Power Source Research Articles

Highly stretchable dynamic hydrogels for soft multilayer electronics.

Recent progress in the development of synthetic polymer networks has enabled the next generation of hydrogel-based machines and devices. The ability to mimic the mechanical and electrical properties of human tissue gives great potential toward the fields of bioelectronics and soft robotics. However, fabricating hydrogel devices that display high ionic conductivity while maintaining high stretchability and softness remains unmet. Here, we synthesize supramolecular poly(ionic) networks, which display high stretchability (>1500%), compressibility (>90%), and rapid self-recovery (<30 s), while achieving ionic conductivities of up to 0.1 S cm -1. Dynamic cross-links give rise to inter-layer adhesion and a stable interface is formed on account of ultrahigh binding affinities (>1013 M-2). Superior adherence between layers enabled the fabrication of an intrinsically stretchable hydrogel power source, paving the way for the next generation of multi-layer tissue mimetic devices.

A Hybrid RBFNN-SPOA Technique for Multi-Source EV Power System with Single-Switch DC-DC Converter

With a single-switched DC-DC converter, a hybrid approach is proposed for a fast-charging (FC) dc to dc converter with the controller for an electric vehicle charging station (EVCS) that combines solar photovoltaic (PV), fuel cells (FC), and a battery energy storage system (BESS). The proposed hybrid technique integrates a radial-basis-function-neural-network (RBFNN) and a student-psychology-optimization-algorithm (SPOA); commonly known as the RBFNN-SPOA technique. The PV-FC hybrid electric vehicle systems, like controllers, electric vehicle, and the vehicle’s power source, are displayed. The proposed converter architectures have less voltage waveform changes, a low voltage stress on semiconductor power sources, and a high-voltage ratio of conversion. The proposed method is to use FC successfully at battery charge states and varied radiation levels. The FC in the controller of SPOA may change the inputs and outputs depending on the battery state of charge (SoC) and PV irradiation. Similarly, the needed input-torque for the motor is forecasted by the recalling recurrent neural network controller using several manually produced torque signals. The performance of the proposed technique is evaluated in MATLAB and is compared to ant colony optimization (ACO), crow optimization algorithm (COA), and fuzzy logic controller (FLC) approaches. According to the results, the efficiency of the proposed technique is 99.17%.

Natural source-field induced polarisation exploration of an iron-oxide copper-gold (IOCG) deposit under thick cover

Induced polarisation (IP) is a common geophysical method of exploration for disseminated sulphides. However, in areas with deep (>200 m) and conductive (10 Ωm or less) cover, the technique is less successful as it requires a significant transmitter source and large-offset dipoles. An alternative approach is to use natural-variations in Earth’s external magnetic field as the polarising source of the signal, known as natural-field IP. This paper presents a study of extracting IP information from electrical dipole observations during a broadband magnetotelluric (MT) program with a 9 km by 9 km grid of 100 sites above the Vulcan IOCG deposit beneath 750 m of cover, ∼40 km north of the Olympic Dam IOCG mine in South Australia. Inter-site transfer functions between 95 sites and five reference sites at the southeast and southwest corners of the grid were computed to determine a phase shift between horizontal electric fields in the bandwidth of 1–100 s period. Phase shifts of up to – 5 degrees were centred on a region of brecciated hematite where drill holes intersected pyrite, and an inferred fault-zone from passive seismics that marks the boundary between upper crust that is resistive (>100 Ω.m) with high magnetic susceptibility to the south of the fault, and a region of conductive crust (<10 Ω.m) which is low magnetic susceptibility. Our study suggests that the natural-field IP method can identify regions of polarizable minerals beneath deep cover where artificial power sources cannot be feasibly deployed. Such surveys are cheaper, safer, and easier to deploy as only receivers are required, and 3D coverage can be obtained as the source-field is of much larger dimension than the survey array. In addition, the natural-field IP signals are observed as part of the MT program so that both electrical resistivity and polarisation parameters can be determined.

