Technologies

2024

Jump to: 2023

11 pages, 1039 KiB

Open AccessArticle

Granular Weighted Fuzzy Approach Applied to Short-Term Load Demand Forecasting

by Cesar Vinicius Züge and Leandro dos Santos Coelho

Technologies 2024, 12(10), 182; https://doi.org/10.3390/technologies12100182 - 1 Oct 2024

Viewed by 1466

Abstract

The development of accurate models to forecast load demand across different time horizons is challenging due to demand patterns and endogenous variables that affect short-term and long-term demand. This paper presents two contributions. First, it addresses the problem of the accuracy of the [...] Read more.

The development of accurate models to forecast load demand across different time horizons is challenging due to demand patterns and endogenous variables that affect short-term and long-term demand. This paper presents two contributions. First, it addresses the problem of the accuracy of the probabilistic forecasting model for short-term time series where endogenous variables interfere by emphasizing a low computational cost and efficient approach such as Granular Weighted Multivariate Fuzzy Time Series (GranularWMFTS) based on the fuzzy information granules method and a univariate form named Probabilistic Fuzzy Time Series. Secondly, it compares time series forecasting models based on algorithms such as Holt-Winters, Auto-Regressive Integrated Moving Average, High Order Fuzzy Time Series, Weighted High Order Fuzzy Time Series, and Multivariate Fuzzy Time Series (MVFTS) where this paper is based on Root Mean Squared Error, Symmetric Mean Absolute Percentage Error, and Theil’s U Statistic criteria relying on 5% error criteria. Finally, it presents the concept and nuances of the forecasting approaches evaluated, highlighting the differences between fuzzy algorithms in terms of fuzzy logical relationship, fuzzy logical relationship group, and fuzzification in the training phase. Overall, the GranularWMVFTS and weighted MVFTS outperformed other evaluated forecasting approaches regarding the performance criteria adopted with a low computational cost. Full article

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21 pages, 2290 KiB

Open AccessArticle

Red-Billed Blue Magpie Optimizer for Electrical Characterization of Fuel Cells with Prioritizing Estimated Parameters

by Attia A. El-Fergany and Ahmed M. Agwa

Technologies 2024, 12(9), 156; https://doi.org/10.3390/technologies12090156 - 8 Sep 2024

Viewed by 2157

Abstract

The red-billed blue magpie optimizer (RBMO) is employed in this research study to address parameter extraction in polymer exchange membrane fuel cells (PEMFCs), along with three recently implemented optimizers. The sum of squared deviations (SSD) between the simulated and measured stack voltages defines [...] Read more.

The red-billed blue magpie optimizer (RBMO) is employed in this research study to address parameter extraction in polymer exchange membrane fuel cells (PEMFCs), along with three recently implemented optimizers. The sum of squared deviations (SSD) between the simulated and measured stack voltages defines the fitness function of the optimization problem under investigation subject to a set of working constraints. Three distinct PEMFCs stacks models—the Ballard Mark, Temasek 1 kW, and Horizon H-12 units—are used to illustrate the applied RBMO’s feasibility in solving this challenge in comparison to other recent algorithms. The highest percentages of biased voltage per reading for the Ballard Mark V, Temasek 1 kW, and Horizon H-12 are, respectively, +0.65%, +0.20%, and −0.14%, which are negligible errors. The primary characteristics of PEMFC stacks under changing reactant pressures and cell temperatures are used to evaluate the precision of the cropped optimized parameters. In the final phase of this endeavor, the sensitivity of the cropped parameters to the PEMFCs model’s performance is investigated using two machine learning techniques, namely, artificial neural network and Gaussian process regression models. The simulation results demonstrate that the RBMO approach extracts the PEMFCs’ appropriate parameters with high precision. Full article

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21 pages, 5219 KiB

Open AccessArticle

Ensemble Learning for Nuclear Power Generation Forecasting Based on Deep Neural Networks and Support Vector Regression

by Jorge Gustavo Sandoval Simão and Leandro dos Santos Coelho

Technologies 2024, 12(9), 148; https://doi.org/10.3390/technologies12090148 - 2 Sep 2024

Viewed by 2039

Abstract

Forecasting nuclear energy production is essential for market operations such as security, economic efficiency, resource optimization, grid stability, and the integration of renewable energy sources. Forecasting approaches allow nuclear power plants to operate consistently, contributing to the overall reliability and long-term viability of [...] Read more.

