Energy Harvesting and Energy Storage Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (31 January 2022) | Viewed by 41479

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Special Issue Editors

Department of Electrical and Electronic Engineering, Ariel University, Ariel 40700, Israel
Interests: piezoelectricity; multiferroicity; energy harvesting; energy storage; photovoltaic systems; dielectrics; crystallography
Special Issues, Collections and Topics in MDPI journals
Department of Electrical and Electronics Engineering, Ariel University, Ariel 40700, Israel
Interests: PV electrical generation; power electronics; electrical machines; vanadium redox batteries
Special Issues, Collections and Topics in MDPI journals
Department of Electronics and Computer Technology, University of Granada, 18071 Granada, Spain
Interests: nanotechnology; sensors; electrical characterization; nanoelectronics; laser-induced nanomaterials; energy harvesting; energy conversion; flexible electronics; memristive devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the principles set for finding the balance between these pillars is to limit the use of non-renewable energy sources. A promising method to resolve this challenge is to harvest energy from the ambient environment and convert it into electrical power. In recent days, the development of new energy generation technologies, such as solar, wind, and thermal energy, is high on demand to replace fossil fuel energy resources with cleaner renewable sources. Energy harvesting systems have emerged as a prominent research area and continue to grow at a rapid pace.

Modern technologies such as portable electronic devices, electrical transportation, communication systems, and smart medical equipment need efficient energy storage systems. Electrical energy storage devices are also used for smart grid control, grid stability, and peak-power saving, as well as for frequency and voltage regulation. Electricity generated from renewable sources (e.g., solar power, wind energy) can hardly deliver an immediate response to demand because of fluctuating power supply. Hence, it has been suggested to preserve the harvested electrical energy for future requirements. The present status of electrical energy storage technologies is quite far from the needed demand.

It is our pleasure to invite researchers and scientists to submit your research work to this Special Issue. The objective of this Special Issue is to present studies in the field of energy harvesting and energy storage systems. We look forward to receiving your outstanding theoretical and experimental research findings.

Dr. Shailendra Rajput
Dr. Moshe Averbukh
Prof. Noel Rodriguez
Guest Editors

Manuscript Submission Information

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Keywords

  • Energy harvesting
  • Photovoltaic system
  • MPPT
  • Electrostatic Energy Harvester
  • Electromagnetic Energy Harvester
  • Mechanic to Electrical Energy Conversion
  • Energy Storage
  • Ultracapacitor
  • Capacitive Reactive Power
  • Smart Grid

Published Papers (14 papers)

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Editorial

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4 pages, 170 KiB  
Editorial
Energy Harvesting and Energy Storage Systems
Electronics 2022, 11(7), 984; https://doi.org/10.3390/electronics11070984 - 23 Mar 2022
Cited by 8 | Viewed by 1583
Abstract
Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity [...] Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)

