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Keywords = allowable maximum trading power

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24 pages, 6185 KiB  
Article
Decentralized Energy Management for Efficient Electric Vehicle Charging in DC Microgrids: A Piece-Wise Droop Control Approach
by Mallareddy Mounica, Bhooshan Avinash Rajpathak, Mohan Lal Kolhe, K. Raghavendra Naik, Janardhan Rao Moparthi, Sravan Kumar Kotha and Devasuth Govind
Processes 2025, 13(6), 1748; https://doi.org/10.3390/pr13061748 - 2 Jun 2025
Viewed by 808
Abstract
This paper addresses the challenges of efficient electric vehicle (EV) charging integration in Direct Current (DC) microgrids (MGs), particularly the impact of intermittent EV loads on power sharing and voltage regulation. Traditional droop control methods suffer from inherent trade-offs between performance indices of [...] Read more.
This paper addresses the challenges of efficient electric vehicle (EV) charging integration in Direct Current (DC) microgrids (MGs), particularly the impact of intermittent EV loads on power sharing and voltage regulation. Traditional droop control methods suffer from inherent trade-offs between performance indices of parallel distributed energy resources (DERs), which in turn results in improper source utilization. We propose a novel decentralized piece-wise droop control (PDC) approach with voltage compensation for EV charging to overcome this limitation and to minimize the unequal cable resistance effect on power sharing. This strategy dynamically optimises the droop characteristics based on EV charging load profiles, partitioning the droop curve to optimize power sharing accuracy and voltage stability considering the constraints of maximum allowable voltage deviation and loading. Simulation and experimental results demonstrate significant improvements in power sharing, enhanced DER utilization, and voltage deviations consistently within 2.5% when compared with traditional strategies. PDC offers a robust solution for enabling efficient and reliable EV charging in MGs, as it is not sensitive for EV load prediction errors and measurement noise. Full article
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20 pages, 6471 KiB  
Article
A Compact Low-Power Chopper Low Noise Amplifier for High Density Neural Front-Ends
by Alessandro Fava, Francesco Centurelli, Pietro Monsurrò and Giuseppe Scotti
Sensors 2025, 25(4), 1157; https://doi.org/10.3390/s25041157 - 13 Feb 2025
Cited by 2 | Viewed by 1165
Abstract
This paper presents a low-power and area-efficient chopper-stabilized low noise amplifier (CS-LNA) for in-pixel neural recording systems. The proposed CS-LNA can be used in a multi-channel architecture, in which the chopper mixers of the LNA are exploited to provide the time division multiplexing [...] Read more.
This paper presents a low-power and area-efficient chopper-stabilized low noise amplifier (CS-LNA) for in-pixel neural recording systems. The proposed CS-LNA can be used in a multi-channel architecture, in which the chopper mixers of the LNA are exploited to provide the time division multiplexing (TDM) of several channels, while reducing the flicker noise and rejecting the Electrode DC Offset (EDO). A detailed noise analysis including the effect of the chopper stabilization on flicker noise, and a design flow to optimize the trade-off between input-referred noise and silicon area are presented, and utilized to design the LNA. The adopted approach to reject the EDO allows to tolerate an input offset of ±50 mV, without appreciably affecting the CS-LNA performance, and does not require an additional DC Servo Loop (DSL). The proposed CS-LNA has been fabricated in a 0.13 μm CMOS process with an area of 0.0268 mm2, consuming about 2 μA from a 0.8 V supply voltage. It achieves an integral noise of 4.19 μVrms (2.58 μVrms) from 1 to 7.5 kHz (from 300 to 7.5 kHz) and results in a noise efficiency factor (NEF) of 2.63 (1.62). Besides achieving a maximum gain of 38.67 dB with a tuning range of about 12 dB, the neural amplifier exhibits a CMRR of 67 dB. A comparison with the recent literature dealing with in-pixel amplifiers shows state-of-the-art performance. Full article
(This article belongs to the Section Biomedical Sensors)
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23 pages, 4230 KiB  
Article
Optimizing Peer-to-Peer Energy Transactions: Determining the Allowable Maximum Trading Power for Participants
by Pikkanate Angaphiwatchawal and Surachai Chaitusaney
Energies 2024, 17(6), 1423; https://doi.org/10.3390/en17061423 - 15 Mar 2024
Cited by 1 | Viewed by 1719
Abstract
This paper presents a comprehensive study on the impacts of peer-to-peer (P2P) energy markets on distribution systems, specifically focusing on voltage, power loss, and congestion. While P2P energy markets create opportunities for direct trading between prosumers and consumers, ensuring compliance with distribution system [...] Read more.