Forecasting nuclear energy production is essential for market operations such as security, economic efficiency, resource optimization, grid stability, and the integration of renewable energy sources. Forecasting approaches allow nuclear power plants to operate consistently, contributing to the overall reliability and long-term viability of the energy system. It is noted that energy systems researchers are increasingly interested in machine learning models used to face the challenge of time series forecasting. This study evaluates a hybrid ensemble learning of three time series forecasting models including least-squares support vector regression, gated recurrent unit, and long short-term memory models applied to nuclear power time series forecasting on the dataset of French power plants from 2009 to 2020. Furthermore, this research evaluates forecasting results in which approaches are directed towards the optimized RreliefF (Robust relief Feature) selection algorithm using a hyperparameter optimization based on tree-structured Parzen estimator and following an ensemble learning approach, showing promising results in terms of performance metrics. The suggested ensemble learning model, which combines deep learning and the RreliefF algorithm using a hold-out, outperforms the other nine forecasting models in this study according to performance criteria such as 75% for the coefficient of determination, a root squared error average of 0.108, and an average absolute error of 0.080. Full article

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20 pages, 4305 KiB

Open AccessArticle

Experimental Benchmarking of Existing Offline Parameter Estimation Methods for Induction Motor Vector Control

by Butukuri Koti Reddy, Krishna Sandeep Ayyagari, Yemula Pradeep Kumar, Nimay Chandra Giri, Panganamamula Venkata Rajgopal, Georgios Fotis and Valeri Mladenov

Technologies 2024, 12(8), 123; https://doi.org/10.3390/technologies12080123 - 1 Aug 2024

Viewed by 1823

Abstract

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 [...] Read more.

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. Full article

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16 pages, 12863 KiB

Open AccessFeature PaperArticle

Multi-Objective Optimisation of the Battery Box in a Racing Car

by Chao Ma, Caiqi Xu, Mohammad Souri, Elham Hosseinzadeh and Masoud Jabbari

Technologies 2024, 12(7), 93; https://doi.org/10.3390/technologies12070093 - 25 Jun 2024

Viewed by 1975

Abstract

The optimisation of electric vehicle battery boxes while preserving their structural performance presents a formidable challenge. Many studies typically involve fewer than 10 design variables in their optimisation processes, a deviation from the reality of battery box design scenarios. The present study, for [...] Read more.

The optimisation of electric vehicle battery boxes while preserving their structural performance presents a formidable challenge. Many studies typically involve fewer than 10 design variables in their optimisation processes, a deviation from the reality of battery box design scenarios. The present study, for the first time, attempts to use sensitivity analysis to screen the design variables and achieve an efficient optimisation design with a large number of original design variables. Specifically, the sensitivity analysis method was proposed to screen a certain number of optimisation variables, reducing the computational complexity while ensuring the efficiency of the optimisation process. A combination of the Generalised Regression Neural Network (GRNN) and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) was employed to construct surrogate models and solve the optimisation problem. The optimisation model integrates these techniques to balance structural performance and weight reduction. The optimisation results demonstrate a significant reduction in battery box weight while maintaining structural integrity. Therefore, the proposed approach in this study provides important insights for achieving high-efficiency multi-objective optimisation of battery box structures. Full article

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13 pages, 5825 KiB

Open AccessArticle

A Modified Criss-Cross-Based T-Type MLI with Reduced Power Components

by Kailash Kumar Mahto, Bidyut Mahato, Bikramaditya Chandan, Durbanjali Das, Priyanath Das, Swati Kumari, Vasiliki Vita, Christos Pavlatos and Georgios Fotis

Technologies 2024, 12(6), 90; https://doi.org/10.3390/technologies12060090 - 18 Jun 2024

Viewed by 1557

Abstract

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, [...] Read more.

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. Full article

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15 pages, 5227 KiB

Open AccessArticle

New Upgrade to Improve Operation of Conventional Grid-Connected Photovoltaic Systems

by Manuel Cáceres, Alexis Raúl González Mayans, Andrés Firman, Luis Vera and Juan de la Casa Higueras

Technologies 2024, 12(5), 61; https://doi.org/10.3390/technologies12050061 - 2 May 2024

Viewed by 1657

Abstract

The incorporation of distributed generation with photovoltaic systems entails a drawback associated with intermittency in the generation capacity due to variations in the solar resource. In general, this aspect limits the level of penetration that this resource can have without producing an appreciable [...] Read more.