Research

Jump to: Editorial, Review

27 pages, 11649 KiB  
Article
Renewable Energy Micro-Grid Interfacing: Economic and Environmental Issues
Electronics 2022, 11(5), 815; https://doi.org/10.3390/electronics11050815 - 05 Mar 2022
Cited by 18 | Viewed by 1963
Abstract
This paper presents a study on the technical, economic, and environmental aspects of renewable energy resources-based distributed generation units (DGs). These units are connected to the medium-voltage network to create a new structure called a microgrid (MG). Renewable energies, especially wind and solar, [...] Read more.
This paper presents a study on the technical, economic, and environmental aspects of renewable energy resources-based distributed generation units (DGs). These units are connected to the medium-voltage network to create a new structure called a microgrid (MG). Renewable energies, especially wind and solar, are the most important generation units among DGs. The stochastic behavior of renewable resources increases the need to find the optimum operation of the MG. The optimal operation of a typical MG aims to simultaneously minimize the operational costs and the accompanied emission pollutants over a daily scheduling horizon. Several renewable DGs are investigated in the MG, consisting of biomass generators (BGs), wind turbines (WTs), and photovoltaics (PV). For the proposed operating strategy of the MG, a recent equilibrium optimization (EO) technique is developed and is inspired by the mass balance models for a control volume that are used to estimate their dynamic and equilibrium states. The uncertainties of wind speed and solar irradiation are considered via the Weibull and Beta-probability density functions (PDF) with different states of mean and standard deviation for each hour, respectively. Based on the developed EO, the hourly output powers of the PV, WT, and BGs are optimized, as are the associated power factors of the BGs. The proposed MG operating strategy based on the developed EO is tested on the IEEE 33-bus system and the practical large-scale 141-bus system of AES-Venezuela in the metropolitan area of Caracas. The simulation results demonstrate the significant benefits of the optimal operation of a typical MG using the developed EO by minimizing the operational costs and emissions while preserving the penetration level of the DGs by 60%. Additionally, the voltage profile of the MG operation for each hour is highly enhanced where the minimum voltage at each hour is corrected within the permissible limit of [0.95–1.05] Pu. Moreover, the active power losses per hour are greatly reduced. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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13 pages, 1609 KiB  
Article
Parameter Extraction of Solar Module Using the Sooty Tern Optimization Algorithm
Electronics 2022, 11(4), 564; https://doi.org/10.3390/electronics11040564 - 13 Feb 2022
Cited by 24 | Viewed by 1900
Abstract
Photovoltaic module parameter estimation is a critical step in observing, analyzing, and optimizing the efficiency of solar power systems. To find the best value for unknown parameters, an efficient optimization strategy is required. This paper presents the implementation of the sooty tern optimization [...] Read more.
Photovoltaic module parameter estimation is a critical step in observing, analyzing, and optimizing the efficiency of solar power systems. To find the best value for unknown parameters, an efficient optimization strategy is required. This paper presents the implementation of the sooty tern optimization (STO) algorithm for parameter assessment of a solar cell/module. The simulation findings were compared to four pre-existing optimization algorithms: sine cosine (SCA) algorithm, gravitational search algorithm (GSA), hybrid particle swarm optimization and gravitational search algorithm (PSOGSA), and whale optimization (WOA). The convergence rate and root mean square error evaluations show that the STO method surpasses the other studied optimization techniques. Additionally, the statistical results show that the STO method is superior in average resilience and accuracy. The superior performance and reliability of the STO method are further validated by the Friedman ranking test. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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27 pages, 7070 KiB  
Article
Fuzzy Logic-Based Direct Power Control Method for PV Inverter of Grid-Tied AC Microgrid without Phase-Locked Loop
Electronics 2021, 10(24), 3095; https://doi.org/10.3390/electronics10243095 - 13 Dec 2021
Cited by 30 | Viewed by 2273
Abstract
A voltage source inverter (VSI) is the key component of grid-tied AC Microgrid (MG) which requires a fast response, and stable, robust controllers to ensure efficient operation. In this paper, a fuzzy logic controller (FLC)-based direct power control (DPC) method for photovoltaic (PV) [...] Read more.
A voltage source inverter (VSI) is the key component of grid-tied AC Microgrid (MG) which requires a fast response, and stable, robust controllers to ensure efficient operation. In this paper, a fuzzy logic controller (FLC)-based direct power control (DPC) method for photovoltaic (PV) VSI was proposed, which was modelled by modulating MG’s point of common coupling (PCC) voltage. This paper also introduces a modified grid synchronization method through the direct power calculation of PCC voltage and current, instead of using a conventional phase-locked loop (PLL) system. FLC is used to minimize the errors between the calculated and reference powers to generate the required control signals for the VSI through sinusoidal pulse width modulation (SPWM). The proposed FLC-based DPC (FLDPC) method has shown better tracking performance with less computational time, compared with the conventional MG power control methods, due to the elimination of PLL and the use of a single power control loop. In addition, due to the use of FLC, the proposed FLDPC exhibited negligible steady-state oscillations in the output power of MG’s PV-VSI. The proposed FLDPC method performance was validated by conducting real-time simulations through real time digital simulator (RTDS). The results have demonstrated that the proposed FLDPC method has a better reference power tracking time of 0.03 s along with reduction in power ripples and less current total harmonic distortion (THD) of 1.59%. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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15 pages, 2443 KiB  