Triboelectric Series of Two‐dimensional Metal Carbide MXenes

AbstractThe ever‐increasing prevalence of intelligent electronics underscores an escalating demand for sustainable power sources. Among the emerging energy harvesting technologies, triboelectric nanogenerators (TENGs) stand out as a promising solution for such pressing needs. To date, ongoing efforts have primarily focused on enhancing TENG output, particularly through the development of novel triboelectric materials. Among the potential candidates is the thriving class of two‐dimensional transition‐metal carbides, MXenes, which have predominantly been incorporated into triboelectric layers as nanofillers to enhance their triboelectric properties. Yet, the specific triboelectric characteristics of distinct MXenes remain marginally explored. Herein, the triboelectric properties of various metal carbide MXenes, i.e., V2CTx, Ti3C2Tx, and Nb2CTx, are investigated by assessing the performance of various MXene‐based TENGs combined with different polymers and analyzing their surface potential. According to the attained triboelectric polarities, a triboelectric series of the studied MXenes is determined, demonstrating their remarkable positive triboelectric properties. Further investigations preliminarily reveal the influence of the synthesis method, etchants, intercalating compounds, and postsynthesis procedures on the triboelectric properties of MXenes. Hence, beyond extending the conventional triboelectric series to different metal carbide MXenes, the findings present innovative perspectives on leveraging MXenes to develop high‐performance TENGs for flexible and wearable electronics.

Healthcare and the Internet of Medical Things: Applications, Trends, Key Challenges, and Proposed Resolutions

In recent years, the Internet of medical things (IoMT) has become a significant technological advancement in the healthcare sector. This systematic review aims to identify and summarize the various applications, key challenges, and proposed technical solutions within this domain, based on a comprehensive analysis of the existing literature. This review highlights diverse applications of the IoMT, including mobile health (mHealth) applications, remote biomarker detection, hybrid RFID-IoT solutions for scrub distribution in operating rooms, IoT-based disease prediction using machine learning, and the efficient sharing of personal health records through searchable symmetric encryption, blockchain, and IPFS. Other notable applications include remote healthcare management systems, non-invasive real-time blood glucose measurement devices, distributed ledger technology (DLT) platforms, ultra-wideband (UWB) radar systems, IoT-based pulse oximeters, accident and emergency informatics (A&amp;EI), and integrated wearable smart patches. The key challenges identified include privacy protection, sustainable power sources, sensor intelligence, human adaptation to sensors, data speed, device reliability, and storage efficiency. The proposed mitigations encompass network control, cryptography, edge-fog computing, and blockchain, alongside rigorous risk planning. The review also identifies trends and advancements in the IoMT architecture, remote monitoring innovations, the integration of machine learning and AI, and enhanced security measures. This review makes several novel contributions compared to the existing literature, including (1) a comprehensive categorization of IoMT applications, extending beyond the traditional use cases to include emerging technologies such as UWB radar systems and DLT platforms; (2) an in-depth analysis of the integration of machine learning and AI in IoMT, highlighting innovative approaches in disease prediction and remote monitoring; (3) a detailed examination of privacy and security measures, proposing advanced cryptographic solutions and blockchain implementations to enhance data protection; and (4) the identification of future research directions, providing a roadmap for addressing current limitations and advancing the scientific understanding of IoMT in healthcare. By addressing current limitations and suggesting future research directions, this work aims to advance scientific understanding of the IoMT in healthcare.

Sizing of storage‐based renewable off‐grid system according to supply of electrical and thermal energies considering unscented transformation‐based stochastic optimization: A case study