The incorporation of distributed generation with photovoltaic systems entails a drawback associated with intermittency in the generation capacity due to variations in the solar resource. In general, this aspect limits the level of penetration that this resource can have without producing an appreciable impact on the quality of the electrical supply. With the intention of reducing its intermittency, this paper presents the characterization of a methodology for maximizing grid-connected PV system operation under low-solar-radiation conditions. A new concept of a hybrid system based on a constant current source and capable of integrating different sources into a conventional grid-connected PV system is presented. Results of an experimental characterization of a low-voltage grid–PV system connection with a DC/DC converter for constant-current source application are shown in zero and non-zero radiation conditions. The results obtained demonstrate that the proposed integration method works efficiently without causing appreciable effects on the parameters that define the quality of the electrical supply. In this way, it is possible to efficiently incorporate another source of energy, taking advantage of the characteristics of the GCPVS without further interventions in the system. It is expected that this topology could help to integrate other generation and/or storage technologies into already existing PV systems, opening a wide field of research in the PV systems area. Full article

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19 pages, 1747 KiB

Open AccessReview

Past, Present, and Future of New Applications in Utilization of Eddy Currents

by Nestor O. Romero-Arismendi, Juan C. Olivares-Galvan, Jose L. Hernandez-Avila, Rafael Escarela-Perez, Victor M. Jimenez-Mondragon and Felipe Gonzalez-Montañez

Technologies 2024, 12(4), 50; https://doi.org/10.3390/technologies12040050 - 9 Apr 2024

Cited by 4 | Viewed by 4459

Abstract

Eddy currents are an electromagnetic phenomenon that represent an inexhaustible source of inspiration for technological innovations in the 21st century. Throughout history, these currents have been a subject of research and technological development in multiple fields. This article delves into the fascinating world [...] Read more.

Eddy currents are an electromagnetic phenomenon that represent an inexhaustible source of inspiration for technological innovations in the 21st century. Throughout history, these currents have been a subject of research and technological development in multiple fields. This article delves into the fascinating world of eddy currents, revealing their physical foundations and highlighting their impact on a wide range of applications, ranging from non-destructive evaluation of materials to levitation phenomena, as well as their influence on fields as diverse as medicine, the automotive industry, and aerospace. The nature of eddy currents has stimulated the imaginations of scientists and engineers, driving the creation of revolutionary technologies that are transforming our society. As we progress through this article, we will cover the main aspects of eddy currents, their practical applications, and challenges for future works. Full article

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21 pages, 5583 KiB

Open AccessArticle

Performance Assessment of Different Sustainable Energy Systems Using Multiple-Criteria Decision-Making Model and Self-Organizing Maps

by Satyabrata Dash, Sujata Chakravarty, Nimay Chandra Giri, Umashankar Ghugar and Georgios Fotis

Technologies 2024, 12(3), 42; https://doi.org/10.3390/technologies12030042 - 19 Mar 2024

Cited by 6 | Viewed by 2632

Abstract

The surging demand for electricity, propelled by the widespread adoption of intelligent grids and heightened consumer interaction with electricity demand and pricing, underscores the imperative for precise prognostication of optimal power plant utilization. To confront this challenge, a dataset centered on issue-centric power [...] Read more.

The surging demand for electricity, propelled by the widespread adoption of intelligent grids and heightened consumer interaction with electricity demand and pricing, underscores the imperative for precise prognostication of optimal power plant utilization. To confront this challenge, a dataset centered on issue-centric power plans is meticulously crafted. This dataset encapsulates pivotal facets indispensable for attaining sustainable power generation, including meager gas emissions, installation cost, low maintenance cost, elevated power generation, and copious resource availability. The selection of an optimal power plant entails a multifaceted decision-making process, demanding a systematic approach. Our research advocates the amalgamation of multiple-criteria decision-making (MCDM) models with self-organizing maps to gauge the efficacy of diverse sustainable energy systems. The examination discerns solar energy as the preeminent MCDM criterion, securing the apex position with a score of 83.4%, attributable to its ample resource availability, considerable energy generation, nil greenhouse gas emissions, and commendable efficiency. Wind and hydroelectric power closely trail, registering scores of 75.3% and 74.5%, respectively, along with other energy sources. The analysis underscores the supremacy of the renewable energy sources, particularly solar and wind, in fulfilling sustainability objectives and scrutinizing factors such as cost, resource availability, and the environmental impact. The proposed methodology empowers stakeholders to make judicious decisions, accentuating facets that are required for more sustainable and resilient power infrastructure. Full article

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16 pages, 1505 KiB

Open AccessFeature PaperArticle

Angle Calculus-Based Thrust Force Determination on the Blades of a 10 kW Wind Turbine

by José Rafael Dorrego-Portela, Adriana Eneida Ponce-Martínez, Eduardo Pérez-Chaltell, Jaime Peña-Antonio, Carlos Alberto Mateos-Mendoza, José Billerman Robles-Ocampo, Perla Yazmin Sevilla-Camacho, Marcos Aviles and Juvenal Rodríguez-Reséndiz

Technologies 2024, 12(2), 22; https://doi.org/10.3390/technologies12020022 - 5 Feb 2024

Cited by 2 | Viewed by 2123

Abstract

In this article, the behavior of the thrust force on the blades of a 10 kW wind turbine was obtained by considering the characteristic wind speed of the Isthmus of Tehuantepec. Analyzing mechanical forces is essential to efficiently and safely design the different [...] Read more.