Article
A Novel Opposition-Based Arithmetic Optimization Algorithm for Parameter Extraction of PEM Fuel Cell
Electronics 2021, 10(22), 2834; https://doi.org/10.3390/electronics10222834 - 18 Nov 2021
Cited by 19 | Viewed by 1604
Abstract
The model-identification and parameter extraction are a well-defined method for modeling and development purposes of a proton exchange membrane fuel cell (PEMFC) to improve the performance. This paper introduces a novel opposition-based arithmetic optimization algorithm (OBAOA) for identifying the unspecified parameters of PEMFCs. [...] Read more.
The model-identification and parameter extraction are a well-defined method for modeling and development purposes of a proton exchange membrane fuel cell (PEMFC) to improve the performance. This paper introduces a novel opposition-based arithmetic optimization algorithm (OBAOA) for identifying the unspecified parameters of PEMFCs. The cost function is defined as the sum of the square deviations between the experimentally measured values and the optimal achieved values from the algorithm. Ballard Mark V PEM fuel cell is employed and analyzed to demonstrate the capability of the proposed algorithm. To demonstrate system efficiency, simulation results are compared to those of other optimizers under the same conditions. Furthermore, the proposed algorithm is validated through benchmark functions. The final results revealed that the proposed opposition-based arithmetic optimization algorithm can accurately retrieve the parameters of a PEMFC model. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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21 pages, 6851 KiB  
Article
A Novel Three-Phase Harmonic Power Flow Algorithm for Unbalanced Radial Distribution Networks with the Presence of D-STATCOM Devices
Electronics 2021, 10(21), 2663; https://doi.org/10.3390/electronics10212663 - 30 Oct 2021
Cited by 5 | Viewed by 1465
Abstract
Due to the rapid advancement in power electronic devices in recent years, there is a fast growth of non-linear loads in distribution networks (DNs). These non-linear loads can cause harmonic pollution in the networks. The harmonic pollution is low, and the resonance problem [...] Read more.
Due to the rapid advancement in power electronic devices in recent years, there is a fast growth of non-linear loads in distribution networks (DNs). These non-linear loads can cause harmonic pollution in the networks. The harmonic pollution is low, and the resonance problem is absent in distribution static synchronous compensators (D-STATCOM), which is the not case in traditional compensating devices such as capacitors. The power quality issue can be enhanced in DNs with the interfacing of D-STATCOM devices. A novel three-phase harmonic power flow algorithm (HPFA) for unbalanced radial distribution networks (URDN) with the existence of linear and non-linear loads and the integration of a D-STATCOM device is presented in this paper. The bus number matrix (BNM) and branch number matrix (BRNM) are developed in this paper by exploiting the radial topology in DNs. These matrices make the development of HPFA simple. Without D-STATCOM integration, the accuracy of the fundamental power flow solution and harmonic power flow solution are tested on IEEE−13 bus URDN, and the results are found to be precise with the existing work. Test studies are conducted on the IEEE−13 bus and the IEEE−34 bus URDN with interfacing D-STATCOM devices, and the results show that the fundamental r.m.s voltage profile is improved and the fundamental harmonic power loss and total harmonic distortion (THD) are reduced. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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14 pages, 6514 KiB  
Article
An Ultra-Low-Power CMOS Supercapacitor Storage Unit for Energy Harvesting Applications
Electronics 2021, 10(17), 2097; https://doi.org/10.3390/electronics10172097 - 29 Aug 2021
Cited by 3 | Viewed by 2279
Abstract
This work presents an ultra-low-power CMOS supercapacitor storage unit suitable for a plethora of low-power autonomous applications. The proposed unit exploits the unregulated voltage output of harvesting circuits (i.e., DC-DC converters) and redirects the power to the storage elements and the working loads. [...] Read more.
This work presents an ultra-low-power CMOS supercapacitor storage unit suitable for a plethora of low-power autonomous applications. The proposed unit exploits the unregulated voltage output of harvesting circuits (i.e., DC-DC converters) and redirects the power to the storage elements and the working loads. Being able to adapt to the input energy conditions and the connected loads’ supply demands offers extended survival to the system with the self-startup operation and voltage regulation. A low-complexity control unit is implemented which is composed of power switches, comparators and logic gates and is able to supervise two supercapacitors, a small and a larger one, as well as a backup battery. Two separate power outputs are offered for external load connection which can be controlled by a separate unit (e.g., microcontroller). Furthermore, user-controlled parameters such as charging and discharging supercapacitor voltage thresholds, provide increased versatility to the system. The storage unit was designed and fabricated in a 0.18 um standard CMOS process and operates with ultra-low current consumption of 432 nA at 2.3 V. The experimental results validate the proper operation of the overall structure. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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19 pages, 5765 KiB  