This paper presents a comprehensive study on the impacts of peer-to-peer (P2P) energy markets on distribution systems, specifically focusing on voltage, power loss, and congestion. While P2P energy markets create opportunities for direct trading between prosumers and consumers, ensuring compliance with distribution system constraints remains a challenge. This paper proposes an iterative method and graphical interpretation in order to assess complex interactions, addressing the persistent issue of network constraints. Additionally, this paper proposes a method to determine distribution locational marginal prices (DLMPs) for real-time traditional energy markets. This ensures effective coordination among sellers, buyers, and the distribution system operator. The proposed method aims to prevent negative impacts on distribution system operation via the determination of the allowable maximum trading power (MTP), ensuring empirical validity and practical implementation via operating conditions and forecast errors, thus distinguishing it from prior studies. This paper also establishes a model for P2P energy market interactions, utilizing linear estimations for efficient DLMP updates. The contributions of this paper enhance the understanding and operation of P2P energy markets, and is supported by simulation results validating the proposed method. Full article
(This article belongs to the Section C: Energy Economics and Policy)
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14 pages, 2749 KiB  
Article
A Novel Scheduling Algorithm for Improved Performance of Multi-Objective Safety-Critical WSN Using Spatial Self-Organizing Feature Map
by Issam Al-Nader, Aboubaker Lasebae and Rand Raheem
Electronics 2024, 13(1), 19; https://doi.org/10.3390/electronics13010019 - 19 Dec 2023
Cited by 2 | Viewed by 1205
Abstract
Technological advances in the internet of things (IoT) allowed a low-cost, yet small sensor device to operate with limited power in a dynamic harsh environment where human intervention is impossible. The wireless sensor network (WSN) is an example of the IoT in which [...] Read more.
Technological advances in the internet of things (IoT) allowed a low-cost, yet small sensor device to operate with limited power in a dynamic harsh environment where human intervention is impossible. The wireless sensor network (WSN) is an example of the IoT in which physical devices’ software and sensors can interconnect to provide application services. It is important that such applications be dependable to meet the required quality of service (QoS) and function as expected. Consequently, the multi-objective optimization (MOO) problem in WSNs aims to address the trade-off among coverage, connectivity, and network lifetime requirements. Node scheduling is one approach of many used to optimize energy in WSNs. The contribution of this work is the proposal of a self-organizing feature map (SOFM) to enhance the node scheduling in WSNs. The proposed SOFM node-scheduling algorithm aims to spatially explore the state space domain and obtain an optimal solution. In our experiment, the proposed SOFM node-scheduling algorithm is evaluated against a comparable algorithm, namely the BAT node-scheduling algorithm, via MATLAB simulator. The results showed that the SOFM node-scheduling algorithm outperformed the latter by 27% and 28% for the maximum and minimum coverage, respectively, with similar performance of 99% of connectivity and network lifetime. Full article
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24 pages, 15369 KiB  
Article
Design of Dual-Notch-Filter-Based Controllers for Enhancing the Dynamic Response of Universal Single-Phase Grid-Connected Power Converters
by Sahar Borafker, Pavel Strajnikov and Alon Kuperman
Appl. Sci. 2023, 13(18), 10144; https://doi.org/10.3390/app131810144 - 8 Sep 2023
Cited by 2 | Viewed by 1582
Abstract
Trade-off between transient response and grid-side current quality is a well-known issue of single-phase mains-connected power converters. A dual-loop control structure (usually based on PI or type-II controllers) is typically employed in such systems to regulate the DC link voltage to a constant [...] Read more.