In this article, the behavior of the thrust force on the blades of a 10 kW wind turbine was obtained by considering the characteristic wind speed of the Isthmus of Tehuantepec. Analyzing mechanical forces is essential to efficiently and safely design the different elements that make up the wind turbine because the thrust forces are related to the location point and the blade rotation. For this reason, the thrust force generated in each of the three blades of a low-power wind turbine was analyzed. The angular position (

θ

) of each blade varied from 0° to 120°, the blades were segmented (r), and different wind speeds were tested, such as cutting, design, average, and maximum. The results demonstrate that the thrust force increases proportionally with increasing wind speed and height, but it behaves differently on each blade segment and each angular position. This method determines the angular position and the exact blade segment where the smallest and the most considerable thrust force occurred. Blade 1, positioned at an angular position of 90°, is the blade most affected by the thrust force on P15. When the blade rotates 180°, the thrust force decreases by 9.09 N; this represents a 66.74% decrease. In addition, this study allows the designers to know the blade deflection caused by the thrust force. This information can be used to avoid collision with the tower. The thrust forces caused blade deflections of 10% to 13% concerning the rotor radius used in this study. These results guarantee the operation of the tested generator under their working conditions. Full article

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15 pages, 3607 KiB

Open AccessArticle

An Optimum Load Forecasting Strategy (OLFS) for Smart Grids Based on Artificial Intelligence

by Asmaa Hamdy Rabie, Ahmed I. Saleh, Said H. Abd Elkhalik and Ali E. Takieldeen

Technologies 2024, 12(2), 19; https://doi.org/10.3390/technologies12020019 - 1 Feb 2024

Cited by 4 | Viewed by 2115

Abstract

Recently, the application of Artificial Intelligence (AI) in many areas of life has allowed raising the efficiency of systems and converting them into smart ones, especially in the field of energy. Integrating AI with power systems allows electrical grids to be smart enough [...] Read more.

Recently, the application of Artificial Intelligence (AI) in many areas of life has allowed raising the efficiency of systems and converting them into smart ones, especially in the field of energy. Integrating AI with power systems allows electrical grids to be smart enough to predict the future load, which is known as Intelligent Load Forecasting (ILF). Hence, suitable decisions for power system planning and operation procedures can be taken accordingly. Moreover, ILF can play a vital role in electrical demand response, which guarantees a reliable transitioning of power systems. This paper introduces an Optimum Load Forecasting Strategy (OLFS) for predicting future load in smart electrical grids based on AI techniques. The proposed OLFS consists of two sequential phases, which are: Data Preprocessing Phase (DPP) and Load Forecasting Phase (LFP). In the former phase, an input electrical load dataset is prepared before the actual forecasting takes place through two essential tasks, namely feature selection and outlier rejection. Feature selection is carried out using Advanced Leopard Seal Optimization (ALSO) as a new nature-inspired optimization technique, while outlier rejection is accomplished through the Interquartile Range (IQR) as a measure of statistical dispersion. On the other hand, actual load forecasting takes place in LFP using a new predictor called the Weighted K-Nearest Neighbor (WKNN) algorithm. The proposed OLFS has been tested through extensive experiments. Results have shown that OLFS outperforms recent load forecasting techniques as it introduces the maximum prediction accuracy with the minimum root mean square error. Full article

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31 pages, 13657 KiB

Open AccessArticle

A Comprehensive Performance Analysis of a 48-Watt Transformerless DC-DC Boost Converter Using a Proportional–Integral–Derivative Controller with Special Attention to Inductor Design and Components Reliability

by Kuldeep Jayaswal, D. K. Palwalia and Josep M. Guerrero

Technologies 2024, 12(2), 18; https://doi.org/10.3390/technologies12020018 - 30 Jan 2024

Cited by 3 | Viewed by 2350

Abstract

In this research paper, a comprehensive performance analysis was carried out for a 48-watt transformerless DC-DC boost converter using a Proportional–Integral–Derivative (PID) controller through dynamic modeling. In a boost converter, the optimal design of the magnetic element plays an important role in efficient [...] Read more.