AbstractThe paper presents the planning (sizing) of a hybrid islanded system containing only renewable sources including wind turbines, photovoltaics, and bio‐waste energy units for the simultaneous supply of electrical and thermal energy. The mentioned renewable sources are used to supply electrical energy. The bio‐waste unit (BEU) is equipped with combined electrical and thermal technology. It is used along with heat pumps to supply thermal energy. Electrical and thermal storage are employed to make the renewable power output as close as possible to the demand level. Electric storage can be either stationary (e.g., battery) or mobile (e.g., electric vehicles), but thermal storage is as stationary type of storage. In the following, the proposed scheme minimizes construction and maintenance costs imposed by power sources, storage devices, and power electronic converters, and expected storage degradation cost. This plan is bound to the model of operation of sources, storage devices, and power electronic converters. In this model, renewables are the main source of power to supply consumers, where storage is adopted to increase the generation level to make it as close as possible to the demand curve. The uncertain parameters are imposed by the load, renewable phenomena, and mobile storage parameters. To model these uncertainties, stochastic optimization based on unscented transformation is used. Finally, the findings of the paper demonstrate that the suggested scheme succeeds in the economic planning of the system with a simultaneous supply of electrical and thermal energy. The BEU equipped with a combined electricity and heat system along with thermal storage and a heat pump to supply thermal load besides providing electric energy can reduce the planning cost by 2.9% compared with the case with only electrical energy. Also, the mobile storage presence in the hybrid system can reduce the number of stationary storage devices, which alone results in a 7.7% decrease in the planning cost of the hybrid system.

Piezoelectric Enhancement in P(VDF-TrFE) Copolymer Films via Controlled and Template-Induced Epitaxy.

The surge in wearable electronics and Internet of Things technologies necessitates the development of both flexible sensors and a sustainable, efficient, and compact power source. The latter further challenges conventional batteries due to environmental pollution and compatibility issues. Addressing this gap, piezoelectric energy harvesters emerge as one kind of promising alternative to convert mechanical energy from ambient sources to electrical energy to charge those low-energy-consumption electronic devices. Despite slightly lower piezoelectric performance compared with those inorganic materials, piezoelectric polymers, notably poly(vinylidene fluoride-co-trifluoroethylene) P(VDF-TrFE), offer compelling properties for both flexible mechanical energy harvesting and self-powered strain/stress sensing, though their piezoelectric performance is expected to be further enhanced via varieties of modulation strategies of microstructures. Herein, we reported the controlled epitaxy process of micrometer-thick copolymer films with the cooperation of friction-transferred poly(tetrafluoroethylene) templates and precise modulation of the annealing conditions. Epitaxial P(VDF-TrFE) films present averaged d33 piezoelectric coefficient of -58.2 pC/N between 50 Hz and 1 kHz with good electromechanical and thermal stability. Owing to the nature of anisotropic crystallization, the epitaxial films exhibit an anisotropic transverse piezoelectric property. Epitaxial films were further utilized for mechanical energy harvesting and monitoring of human pulsation and respiration. This study provided a feasible route for the development of high-performance flexible piezoelectric devices to meet the requirement of flexible electronics.

Multi-Surface Adhesion Luminescent Solar Concentrators for Supply-Less IoT.

The growing prevalence of Internet of Things (IoT) devices hinges on resolving the challenge of powering sensors and transmitters. Addressing this, supply-less IoT devices are gaining traction by integrating energy harvesters. This study introduces a temperature sensor devoid of external power sources, achieved through a novel luminescent solar concentrator (LSC) device based on a stretchable, adhesive elastomer. Leveraging a lanthanide-doped styrene-ethylene-butylene-styrene matrix, the LSC yielded 0.09% device efficiency. The resultant temperature sensor exhibits a thermal sensitivity of 2.1%°C-1 and a 0.06°C temperature uncertainty, autonomously transmitting real-time data to a server for user visualization via smartphones. Additionally, the integration of LED-based lighting enables functionality in low-light conditions, ensuring 24h cycle operation and the possibility of having four distinct thermometric parameters without changing the device configuration, stating remarkable robustness and reliability of the system.

A Survey on Anomalies and Faults That May Impact the Reliability of Renewable-Based Power Systems