Article
Battery Management System Algorithm for Energy Storage Systems Considering Battery Efficiency
Electronics 2021, 10(15), 1859; https://doi.org/10.3390/electronics10151859 - 02 Aug 2021
Cited by 20 | Viewed by 7858
Abstract
Aging increases the internal resistance of a battery and reduces its capacity; therefore, energy storage systems (ESSs) require a battery management system (BMS) algorithm that can manage the state of the battery. This paper proposes a battery efficiency calculation formula to manage the [...] Read more.
Aging increases the internal resistance of a battery and reduces its capacity; therefore, energy storage systems (ESSs) require a battery management system (BMS) algorithm that can manage the state of the battery. This paper proposes a battery efficiency calculation formula to manage the battery state. The proposed battery efficiency calculation formula uses the charging time, charging current, and battery capacity. An algorithm that can accurately determine the battery state is proposed by applying the proposed state of charge (SoC) and state of health (SoH) calculations. To reduce the initial error of the Coulomb counting method (CCM), the SoC can be calculated accurately by applying the battery efficiency to the open circuit voltage (OCV). During the charging and discharging process, the internal resistance of a battery increase and the constant current (CC) charging time decrease. The SoH can be predicted from the CC charging time of the battery and the battery efficiency, as proposed in this paper. Furthermore, a safe system is implemented during charging and discharging by applying a fault diagnosis algorithm to reduce the battery efficiency. The validity of the proposed BMS algorithm is demonstrated by applying it in a 3-kW ESS. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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11 pages, 757 KiB  
Article
Design of a Charge Pump Circuit and System with Input Impedance Modulation for a Flexible-Type Thermoelectric Generator with High-Output Impedance
Electronics 2021, 10(10), 1212; https://doi.org/10.3390/electronics10101212 - 19 May 2021
Cited by 9 | Viewed by 2113
Abstract
This paper describes a charge pump system for a flexible thermoelectric generator (TEG). Even though the TEG has high-output impedance, the system controls the input voltage to keep it higher than the minimum operating voltage by modulating the input impedance of the charge [...] Read more.
This paper describes a charge pump system for a flexible thermoelectric generator (TEG). Even though the TEG has high-output impedance, the system controls the input voltage to keep it higher than the minimum operating voltage by modulating the input impedance of the charge pump using two-phase operation with low- and high-input impedance modes. The average input impedance can be matched with the output impedance of the TEG. How the system can be designed is also described in detail. A design demonstration was performed for the TEG with 400 Ω. The fabricated system was also measured with a flexible-type TEG based on carbon nanotubes. Even with an output impedance of 1.4 kΩ, the system converted thermal energy into electric power of 30 μW at 2.5 V to the following sensor ICs. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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9 pages, 4645 KiB  
Article
A Fully Integrated AC-DC Converter in 1 V CMOS for Electrostatic Vibration Energy Transducer with an Open Circuit Voltage of 10 V
Electronics 2021, 10(10), 1185; https://doi.org/10.3390/electronics10101185 - 15 May 2021
Cited by 5 | Viewed by 2126
Abstract
This paper proposes an AC-DC converter for electrostatic vibration energy harvesting. The converter is composed of a CMOS full bridge rectifier and a CMOS shunt regulator. Even with 1 V CMOS, the open circuit voltage of the energy transducer can be as high [...] Read more.
This paper proposes an AC-DC converter for electrostatic vibration energy harvesting. The converter is composed of a CMOS full bridge rectifier and a CMOS shunt regulator. Even with 1 V CMOS, the open circuit voltage of the energy transducer can be as high as 10 V and beyond. Bandgap reference (BGR) inputs a regulated voltage, which is controlled by the output voltage of the BGR. Built-in power-on reset is introduced, which can minimize the silicon area and power to function normally found upon start-up. The AC-DC converter was fabricated with a 65 nm low-Vt 1 V CMOS with 0.081 mm2. 1 V regulation was measured successfully at 20–70 °C with a power conversion efficiency of 43%. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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15 pages, 1460 KiB  
Article
Valuation of Wind Energy Turbines Using Volatility of Wind and Price
Electronics 2021, 10(9), 1098; https://doi.org/10.3390/electronics10091098 - 07 May 2021
Cited by 3 | Viewed by 1542
Abstract
The limitedness of the nonrenewable local energy resources in Israel, even in the background of the later gas fields’ findings, continues to force the state to devote various efforts towards ‘green’ energy development. These efforts include installations, both for the solar and for [...] Read more.
