability. However, optimal vector control, critical for maximizing dynamic performance, hinges on accurate parameter estimation. This control strategy necessitates precise knowledge of the motor's parameters, obtainable through experimentation or calculation based on its design specifications. Numerous methods, ranging from traditional to computational, have been proposed by various researchers, often relying on specific assumptions that might compromise the performance of modern motor control techniques. This paper meticulously reviews the most frequently utilized methods and presents experimental results from a single motor. We rigorously compare these results against established benchmark methods, including IEEE Standard 112-2017, and subsequently identify the superior approach, boasting a maximum error of only 6.5% compared to 19.65% for competing methods. Our study investigates the parameter estimation of induction motor. The methodology primarily utilizes RMS values for measurement tasks. Moreover, the impact of harmonics, particularly when an induction motor is supplied by an inverter is briefly addressed. The pioneering contribution of this work lies in pinpointing a more accurate parameter estimation method for enhanced vector control performance. These findings pave the way for exceptional vector control, particularly at lower speeds, ultimately elevating both vector control and drive performance. [ABSTRACT FROM AUTHOR]

Significant advancements in the field of power electronics have created an ideal opportunity to introduce various topologies of multilevel inverters. These multilevel inverter topologies comprise different notable characteristics, such as staircase sinusoidal output voltage with high quality, a lowered number of power switches, no filter requirement, etc. In this literature, a new asymmetrical MLI topology is proposed to reduce the number of components of the inverter with admirable voltage-step creation. The proposed topology provides a 17-level, staircase-type, nearly sinusoidal output voltage waveform. The number of switches required for the proposed multilevel inverter topology is fewer compared to the existing topology for the same level. A carrier-based sinusoidal pulse-width modulation technique is used for the proposed topology at a switching frequency of 3 kHz. The functioning of the proposed inverter topology is thoroughly examined. A 17-level asymmetrical inverter is executed; both the MATLAB/SIMULINK as well as the experimental results using dSPACE-1103 controller. The simulation results are verified using the experimental results for the proposed 17-level multilevel inverter for modulation indexes of 1 and 0.6. [ABSTRACT FROM AUTHOR]

This research paper introduces a new topology for multilevel inverters, emphasizing the reduction of harmonic distortion and the optimization of the component count. The complexity of an inverter is determined by the number of power switches, which is significantly reduced in the presented topology, as fewer switches require fewer driver circuits. In this proposed topology, a new single-phase generalized multilevel inverter is analyzed with an equal magnitude of voltage supply. A 9-level, 11-level, or 13-level symmetrical inverter with RL load is analyzed in MATLAB/Simulink 2019b and then experimentally validated using the dSPACE-1103 controller. The experimental verification of the load voltage and current with different modulation indices is also presented. The analysis of the proposed topology concludes that the total required number of components is lower than that necessary for the classical inverter topologies, as well as for some new proposed multilevel inverters that are also compared with the proposed topology in terms of gate driver circuits, power switches, and DC sources, which thereby enhances the goodness of the proposed topology. Thus, a comparison of this inverter with the other topologies validates its acceptance. [ABSTRACT FROM AUTHOR]

When tracking the peak power point in PV systems, incremental conductance is the most common technique used. This approach preserves the first trap in the local peak power point, but it is unable to quickly keep up with the ever-changing peak power point under varying irradiance and temperature conditions. In this paper, the authors propose a hybrid algorithm, combining an artificial ecosystem optimizer and an incremental-conductance-based MPPT to solve these issues of traditional MPPT under varying irradiance and temperature conditions. The proposed hybrid algorithm has been applied to three scenarios, namely the constant irradiance condition, the varying irradiance condition, and the varying temperature condition. Under the constant irradiance condition, the PV array is maintained at a temperature of 25 °C and an irradiance of 1000 W / m 2 . The voltage of the DC link of the neutral-pointed-clamped inverter is maintained at 1000 V. Under the varying irradiance condition, the irradiance of the PV array is increased from 400   W / m 2   to 1000 W / m 2 with a step size of 0.2 s. The same step size is maintained while decreasing the irradiance level from 1000 W / m 2 to 400 W / m 2 ,   with a step change of 0.2 s. However, the temperature is maintained at 25 °C. Under the varying temperature condition, the temperature of the PV array varies from 35 °C, 25 °C, 15 °C, 10 °C, 15 °C, 25 °C, and 35 °C with a step size of 0.2 s, and the irradiance is maintained at 1000   W / m 2 . The DC link voltage in all three conditions is maintained at 1000 V, which confirms that the hybrid algorithm has been able to vary the duty cycle of the pulse wave modulation generator in such a manner that the variable DC voltage produced by the PV array has been changed by the flyback converter into a stable DC voltage. The simulation results show that the total harmonic distortion (THD) under all the simulated scenarios is within 5%, which agrees with IEEE standards. In the future, this algorithm may be compared with other types of available MPPTs under partial shading. [ABSTRACT FROM AUTHOR]

Electrostatic discharge (ESD) is a physical phenomenon that may destroy electronic components due to its high discharge current that may reach a few amperes in just a few ns. However, another major aspect of ESD is the related high-frequency electromagnetic (E/M) fields radiated by the ESD event. The electronic equipment that is affected by the ESD phenomenon is additionally affected by the induced voltages caused by these E/M fields. This is the reason that the current version of the IEC 61000-4-2 on ESD has a special reference to these fields and the measurement setup. Starting with the classical formulation of these fields, this paper reviews the most popular techniques for calculating the ESD electromagnetic fields while also emphasizing the best methods for minimizing computational effort. There is also a separate section for the measurement techniques that have been applied in research works, whose outcomes could be implemented in the next revision of the IEC 61000-4-2. It is extremely important for the next revision to include these measurement setups and the E/M field sensors because the ESD generators should comply with certain values related to the E/M fields they produce. [ABSTRACT FROM AUTHOR]

Many citizens of European countries may soon experience a long and extensive blackout. The lack of predictability in the output of renewable energy sources, aggravating the problem of consistently matching supply with demand on electric grids, along with cyber-attacks or even worse unpredictable incidents in the electric grid are some factors that may mean a blackout is much more likely than in previous years. This paper covers the possibility of an extensive blackout in a country of the interconnected European electricity transmission system or, even worse, a blackout in a wide area of the European continent. The topic of this paper becomes even more important and timely given the energy crisis due to the war in Ukraine, which has made the possibility of a blackout in the winter of 2022–2023 high. First, the major European blackouts that occurred in the past 20 years are presented, examining their causes. On 8 January 2021, the European electricity grid was divided into two separate sections, with different frequencies; some additional scenarios are considered which, if they had happened, could have led to blackouts in some European countries or, even worse, a wide area of Europe. This work also examines how to avoid such an eventuality, as well as how European TSOs should react in case a blackout occurs. Focused on the fast and reliable supply of consumers after a blackout, a novel restoration strategy based on the A* Algorithm is presented. Its efficiency is validated in the IEEE-39 and IEEE-68 bus systems. [ABSTRACT FROM AUTHOR]