The decarbonization of the electricity grid is one of the actions that can help reduce fossil fuel emissions, and thus their impact on global warming in the future. This decarbonization will be achieved mainly through the integration and widespread diffusion of renewable power sources. This is also going to be supported by the shift from the paradigm of production–transmission–distribution, where electricity production oversees large-size power plants, to renewable-based distributed/diffused production, where electricity is generated very close or even by the same (group of) user(s) (or prosumers in the latter case). The number of mid-/small-size installations based on renewable energy technologies will therefore increase substantially, and the related renewable generation will be dominant against that from large-size power plants. Unfortunately, this will very likely reduce the reliability of the grid, unless appropriate countermeasures are taken/implemented, hopefully at the same time that the paradigm shift is being achieved. To this aim, it is important to identify the anomalies and main fault causes that might possibly affect some of the central renewable (wind, PV, hydrogen) and ancillary technologies that will be used to establish future renewable-based power systems. Accordingly, this paper presents a literature survey, also extending the focus to related datasets that can be used for deeper investigation. It is highlighted that the gaps mainly refer to a lack of a common taxonomy that prevents the establishment of structured knowledge in the scope of renewable-based power systems, a lack of contributions to anomalies/faults specific to wind turbines, and a lack of datasets related to electrolyzers, fuel cells, DC/x conversion, and monitoring and communication systems. Further, in the case of monitoring and communication systems, the scientific literature is both very dated, therefore not considering possible new aspects that would be currently worthy of investigation, and not oriented toward the particular domain addressed, thus considering peculiar aspects that are left out.

Methods for Determining Losses and Parameters of Cylindrical-Rotor Medium-Power Synchronous Generators

This paper presents the analytical and numerical application of a method to determine the parameters and power losses in the core of two medium-power synchronous generators. These generators are used as emergency power sources powered by diesel engines, gas engines, and gas turbines. They cover peak electricity demand but can also be used in traction drives. This article presents a new numerical method for determining losses in the generator core based on the use of a time-stepping solution using the FEM method and calculating these losses using analytical formulas. In calculating the losses for the FEM method, approximations of the loss characteristics of the sheet were used with a wide range of induction values and frequencies. This method is specific to the solution used and was adapted from the authors’ previous work on losses in induction machines. A one-phase winding with alternating voltage was supplied to determine the basic parameters in the form of synchronous reactance. Also, an important novelty is the introduction of a new method of determining the saturation state of the magnetic circuit, which significantly affects the machine parameters. The obtained results were used in analytical calculations and implemented in a computer program that allows for the calculation of electromagnetic parameters, operating characteristics, and core losses, taking into account additional losses, total losses, and efficiency, as well as machine parameters in unsteady operating states and the current characteristics of a three-phase symmetrical short circuit at the machine terminals. The calculations obtained were verified experimentally by measurements of real machines.

Rational construction of noble-metal-free fuel cell-supercapacitor hybrid power source using polyaniline electrode as both anode and cathode

The integration of fuel cell device and supercapacitor device into a singular hybrid power source at the electrode level can make the best use of the advantages of each individual device and more importantly, eliminate the energy loss by virtue of the conversion of chemical energy to electric energy on electrocatalyst material and the storage of electric energy on energy storage material simultaneously. To avoid the use of noble metal electrocatalyst and exploit the dual electrocatalytic and capacitive function of polyaniline, a noble-metal-free fuel cell-supercapacitor hybrid power source employing polyaniline electrode as both anode and cathode is rationally constructed. Based on electrochemical in-situ Raman spectroscopy, this work proposes that the open circuit potential (OCP) of polyaniline electrode is a simple and quick indicator of the redox state of polyaniline. After carefully selecting the fuel and carbon-based support, it is found that the ascorbic acid fuel and the carbon fiber cloth supported polyaniline contributes to the lowest OCP threshold in the anode, and thus the fastest self-charge and largest stabilized open circuit voltage of hybrid power source. The hybrid power source can be self-charged to 0.32 V and yield a peak power density of 0.21 mW cm−2.

Conditions of Decision-Making Related to Implementation of Hydrogen-Powered Vehicles in Urban Transport: Case Study of Poland

The changes in geopolitical and ecological conditions brought about the need to use environmentally friendly sources of vehicle power. This impacted the accelerated activities related to the use of hydrogen fuel in transport means. Based on the observations carried out in the countries of Central and Eastern Europe, it was found that the process of implementing hydrogen-powered vehicles in public transport is connected with difficulties faced by transport companies with regard to the purchase of these transport means. This study aims to analyse the conditions for making decisions regarding the implementation of hydrogen-powered buses in urban transport. A case study was considered, and the factors influencing the decisions related to the application of hydrogen-powered buses in Poland were analysed. The survey method was used to carry out the research. A questionnaire was developed, and the survey was conducted among representatives of transport companies that provide public transport services in Polish cities. As a result of the research, it was found that city authorities play a key role in deciding on the implementation of hydrogen-powered buses. The highest ranks among the proposed criteria influencing the decision on the purchase of hydrogen-powered buses were the economic ones. The concerns and benefits resulting from the potential purchase of hydrogen-powered buses were also examined. It was revealed that the decision to buy buses is most influenced by factors such as ensuring access to hydrogen and its price. The recommendations for transport companies and city authorities were formulated.