The limitedness of the nonrenewable local energy resources in Israel, even in the background of the later gas fields’ findings, continues to force the state to devote various efforts towards ‘green’ energy development. These efforts include installations, both for the solar and for wind energy, thus improving the diversity of energy sources. While the standard discounted cash flow (DCF) method using the net present value (NPV) criterion is extensively adopted to evaluate investments, the standard DCF method is inappropriate for the rapidly changing investment climate and for the managerial flexibility in investment decisions. In recent years, the real options analysis (ROA) technique has been widely applied in many studies for the valuation of renewable energy investment projects. Taking into account the above background, we apply, in this study, the real options analysis approach for the valuation of wind energy turbines and apply it to the analysis of wind energy economic potential in Israel, which is the context of our work. We hypothesize that due to nature of wind energy production uncertainties, the ROA method is better than the alternative. The novelty of this paper includes the following: real world wind statistics of the Merom Golan site in Israel (velocity 3.73 m/s, with a standard deviation of 2.03 m/s), a realistic power generation estimation (power generation of 1205.84 kW with a standard deviation of about 0.5% in annual value which is worth about 1.3 M$ per annum), and an economic model to evaluate the profitability of such a project. We thus discuss the existing challenges of diversifying renewable energy sources in Israel by adding wind installations. Our motivation is to introduce a method which will allow investors and officials to take into account uncertainties when deciding in investing in such wind installations. The outcomes of the paper, which are obtained using the method of Weibull statistics and the Black–Scholes ROA technique, include the result that market price volatility adds to the uncertainties much more than any wind fluctuations, provided that the analysis is integrated over a long enough time. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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12 pages, 1639 KiB  
Article
Parameter Extraction of Photovoltaic Module Using Tunicate Swarm Algorithm
Electronics 2021, 10(8), 878; https://doi.org/10.3390/electronics10080878 - 07 Apr 2021
Cited by 29 | Viewed by 3203
Abstract
In the renewable energy sector, the extraction of parameters for solar photovoltaic (PV) cells is a widely studied area of research. Parameter extraction is a non-linear complex optimization problem for solar PV cells. In this research work, the authors have implemented the Tunicate [...] Read more.
In the renewable energy sector, the extraction of parameters for solar photovoltaic (PV) cells is a widely studied area of research. Parameter extraction is a non-linear complex optimization problem for solar PV cells. In this research work, the authors have implemented the Tunicate swarm algorithm (TSA) to estimate the optimized value of the unknown parameters of a PV cell/module under standard temperature conditions. The simulation results have been compared with four different, pre-existing optimization algorithms: gravitational search algorithm (GSA), a hybrid of particle swarm optimization and gravitational search algorithm (PSOGSA), sine cosine (SCA), and whale optimization (WOA). The comparison of results broadly demonstrates that the TSA algorithm outperforms the existing optimization algorithms in terms of root mean square error (RMSE) and convergence rate. Furthermore, the statistical results confirm that the TSA algorithm is a better algorithm in terms of average robustness and precision. The Friedman ranking test is also carried out to demonstrate the competency and reliability of the implemented approach. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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22 pages, 5465 KiB  
Article
An Effective Method for Parameter Estimation of a Solar Cell
Electronics 2021, 10(3), 312; https://doi.org/10.3390/electronics10030312 - 28 Jan 2021
Cited by 27 | Viewed by 4319
Abstract
Parameter extraction of the photovoltaic cell is a highly nonlinear complex optimization problem. This article proposes a new hybrid version of whale optimization and particle swarm optimization algorithm to optimize the photovoltaic cell parameters. The exploitation ability of particle swarm optimization with adaptive [...] Read more.
Parameter extraction of the photovoltaic cell is a highly nonlinear complex optimization problem. This article proposes a new hybrid version of whale optimization and particle swarm optimization algorithm to optimize the photovoltaic cell parameters. The exploitation ability of particle swarm optimization with adaptive weight function is implemented in the pipeline mode with a whale optimization algorithm to improve its exploitation capability and convergence speed. The performance of the proposed hybrid algorithm is compared with six different optimization algorithms in terms of root mean square error and rate of convergence. The simulation result shows that the proposed hybrid algorithm produces not only optimized parameters at different irradiation levels (i.e., 1000 W/m2, 870 W/m2, 720 W/m2, and 630 W/m2) but also estimates minimum root mean square error even at a low level of irradiations. Furthermore, the statistical analysis validates that the average accuracy and robustness of the proposed algorithm are better than other algorithms. The best values of root mean square error generated by the proposed algorithm are 7.1700×104 and 9.8412×104 for single-diode and double-diode models. It is observed that the estimated parameters based on the optimization process are highly consistent with the experimental data. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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Review