Trade-off between transient response and grid-side current quality is a well-known issue of single-phase mains-connected power converters. A dual-loop control structure (usually based on PI or type-II controllers) is typically employed in such systems to regulate the DC link voltage to a constant reference (in order to maintain power balance) while forcing the grid-side current to have a specific shape (in order to comply with power quality requirements). Introducing notch term/s (tuned to certain multiple/s of the mains base frequency) into one of the loops allows either for the improvement of the dynamic performance without worsening the total harmonic distortion of grid-side current or for the enhancement of the current quality without impairing the dynamic response. Since the maximum tolerable value of total harmonic distortion is typically imposed by a certain power quality standard, it is desirable to enhance the transient response of the power converter system as much as possible while keeping the total harmonic distortion at the maximum allowed value. However, universal off-grid operating power conversion systems must support both 50 Hz and 60 Hz mains; consequently, tuning the notch term/s to 50 Hz multiple/s would not be sufficient for a 60 Hz mains operation and vice-versa. Consequently, this work examines the possibility of introducing a dual-notch term into the control loop in order to cover both above-mentioned base frequencies. It is demonstrated that under typical base frequency uncertainty values, the performances of dual-notch terms are nearly decoupled so that the term tuned to a 50 Hz frequency (and optionally to its multiples) has nearly no influence at a 60 Hz mains operation and vice-versa. Consequently, the methodology allows for the improvement of the dynamics of universal grid-connected power converters without total harmonic distortion (THD) deterioration. A stability analysis of the proposed control structure is carried out and quantitative design guidelines, allowing for the attainment of an optimized dynamic response for a given maximum tolerable total harmonic distortion, minimum allowed phase margin and a certain base frequency uncertainty, are established. It is shown that a DC link voltage loop bandwidth of 52 Hz may be attained while keeping the grid-side current THD below 5%. Simulations and experimental results support well the proposed design methodology. Full article
(This article belongs to the Special Issue Innovative Technologies in Power Electronics Converters)
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43 pages, 2141 KiB  
Article
Swarm Intelligence-Based Multi-Objective Optimization Applied to Industrial Cooling Towers for Energy Efficiency
by Nadia Nedjah, Luiza de Macedo Mourelle and Marcelo Silveira Dantas Lizarazu
Sustainability 2022, 14(19), 11881; https://doi.org/10.3390/su141911881 - 21 Sep 2022
Cited by 4 | Viewed by 2754
Abstract
Cooling towers constitute a fundamental part of refrigeration systems in power plants and large commercial buildings. Their main function is to treat the heat emitted by other equipment to cool down the temperature of the environment and/or processes. In the considered refrigeration system, [...] Read more.
Cooling towers constitute a fundamental part of refrigeration systems in power plants and large commercial buildings. Their main function is to treat the heat emitted by other equipment to cool down the temperature of the environment and/or processes. In the considered refrigeration system, cooling towers are coupled with compression chillers. The serious world-wide concerns with regard to environmental wear and water scarcity are now common knowledge. One way to mitigate their impact is to reach a state of maximum energy efficiency in industrial processes. For this purpose, this work proposes the application of multi-objective optimization algorithms to find out the optimal operational setpoints of the studied refrigeration system. Here, we exploit swarm intelligence strategies to offer the best trade-offs. This consists of finding solutions that maximize the cooling tower’s effectiveness and yet minimize the global power requirement of the system. Additionally, the solutions must also respect operational constraints for the safe operation of the equipment. In this investigation, we apply two algorithms, multi-objective particle swarm optimization and multi-objective TRIBES, using two different models. The achieved results are compared considering two different scenarios and two different models of the refrigeration system. This allows for the selection of the best algorithm and best equipment model for energy efficiency of the refrigeration system. For the studied configuration, we achieve an energy efficiency factor of 1.78, allowing power savings of 9.48% with tower effectiveness reduction of only 5.32%. Full article
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27 pages, 1730 KiB  
Article
Evolutionary Multi-Objective Optimization Applied to Industrial Refrigeration Systems for Energy Efficiency
by Nadia Nedjah, Luiza de Macedo Mourelle and Marcelo Silveira Dantas Lizarazu
Energies 2022, 15(15), 5575; https://doi.org/10.3390/en15155575 - 1 Aug 2022
Cited by 6 | Viewed by 2639
Abstract
Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In [...] Read more.
Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In this work, the refrigeration is composed of cooling towers dotted with ventilators and compression chillers. The growing environmental concerns and the current scenario of scarce water and energy resources have lead to the adoption of actions to obtain the maximum energy efficiency in such refrigeration equipment. This backs up the application of computational intelligence to optimize the operating conditions of the involved equipment and cooling processes. In this context, we utilize multi-objective optimization algorithms to determine the optimal operational setpoints of the cooling system regarding the cooling towers, its fans and the included chillers. We use evolutionary multi-objective optimization to provide the best trade-offs between two conflicting objectives: maximization of the effectiveness of the cooling towers and minimization of the overall power requirement of the refrigeration system. The optimization process respects the constraints to guarantee the correct and safe operation of the equipment when the evolved solution is implemented. In this work, we apply three evolutionary multi-objective algorithms: Non-dominated Sorting Genetic Algorithm (NSGA-II), Micro-Genetic Algorithm (Micro-GA) and Strength Pareto Evolutionary Algorithm (SPEA2). The results obtained are analyzed under different scenarios and models of the cooling system’s equipment, allowing for the selection of the best algorithm and best equipment’s model to achieve energy efficiency of the studied refrigeration system. Full article
(This article belongs to the Special Issue Intelligent Forecasting and Optimization in Electrical Power Systems)
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18 pages, 33899 KiB  
Article
Dracon: An Open-Hardware Based Platform for Single-Chip Low-Cost Reconfigurable IoT Devices
by Luis Parrilla, Antonio García, Encarnación Castillo, José Antonio Álvarez-Bermejo, Juan Antonio López-Villanueva and Uwe Meyer-Baese
Electronics 2022, 11(13), 2080; https://doi.org/10.3390/electronics11132080 - 2 Jul 2022
Cited by 4 | Viewed by 3020
Abstract
The development of devices for the Internet of Things (IoT) requires the rapid prototyping of different hardware configurations. In this paper, a modular hardware platform allowing to prototype, test and even implement IoT appliances on low-cost reconfigurable devices is presented. The proposed platform, [...] Read more.
The development of devices for the Internet of Things (IoT) requires the rapid prototyping of different hardware configurations. In this paper, a modular hardware platform allowing to prototype, test and even implement IoT appliances on low-cost reconfigurable devices is presented. The proposed platform, named Dracon, includes a Z80-clone microprocessor, up to 64 KB of RAM, and 256 inputs/outputs (I/Os). These I/Os can be used to connect additional co-processors within the same FPGA, external co-processors, communications modules, sensors and actuators. Dracon also includes as default peripherals a UART for programming and accessing the microprocessor, a Real Time Clock, and an Interrupt Timer. The use of an 8-bit microprocessor allows the use of the internal memory of the reconfigurable device as program memory, thereby, enabling the implementation of a complete IoT device within a single low-cost chip. Indeed, results using a Spartan 7 FPGA show that it is possible to implement Dracon with only 1515 6-input LUTs while operating at a maximum frequency of 80 MHz, which results in a better trade-off in terms of area and performance than other less powerful and less versatile alternatives in the literature. Moreover, the presented platform allows the development of embedded software applications independently of the selected FPGA device, enabling rapid prototyping and implementations on devices from different manufacturers. Full article
(This article belongs to the Special Issue Recent FPGA Architectures and Applications)
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29 pages, 970 KiB  
Article
Optimisation of Buyer and Seller Preferences for Peer-to-Peer Energy Trading in a Microgrid
by Shama Naz Islam and Aiswarya Sivadas
Energies 2022, 15(12), 4212; https://doi.org/10.3390/en15124212 - 8 Jun 2022
Cited by 6 | Viewed by 2552
Abstract
In this paper, an optimisation approach to prioritise buyers and sellers in a peer-to-peer (P2P) energy trading market based on distances from the aggregator has been developed. The proposed approach assigns higher preferences to buyers/sellers with a smaller distance, as this will allow [...] Read more.
In this paper, an optimisation approach to prioritise buyers and sellers in a peer-to-peer (P2P) energy trading market based on distances from the aggregator has been developed. The proposed approach assigns higher preferences to buyers/sellers with a smaller distance, as this will allow lower losses in the power transmission. Under this approach, the sellers and buyers operate in a decentralised manner to optimise the preference coefficients along with the energy sold/purchased to achieve certain profits/savings. The proposed approach is implemented using a real-life dataset, and the impacts of different parameters, such as seasonal variations in renewable generation, distances and profit thresholds for sellers, have been investigated. The results show that the proposed approach allows buyers and sellers to purchase/sell more energy from the P2P trading market (2.4 times increase when maximum energy sold is considered) in comparison to the case when all participants are equally preferred. It has been observed that, with increasing distances, sellers are assigned a smaller preference coefficient, which results in sellers being willing to sell a higher amount of energy so that they can achieve the same profit threshold. Full article
(This article belongs to the Section A1: Smart Grids and Microgrids)
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13 pages, 579 KiB  
Article
Sentinel Lymph Node Metastasis on Clinically Negative Patients: Preliminary Results of a Machine Learning Model Based on Histopathological Features
by Annarita Fanizzi, Vito Lorusso, Albino Biafora, Samantha Bove, Maria Colomba Comes, Cristian Cristofaro, Maria Digennaro, Vittorio Didonna, Daniele La Forgia, Annalisa Nardone, Domenico Pomarico, Pasquale Tamborra, Alfredo Zito, Angelo Virgilio Paradiso and Raffaella Massafra
Appl. Sci. 2021, 11(21), 10372; https://doi.org/10.3390/app112110372 - 4 Nov 2021
Cited by 7 | Viewed by 2639
Abstract
The reported incidence of node metastasis at sentinel lymph node biopsy is generally low, so that the majority of women underwent unnecessary invasive axilla surgery. Although the sentinel lymph node biopsy is time consuming and expensive, it is still the intra-operative exam with [...] Read more.