Techno-Economic Analysis of Atmospheric Water Harvesting Across Climates.

Drinking water scarcity is a global challenge as groundwater and surface water availability diminishes. The atmosphere is an alternative freshwater reservoir that has universal availability and could be harvested as drinking water. In order to effectively perform atmospheric water harvesting (AWH), we need to (1) understand how different climate regions (e.g., arid, temperate, and tropical) drive the amount of water that can be harvested and (2) determine the cost to purchase, operate, and power AWH. This research pairs thermodynamics with techno-economic analysis to calculate the water productivity and cost breakdown of a representative condensation-based AWH unit with water treatment. We calculate the monthly and annual levelized cost of water from AWH as a function of climate and power source (grid electricity vs renewable energy from solar photovoltaics (PV)). In our modeled unit, AWH can provide 1744-2710 L/month in a tropical climate, 394-1983 L/month in a temperate climate, and 37-1470 L/month in an arid climate. The levelized cost of water of AWH powered by the electrical grid is $0.06/L in a tropical climate, $0.09/L in a temperate climate, and $0.17/L in an arid climate. If off-grid solar PV was purchased at the time of purchasing the AWH unit to power the AWH, the costs increase to $0.40/L in an arid climate, $0.17/L in a temperate climate, and $0.10/L in a tropical climate. However, if using existing solar PV there are potential cost reductions of 4.25-5-fold between purchasing and using existing solar PV, and 2-3-fold between using the electrical grid and existing solar PV, with the highest cost reductions occurring in the tropical climate. Using existing solar PV, the levelized cost of AWH is $0.09/L in an arid climate, $0.04/L in a temperate climate, and $0.02/L in a tropical climate.

Ambient Moisture-Driven Self-Powered Iontophoresis Patch for Enhanced Transdermal Drug Delivery.

Iontophoretic transdermal drug delivery (TDD) devices are known to enhance the transdermal transport of drugs. However, conventional transdermal iontophoretic devices require external power sources, wired connections, or mechanical parts, which reduce the comfort level for patients during extended use. In this work, a self-powered, wearable transdermal iontophoretic patch (TIP) is proposed by harvesting ambient humidity for energy generation, enabling controlled TDD. This patch primarily uses moist-electric generators (MEGs) as its power source, thus obviating the need for complex power management modules and mechanical components. A single MEG unit can produce an open-circuit voltage of 0.80V and a short-circuit current of 11.65µA under the condition of 80% relative humidity. Amplification of the electrical output is feasible by connecting multiple generator units in series and parallel, facilitating the powering of certain commercial electronic devices. Subsequently, the MEG array is integrated with the TDD circuit to create the wearable TIP. After 20 min of application, the depth of drug penetration through the skin is observed to increase threefold. The effective promotion effect of TIP on the transdermal delivery of ionized drugs is corroborated by simulations and experiments. This wearable TIP offers a simple, noninvasive solution for TDD.

A Current Development of Energy Harvesting Systems for Energy-Independent Bioimplantable Biosensors.

Biosensors have emerged as vital tools for the detection and monitoring of essential biological information. However, their efficiency is often constrained by limitations in the power supply. To address this challenge, energy harvesting systems have gained prominence. These off-grid, independent systems harness energy from the surrounding environment, providing a sustainable solution for powering biosensors autonomously. This continuous power source overcomes critical constraints, ensuring uninterrupted operation and seamless data collection. In this article, a comprehensive review of recent literature on energy harvesting-based biosensors is presented. Various techniques and technologies are critically examined, including optical, mechanical, thermal, and wireless power transfer, focusing on their applications and optimization. Furthermore, the immense potential of these energy harvesting-driven biosensors is highlighted across diverse fields, such as medicine, environmental surveillance, and biosignal analysis. By exploring the integration of energy harvesting systems, this review underscores their pivotal role in advancing biosensor technology. These innovations promise improved efficiency, reduced environmental impact, and broader applicability, marking significant progress in the field of biosensors.