Jump to: Editorial, Research

25 pages, 1137 KiB  
Review
Requirements for Energy-Harvesting-Driven Edge Devices Using Task-Offloading Approaches
Electronics 2022, 11(3), 383; https://doi.org/10.3390/electronics11030383 - 27 Jan 2022
Cited by 10 | Viewed by 5085
Abstract
Energy limitations remain a key concern in the development of Internet of Medical Things (IoMT) devices since most of them have limited energy sources, mainly from batteries. Therefore, providing a sustainable and autonomous power supply is essential as it allows continuous energy sensing, [...] Read more.
Energy limitations remain a key concern in the development of Internet of Medical Things (IoMT) devices since most of them have limited energy sources, mainly from batteries. Therefore, providing a sustainable and autonomous power supply is essential as it allows continuous energy sensing, flexible positioning, less human intervention, and easy maintenance. In the last few years, extensive investigations have been conducted to develop energy-autonomous systems for the IoMT by implementing energy-harvesting (EH) technologies as a feasible and economically practical alternative to batteries. To this end, various EH-solutions have been developed for wearables to enhance power extraction efficiency, such as integrating resonant energy extraction circuits such as SSHI, S-SSHI, and P-SSHI connected to common energy-storage units to maintain a stable output for charge loads. These circuits enable an increase in the harvested power by 174% compared to the SEH circuit. Although IoMT devices are becoming increasingly powerful and more affordable, some tasks, such as machine-learning algorithms, still require intensive computational resources, leading to higher energy consumption. Offloading computing-intensive tasks from resource-limited user devices to resource-rich fog or cloud layers can effectively address these issues and manage energy consumption. Reinforcement learning, in particular, employs the Q-algorithm, which is an efficient technique for hardware implementation, as well as offloading tasks from wearables to edge devices. For example, the lowest reported power consumption using FPGA technology is 37 mW. Furthermore, the communication cost from wearables to fog devices should not offset the energy savings gained from task migration. This paper provides a comprehensive review of joint energy-harvesting technologies and computation-offloading strategies for the IoMT. Moreover, power supply strategies for wearables, energy-storage techniques, and hardware implementation of the task migration were provided. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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