The reported incidence of node metastasis at sentinel lymph node biopsy is generally low, so that the majority of women underwent unnecessary invasive axilla surgery. Although the sentinel lymph node biopsy is time consuming and expensive, it is still the intra-operative exam with the highest performance, but sometimes surgery is achieved without a clear diagnosis and also with possible serious complications. In this work, we developed a machine learning model to predict the sentinel lymph nodes positivity in clinically negative patients. Breast cancer clinical and immunohistochemical features of 907 patients characterized by a clinically negative lymph node status were collected. We trained different machine learning algorithms on the retrospective collected data and selected an optimal subset of features through a sequential forward procedure. We found comparable performances for different classification algorithms: on a hold-out training set, the logistics regression classifier with seven features, i.e., tumor diameter, age, histologic type, grading, multiplicity, in situ component and Her2-neu status reached an AUC value of 71.5% and showed a better trade-off between sensitivity and specificity (69.4 and 66.9%, respectively) compared to other two classifiers. On the hold-out test set, the performance dropped by five percentage points in terms of accuracy. Overall, the histological characteristics alone did not allow us to develop a support tool suitable for actual clinical application, but it showed the maximum informative power contained in the same for the resolution of the clinical problem. The proposed study represents a starting point for future development of predictive models to obtain the probability for lymph node metastases by using histopathological features combined with other features of a different nature. Full article
(This article belongs to the Special Issue Clinical Studies on Breast Lymph Node Involvement)
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19 pages, 4791 KiB  
Article
Double-Layer Energy Efficient Synchronous-Asynchronous Circuit-Switched NoC
by Sandy A. Wasif, Salma Hesham, Diana Goehringer, Klaus Hofmann and Mohamed A. Abd El Ghany
Electronics 2021, 10(15), 1821; https://doi.org/10.3390/electronics10151821 - 29 Jul 2021
Cited by 3 | Viewed by 2229
Abstract
A network-on-chip (NoC) offers high performance, flexibility and scalability in communication infrastructure within multi-core platforms. However, NoCs contribute significantly to the overall system’s power consumption. The double-layer energy efficient synchronous-asynchronous circuit-switched NoC (CS-NoC) is proposed to enhance the power utilization. To reduce the [...] Read more.
A network-on-chip (NoC) offers high performance, flexibility and scalability in communication infrastructure within multi-core platforms. However, NoCs contribute significantly to the overall system’s power consumption. The double-layer energy efficient synchronous-asynchronous circuit-switched NoC (CS-NoC) is proposed to enhance the power utilization. To reduce the dynamic power consumption, single-rail asynchronous protocols are utilized. The two-phase and four-phase encoding algorithms are analyzed to determine the most efficient technique. For the data layer, the two asynchronous protocols reduced the power consumption by 80%, with an increase in latency when compared with the fully synchronous protocol. However, the two-phase single-rail protocol had better performance compared with the four-phase protocol by 38%, with the same power consumption and a slight increase in area of 5%. Based on this conducted analysis, the asynchronous two-phase layer had significant power reduction yet operated at a moderate frequency. Therefore, the proposed NoC is divided into two data transfer layers with a single control layer. The data transfer layers are designed using synchronous and asynchronous protocols. The synchronous layer is designated to high-frequency loads, and the asynchronous layer is confined to low-frequency loads. The switching between the layers creates a trade-off between the maximum allowed frequency and the power consumption. The proposed NoC reduces the overall power consumption by 23% when compared with recent previous work. The NoC maintains the same system performance with an 8% area increase over the fully synchronous double-layer in the literature. Full article
(This article belongs to the Section Circuit and Signal Processing)
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24 pages, 2045 KiB  
Article
Optimal Scheduling of Dynamic Pricing Based V2G and G2V Operation in Microgrid Using Improved Elephant Herding Optimization
by Vinay Kumar Jadoun, Nipun Sharma, Piyush Jha, Jayalakshmi N. S., Hasmat Malik and Fausto Pedro Garcia Márquez
Sustainability 2021, 13(14), 7551; https://doi.org/10.3390/su13147551 - 6 Jul 2021
Cited by 30 | Viewed by 3936
Abstract
The unpredictable nature of the loads and non-linearity of the components of microgrid systems make optimal scheduling more complex. In this paper, a deterministic optimal load-scheduling problem is developed for microgrids operating in both islanding and grid-connected mode under different energy scenarios. Various [...] Read more.