In this research paper, a comprehensive performance analysis was carried out for a 48-watt transformerless DC-DC boost converter using a Proportional–Integral–Derivative (PID) controller through dynamic modeling. In a boost converter, the optimal design of the magnetic element plays an important role in efficient energy transfer. This research paper emphasizes the design of an inductor using the Area Product Technique (APT) to analyze factors such as area product, window area, number of turns, and wire size. Observations were made by examining its response to changes in load current, supply voltage, and load resistance at frequency levels of 100 and 500 kHz. Moreover, this paper extended its investigation by analyzing the failure rates and reliability of active and passive components in a 48-watt boost converter, providing valuable insights about failure behavior and reliability. Frequency domain analysis was conducted to assess the controller’s stability and robustness. The results conclusively underscore the benefits of incorporating the designed PID controller in terms of achieving the desired regulation and rapid response to disturbances at 100 and 500 kHz. The findings emphasize the outstanding reliability of the inductor, evident from the significantly low failure rates in comparison to other circuit components. Conversely, the research also reveals the inherent vulnerability of the switching device (MOSFET), characterized by a higher failure rate and lower reliability. The MATLAB^® Simulink platform was utilized to investigate the results. Full article

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2023

Jump to: 2024

30 pages, 22313 KiB

Open AccessEditor’s ChoiceArticle

Laplace Transform-Based Modelling, Surge Energy Distribution, and Experimental Validation of a Supercapacitor Transient Suppressor

by Sadeeshvara Silva Thotabaddadurage

Technologies 2023, 11(6), 173; https://doi.org/10.3390/technologies11060173 - 6 Dec 2023

Cited by 1 | Viewed by 2786

Abstract

The discovery of the transient-surge-withstanding capability of electrochemical dual-layer capacitors (EDLCs) led to the development of a unique, commercially beneficial circuit topology known as a supercapacitor transient suppressor (STS). Despite its low component count, the new design consists of a transient-absorbing magnetic core [...] Read more.

The discovery of the transient-surge-withstanding capability of electrochemical dual-layer capacitors (EDLCs) led to the development of a unique, commercially beneficial circuit topology known as a supercapacitor transient suppressor (STS). Despite its low component count, the new design consists of a transient-absorbing magnetic core which takes the form of a coupled inductor placed between the AC-main- and load-side varistors. With an introduction to the structural features of metal oxide varistors (MOVs), gas tubes, thyristors, and EDLCs, this research presents a frequency (S)-domain analysis of an STS circuit to accurately model the surge propagation through its coupled inductor. Transient energy distribution trends among STS components are estimated in this paper, with an emphasis on peak energies absorbed and dissipated by the various inductive, capacitive, and resistive circuit elements. Moreover, this study reveals STS transient-mode test waveforms validated by a standard lightning surge simulator with supporting simulation plots based on LTSpice numerical techniques. Both experimental and simulation results are consistent, with the analytical findings showing 90% of the peak transient propagating through the primary coil, whereas only 10% is shared into the secondary coil of the coupled inductor. In addition, it is proven that the two STS MOVs dissipate over 50% of the transient energy for a standard 6 kV/3 kA combinational surge, while the magnetic core absorbs over 20% of the energy. All test procedures conducted during this research adhere to IEEE C62.41/IEC 61000-4-5 standards. Full article

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52 pages, 10354 KiB

Open AccessEditor’s ChoiceReview

Application of Modeling and Control Approaches of Piezoelectric Actuators: A Review

by Mithun Kanchan, Mohith Santhya, Ritesh Bhat and Nithesh Naik

Technologies 2023, 11(6), 155; https://doi.org/10.3390/technologies11060155 - 1 Nov 2023

Cited by 9 | Viewed by 4456

Abstract

Piezoelectric actuators find extensive application in delivering precision motion in the micrometer to nanometer range. The advantages of a broader range of motion, rapid response, higher stiffness, and large actuation force from piezoelectric actuators make them suitable for precision positioning applications. However, the [...] Read more.

Piezoelectric actuators find extensive application in delivering precision motion in the micrometer to nanometer range. The advantages of a broader range of motion, rapid response, higher stiffness, and large actuation force from piezoelectric actuators make them suitable for precision positioning applications. However, the inherent nonlinearity in the piezoelectric actuators under dynamic working conditions severely affects the accuracy of the generated motion. The nonlinearity in the piezoelectric actuators arises from hysteresis, creep, and vibration, which affect the performance of the piezoelectric actuator. Thus, there is a need for appropriate modeling and control approaches for piezoelectric actuators, which can model the nonlinearity phenomenon and provide adequate compensation to achieve higher motion accuracy. The present review covers different methods adopted for overcoming the nonlinearity issues in piezoelectric actuators. This review highlights the charge-based and voltage-based control methods that drive the piezoelectric actuators. The survey also includes different modeling approaches for the creep and hysteresis phenomenon of the piezoelectric actuators. In addition, the present review also highlights different control strategies and their applications in various types of piezoelectric actuators. An attempt is also made to compare the piezoelectric actuator’s different modeling and control approaches and highlight prospects. Full article