The unpredictable nature of the loads and non-linearity of the components of microgrid systems make optimal scheduling more complex. In this paper, a deterministic optimal load-scheduling problem is developed for microgrids operating in both islanding and grid-connected mode under different energy scenarios. Various cases are considered in this research, based on the interaction and dynamic behavior of the microgrid, considering electric vehicles (EVs) in the scenario. The aim of this research is to minimize the overall cost of microgrid operations. The concept of dynamic pricing has also been introduced in order to optimize the energy cost for the consumers. For ensuring the stability of the microgrids, a load variance index has been considered, and the fuzzy-based approach has been used for cost and load variance minimization to reduce the operation cost without compromising the stability of the microgrid. The grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations of EVs are integrated into the microgrid, which would help in valley filling and peak shaving of the loads during the off-peak and peak hours, respectively. In order to solve the proposed complex combinatorial optimization problem, elephant herding optimization (EHO) is modified and implemented. The performance of the proposed improved EHO (IEHO) is first tested on the latest CEC test functions. The results obtained by IEHO after 100 different trials are compared with the latest published methods and are found to be better based on the average value and the standard deviation for different CEC test functions. In addition, the simulation results obtained by particle swarm optimization (PSO), EHO, and proposed IEHO on a microgrid test system for different scenarios with all cases reveal that the proposed model with a mix of energy resources in the dynamic load dispatch environment bring the maximum benefits of microgrid systems. Furthermore, the results obtained from the simulation verifies that if free trade of power is allowed between the microgrids and the main grid, the process of power generation can be more economical, and further introduction of dynamic pricing into the scenario proves to be even cheaper. The implementation of the G2V and V2G operations of EVs operations in the proposed scenario not only helped in cost minimization but also helped in stabilizing the grid. Full article
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13 pages, 1683 KiB  
Article
A Resource Constrained Neural Network for the Design of Embedded Human Posture Recognition Systems
by Gian Domenico Licciardo, Alessandro Russo, Alessandro Naddeo, Nicola Cappetti, Luigi Di Benedetto, Alfredo Rubino and Rosalba Liguori
Appl. Sci. 2021, 11(11), 4752; https://doi.org/10.3390/app11114752 - 21 May 2021
Cited by 18 | Viewed by 2866
Abstract
A custom HW design of a Fully Convolutional Neural Network (FCN) is presented in this paper to implement an embeddable Human Posture Recognition (HPR) system capable of very high accuracy both for laying and sitting posture recognition. The FCN exploits a new base-2 [...] Read more.