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27 pages, 5171 KiB

Open AccessEditor’s ChoiceReview

Modern DC–DC Power Converter Topologies and Hybrid Control Strategies for Maximum Power Output in Sustainable Nanogrids and Picogrids—A Comprehensive Survey

by Anupama Ganguly, Pabitra Kumar Biswas, Chiranjit Sain and Taha Selim Ustun

Technologies 2023, 11(4), 102; https://doi.org/10.3390/technologies11040102 - 1 Aug 2023

Cited by 14 | Viewed by 3675

Abstract

Sustainable energy exhibited immense growth in the last few years. As compared to other sustainable sources, solar power is proved to be the most feasible source due to some unanticipated characteristics, such as being clean, noiseless, ecofriendly, etc. The output from the solar [...] Read more.

Sustainable energy exhibited immense growth in the last few years. As compared to other sustainable sources, solar power is proved to be the most feasible source due to some unanticipated characteristics, such as being clean, noiseless, ecofriendly, etc. The output from the solar power is entirely unpredictable since solar power generation is dependent on the intensity of solar irradiation and solar panel temperature. Further, these parameters are weather dependent and thus intermittent in nature. To conquer intermittency, power converters play an important role in solar power generation. Generally, photovoltaic systems will eventually suffer from a decrease in energy conversion efficiency along with improper stability and intermittent properties. As a result, the maximum power point tracking (MPPT) algorithm must be incorporated to cultivate maximum power from solar power. To make solar power generation reliable, a proper control technique must be added to the DC–DC power converter topologies. Furthermore, this study reviewed the progress of the maximum power point tracking algorithm and included an in-depth discussion on modern and both unidirectional and bidirectional DC–DC power converter topologies for harvesting electric power. Lastly, for the reliability and continuity of the power demand and to allow for distributed generation, this article also established the possibility of integrating solar PV systems into nanogrids and picogrids in a sustainable environment. The outcome of this comprehensive survey would be of strong interest to the researchers, technologists, and the industry in the relevant field to carry out future research. Full article

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21 pages, 89425 KiB

Open AccessCommunication

FPGA-Based Implementation of a New 3-D Multistable Chaotic Jerk System with Two Unstable Balance Points

by Sundarapandian Vaidyanathan, Esteban Tlelo-Cuautle, Khaled Benkouider, Aceng Sambas and Brisbane Ovilla-Martínez

Technologies 2023, 11(4), 92; https://doi.org/10.3390/technologies11040092 - 11 Jul 2023

Cited by 4 | Viewed by 1758

Abstract

Mechanical jerk systems have applications in several areas, such as oscillators, microcontrollers, circuits, memristors, encryption, etc. This research manuscript reports a new 3-D chaotic jerk system with two unstable balance points. It is shown that the proposed mechanical jerk system exhibits multistability with [...] Read more.

Mechanical jerk systems have applications in several areas, such as oscillators, microcontrollers, circuits, memristors, encryption, etc. This research manuscript reports a new 3-D chaotic jerk system with two unstable balance points. It is shown that the proposed mechanical jerk system exhibits multistability with coexisting chaotic attractors for the same set of system constants but for different initial states. A bifurcation analysis of the proposed mechanical jerk system is presented to highlight the special properties of the system with respect to the variation of system constants. A field-programmable gate array (FPGA) implementation of the proposed mechanical jerk system is given by synthesizing the discrete equations that are obtained by applying one-step numerical methods. The hardware resources are reduced by performing pipeline operations, and, finally, the paper concludes that the experimental results of the proposed mechanical jerk system using FPGA-based design show good agreement with the MATLAB simulations of the same system. Full article

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21 pages, 3298 KiB

Open AccessReview

An Extensive Critique on Smart Grid Technologies: Recent Advancements, Key Challenges, and Future Directions

by Sonam Dorji, Albert Alexander Stonier, Geno Peter, Ramya Kuppusamy and Yuvaraja Teekaraman

Technologies 2023, 11(3), 81; https://doi.org/10.3390/technologies11030081 - 19 Jun 2023

Cited by 11 | Viewed by 6926

Abstract

Given the various aspects of climate change and the growing demand for energy, energy efficiency and environmental protection have become major concerns worldwide. If not taken care of, energy demand will become unmanageable due to technological growth in cities and nations. The solution [...] Read more.