A custom HW design of a Fully Convolutional Neural Network (FCN) is presented in this paper to implement an embeddable Human Posture Recognition (HPR) system capable of very high accuracy both for laying and sitting posture recognition. The FCN exploits a new base-2 quantization scheme for weight and binarized activations to meet the optimal trade-off between low power dissipation, a very reduced set of instantiated physical resources and state-of-the-art accuracy to classify human postures. By using a limited number of pressure sensors only, the optimized HW implementation allows keeping the computation close to the data sources according to the edge computing paradigm and enables the design of embedded HP systems. The FCN can be simply reconfigured to be used for laying and sitting posture recognition. Tested on a public dataset for in-bed posture classification, the proposed FCN obtains a mean accuracy value of 96.77% to recognize 17 different postures, while a small custom dataset has been used for training and testing for sitting posture recognition, where the FCN achieves 98.88% accuracy to recognize eight positions. The FCN has been prototyped on a Xilinx Artix 7 FPGA where it exhibits a dynamic power dissipation lower than 11 mW and 7 mW for laying and sitting posture recognition, respectively, and a maximum operation frequency of 47.64 MHz and 26.6 MHz, corresponding to an Output Data Rate (ODR) of the sensors of 16.50 kHz and 9.13 kHz, respectively. Furthermore, synthesis results with a CMOS 130 nm technology have been reported, to give an estimation about the possibility of an in-sensor circuital implementation. Full article
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21 pages, 1093 KiB  
Article
Transmission Strategy for Simultaneous Wireless Information and Power Transfer with a Non-Linear Rectifier Model
by Ning Pan, Mohammad Rajabi, Steven Claessens, Dominique Schreurs and Sofie Pollin
Electronics 2020, 9(7), 1082; https://doi.org/10.3390/electronics9071082 - 1 Jul 2020
Cited by 8 | Viewed by 2965
Abstract
Most studies determining data rate or power conversion efficiency (PCE) of simultaneous wireless information and power transfer (SWIPT) focus on ideal models for the non-linear energy harvester, or focus on simplified waveforms that carry no information. In this paper, we study SWIPT using [...] Read more.
Most studies determining data rate or power conversion efficiency (PCE) of simultaneous wireless information and power transfer (SWIPT) focus on ideal models for the non-linear energy harvester, or focus on simplified waveforms that carry no information. In this paper, we study SWIPT using realistic waveforms and a measurement-based energy harvesting model. For a special class of multisine waveforms carrying only information in the phase, we analyze PCE as a function of waveform design, including the impact of pre-equalization to mitigate wireless channel distortion. A balanced pre-equalizer that trades off between the peak-to-average power ratio (PAPR) and signal to noise ratio, maximizing the total PCE is proposed. The impact on the information rate of the analyzed waveforms is also presented. The results show that balanced pre-equalizers can improve the total PCE more than three times within 5% rate loss compared to the pre-equalizer that solely maximizes the signal PAPR or the capacity using the same transmit power. We also show that the maximum normalized PCE is increased by a factor of two by only allowing phase modulation to ensure the PAPR of one symbol, compared to traditional modulation schemes that carry information in both phase and amplitude to maximize spectral efficiency. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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16 pages, 1374 KiB  
Article
Effect of Link Misalignment in the Optical-Internet of Underwater Things
by Ruhul Amin Khalil, Mohammad Inayatullah Babar, Nasir Saeed, Tariqullah Jan and Ho-Shin Cho
Electronics 2020, 9(4), 646; https://doi.org/10.3390/electronics9040646 - 15 Apr 2020
Cited by 25 | Viewed by 5236
Abstract
Underwater wireless optical communication (UWOC) enables high-speed links in water for the optical Internet of Underwater Things (O-IoUT) networks. O-IoUT provides various marine applications, including ocean exploration, environmental monitoring, and underwater navigation. O-IoUT typically utilizes light-emitting diodes (LEDs) and different laser diodes (LDs) [...] Read more.
Underwater wireless optical communication (UWOC) enables high-speed links in water for the optical Internet of Underwater Things (O-IoUT) networks. O-IoUT provides various marine applications, including ocean exploration, environmental monitoring, and underwater navigation. O-IoUT typically utilizes light-emitting diodes (LEDs) and different laser diodes (LDs) such as green/blue lasers to achieve efficient data communication in the underwater environment. The high-speed optical communication is limited up to a few tens of meters due to underwater channel impairments and misalignment between the transmitter (Tx) and the receiver (Rx). UWOC provides high-speed communications only in the line of sight conditions, and a small misalignment between the Tx and the Rx can degrade the system performance. In an attempt to understand and minimize this misalignment issue, we investigate how received power in a UWOC system depends on the transmitted beam’s divergence angle. Simulation results are provided to show the effectiveness of the study by comparing the plane, Gaussian, and spherical beams. Monte Carlo simulations are utilized to determine the maximum allowable lateral offset between Tx and Rx for a given Tx divergence angle. The results provide an overview and design-based trade-off between different parameters such as lateral offset, the power received, and bandwidth of the channel. The proposed method improves not only the maximum allowed link-span but also the bandwidth of the channel for a given transmission distance. Full article
(This article belongs to the Special Issue Underwater Communication and Networking Systems)
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