Given the various aspects of climate change and the growing demand for energy, energy efficiency and environmental protection have become major concerns worldwide. If not taken care of, energy demand will become unmanageable due to technological growth in cities and nations. The solution to the global energy crisis could be an advanced two-way digital power flow system that is capable of self-healing, interoperability, and predicting conditions under various uncertainties and is equipped with cyber protections against malicious attacks. The smart grid enables the integration of renewable energy sources such as solar, wind, and energy storage into the grid. Therefore, the perception of the smart grid and the weight given to it by researchers and policymakers are of utmost importance. In this paper, the studies of many researchers on smart grids are examined in detail. Based on the literature review, various principles of smart grids, the development of smart grids, functionality of smart grids, technologies of smart grids with their characteristics, communication of smart grids, problems in the implementation of smart grids, and possible future studies proposed by various researchers have been presented. Full article

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11 pages, 2333 KiB

Open AccessCommunication

Analysis of Redundancy Techniques for Electronics Design—Case Study of Digital Image Processing

by Padmanabhan Balasubramanian

Technologies 2023, 11(3), 80; https://doi.org/10.3390/technologies11030080 - 19 Jun 2023

Cited by 3 | Viewed by 2253

Abstract

Electronic circuits/systems operating in harsh environments such as space are likely to experience faults or failures due to the impact of high-energy radiation. Given this, to overcome any faults or failures, redundancy is usually employed as a hardening-by-design approach. Moreover, low power and [...] Read more.

Electronic circuits/systems operating in harsh environments such as space are likely to experience faults or failures due to the impact of high-energy radiation. Given this, to overcome any faults or failures, redundancy is usually employed as a hardening-by-design approach. Moreover, low power and a small silicon footprint are also important considerations for space electronics since these translate into better energy efficiency, less system weight, and less cost. Therefore, the fault-tolerant design of electronic circuits and systems should go hand in hand with the optimization of design metrics, especially for resource-constrained electronics such as those used in space systems. A single circuit or system (also called a simplex implementation) is not fault-tolerant as it may become a single point of failure and is not used for a space application. As an alternative, a triple modular redundancy (TMR) implementation, which uses three identical copies of a circuit or system and a voter to perform majority voting of the circuits and systems outputs, may be used. However, in comparison with a simplex implementation, a TMR implementation consumes about 200% more area and dissipates 200% more power when circuits or systems are triplicated. To mitigate the area and power overheads of a TMR implementation compared to a simplex implementation, researchers have suggested alternative redundancy approaches such as selective TMR (STMR) insertion, partially approximate TMR (PATMR), fully approximate TMR (FATMR), and majority voting-based reduced precision redundancy (VRPR). Among these, VRPR appears to be promising, especially for inherently error-tolerant applications such as digital image/video/audio processing, which is relevant to space systems. However, the alternative redundancy approaches mentioned are unlikely to be suitable for the implementation of control logic. In this work, we analyze various redundancy approaches and evaluate the performance of TMR and VRPR for a digital image processing application. We provide MATLAB-based image processing results corresponding to TMR and VRPR and physical implementation results of functional units based on TMR and VRPR using a 28-nm CMOS technology. Full article

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24 pages, 1742 KiB

Open AccessArticle

An Efficient Smart Pharmaceutical Packaging Technology Framework to Assess the Quality of Returned Medication through Non-Intrusively Recording Storage Conditions after Dispensation

by James Gerrans, Parastou Donyai, Katherine Finlay and R. Simon Sherratt

Technologies 2023, 11(3), 75; https://doi.org/10.3390/technologies11030075 - 10 Jun 2023

Cited by 1 | Viewed by 3200

Abstract

Medicine waste is a global issue, with economic, environmental, and social consequences that are only predicted to worsen. A structured review of the literature on medicine reuse revealed that there is a lack of technological applications addressing the key concerns raised by pharmaceutical [...] Read more.

Medicine waste is a global issue, with economic, environmental, and social consequences that are only predicted to worsen. A structured review of the literature on medicine reuse revealed that there is a lack of technological applications addressing the key concerns raised by pharmaceutical stakeholders on the safety and feasibility of redispensing medication. A basis and guidelines for solutions aiming at enabling medicine reuse were devised by exploring a conceptual model of a Circular Pharmaceutical Supply Chain (CPSC), discussing concerns raised within the literature and identifying methods to influence the public and pharmaceutical companies. SPaRAS, a novel system to validate the storage conditions and streamline the assessment of returned medicines, is proposed. The Smart Packaging System (SPS) will record the storage conditions of medication while in patient care. The companion Returns Assessment System (RAS) will efficiently communicate with the SPS through RFID, configure the sensors within the SPS to the needs of its assigned medicine and assess the returns against tailored eligibility criteria. The increased safety and efficiency provided by SPaRAS addresses the concerns of large pharmaceutical companies and the public, offering a method to reuse previously owned medication and reduce the effects of unnecessary medicine waste. Full article

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14 pages, 1840 KiB

Open AccessEditor’s ChoiceArticle

Utilization of Artificial Neural Networks for Precise Electrical Load Prediction

by Christos Pavlatos, Evangelos Makris, Georgios Fotis, Vasiliki Vita and Valeri Mladenov

Technologies 2023, 11(3), 70; https://doi.org/10.3390/technologies11030070 - 26 May 2023

Cited by 25 | Viewed by 2699

Abstract

In the energy-planning sector, the precise prediction of electrical load is a critical matter for the functional operation of power systems and the efficient management of markets. Numerous forecasting platforms have been proposed in the literature to tackle this issue. This paper introduces [...] Read more.

In the energy-planning sector, the precise prediction of electrical load is a critical matter for the functional operation of power systems and the efficient management of markets. Numerous forecasting platforms have been proposed in the literature to tackle this issue. This paper introduces an effective framework, coded in Python, that can forecast future electrical load based on hourly or daily load inputs. The framework utilizes a recurrent neural network model, consisting of two simpleRNN layers and a dense layer, and adopts the Adam optimizer and tanh loss function during the training process. Depending on the size of the input dataset, the proposed system can handle both short-term and medium-term load-forecasting categories. The network was extensively tested using multiple datasets, and the results were found to be highly promising. All variations of the network were able to capture the underlying patterns and achieved a small test error in terms of root mean square error and mean absolute error. Notably, the proposed framework outperformed more complex neural networks, with a root mean square error of 0.033, indicating a high degree of accuracy in predicting future load, due to its ability to capture data patterns and trends. Full article

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17 pages, 2067 KiB

Open AccessArticle

Geographical Dependence of Open Hardware Optimization: Case Study of Solar Photovoltaic Racking

by Shafquat Rana, Nicholas Vandewetering, Jadyn Powell, Jonathan Álvarez Ariza and Joshua M. Pearce

Technologies 2023, 11(2), 62; https://doi.org/10.3390/technologies11020062 - 21 Apr 2023

Cited by 4 | Viewed by 3323

Abstract

Open-source technological development is well-known for rapid innovation and providing opportunities to reduce costs and thus increase accessibility for a wide range of products. This is done through distributed manufacturing, in which products are produced close to end users. There is anecdotal evidence [...] Read more.

Open-source technological development is well-known for rapid innovation and providing opportunities to reduce costs and thus increase accessibility for a wide range of products. This is done through distributed manufacturing, in which products are produced close to end users. There is anecdotal evidence that these opportunities are heavily geographically dependent, with some locations unable to acquire components to build open hardware at accessible prices because of trade restrictions, tariffs, taxes, or market availability. Supply chain disruptions during the COVID-19 pandemic exacerbated this and forced designers to pivot towards a la carte-style design frameworks for critical system components. To further develop this phenomenon, a case study of free and open-source solar photovoltaic (PV) racking systems is provided. Two similar open-source designs made from different materials are compared in terms of capital costs for their detailed bill of materials throughout ten locations in North, Central and South America. The differences in economic optimization showed that the costs of wood-based racks were superior in North America and in some South American countries, while metal was less costly in Central and South America. The results make it clear that open hardware designs would be best to allow for local optimization based on material availability in all designs. Full article

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14 pages, 2433 KiB

Open AccessEditor’s ChoiceArticle

Photovoltaic Inverter Reliability Study through SiC Switches Redundant Structures

by Ignacio Villanueva, Nimrod Vázquez, Joaquín Vaquero, Claudia Hernández, Héctor López-Tapia and Rene Osorio-Sánchez

Technologies 2023, 11(2), 59; https://doi.org/10.3390/technologies11020059 - 14 Apr 2023

Cited by 4 | Viewed by 2171

Abstract

Reliability is a very important issue in power electronics; however, sometimes it is not considered, studied, or analyzed. At present, renewables have become more popular, and more complex setups are required to drive this type of system. In the specific case of inverters [...] Read more.

Reliability is a very important issue in power electronics; however, sometimes it is not considered, studied, or analyzed. At present, renewables have become more popular, and more complex setups are required to drive this type of system. In the specific case of inverters in photovoltaic systems, the user’s safety, quality, reliability, and the system’s useful life must be guaranteed. In this paper, the reliability of a full bridge inverter is predicted by calculating metrics such as failure rates and Mean Time Between Failures. Reliability is obtained using different types of structures for SiC MOSFETs: serial systems, active parallel redundant systems, and passive parallel redundant systems. Finally, the reliability study shows that a system with a passive parallel redundant structure is more reliable and has a higher useful life compared to the other structures. Full article

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