Low-carbon oriented planning of shared photovoltaics and energy storage systems in distribution networks via carbon emission flow tracing

With the targets of carbon peaking and carbon neutrality, carbon emission reduction measures have become significant issues in new-type power systems. Distribution networks (DNs), which multiple power sources and flexible loads access to, play an essential role in exploiting the potential of reducing carbon emissions on the demand side. To achieve a global carbon emission reduction considering the carbon quota of each customer, shared photovoltaics (PVs) and energy storage systems (ESSs) are allocated with a centralized calculation and optimization conducted by DNs. To solve two key points in demand-side planning of shared PVs and ESSs in distribution networks, i.e., the accuracy of carbon emission flow (CEF) calculation and carbon quota-oriented optimization planning, this paper proposes a low-carbon oriented planning method for shared PVs and ESSs via CEF tracing. Firstly, a novel CEF calculation method is proposed based on the forward current sweep and backward voltage sweep algorithm, which considers the tracing of reactive power and power losses. Next, carbon emission index and economic index of allocating shared PVs and ESSs are defined. Subsequently, a bi-level optimization model is presented, considering the excess carbon emissions of each load based on carbon accounting and carbon quotas. Finally, the superiority of the proposed method is verified through a modified IEEE 33-node distribution network, and the effects of various investment constraints and carbon quotas are discussed.

Exploring a New Class of PVDF/3‐Aminopropyltriethoxysilane (core) and 2,2‐Bis(hydroxymethyl)butyric Acid (monomer)‐Based Hyperbranched Polyester Hybrid Fibers by Electrospinning Technique for Enhancing Triboelectric Performance

AbstractWith the rapid advancement in sensor technologies, triboelectric nanogenerators (TENGs) have emerged as a promising sustainable power source for intelligent electronics. Herein, fabricated a novel 3‐aminopropyltriethoxysilane (core) and 2,2‐bis(hydroxymethyl)butyric acid (monomer)‐based hyperbranched polyester by facile single‐step polycondensation technique generation 2 (Si‐HBP‐G2). Further, a new class of polyvinylidene fluoride (PVDF) and different weight percentages (0, 5, 10, 15, and 20 wt%) of Si‐HBP‐G2 hybrid fiber blends are prepared by traditional electrospinning technique. The as‐prepared Si‐HBP‐G2 and its blends are well characterized using SEM/EDS, FTIR, NMR, and XRD studies. The influence of Si‐HBP‐G2 content on triboelectric performance in terms of the open circuit potential (VOC) and short circuit current (ISC) is evaluated using aluminum (Al) as a counter electrode. Among them, 15 wt% of Si‐HBP‐G2/PVDF hybrid fiber mat (PG2‐15) exhibits superior electrical performance. Which is almost increased 5.9 times (22–130 V) of VOC and 4.9 times (0.71–3.5 µA) of ISC than PVDF fiber mate. These results reveal the significance of Si‐HBP‐G2 in the triboelectric performance. The optimized TENG device (PG2‐15/Al‐TENG) exhibits a peak power density of 0.2 Wm−2 at 100 MΩ external load. Finally, the PG2‐15/Al‐TENG practically demonstrates real‐time application energy harvesting applications such as powering 100 LEDs and a stopwatch.

A Current Development of Energy Harvesting Systems for Energy-Independent Bioimplantable Biosensors.

Biosensors have emerged as vital tools for the detection and monitoring of essential biological information. However, their efficiency is often constrained by limitations in the power supply. To address this challenge, energy harvesting systems have gained prominence. These off-grid, independent systems harness energy from the surrounding environment, providing a sustainable solution for powering biosensors autonomously. This continuous power source overcomes critical constraints, ensuring uninterrupted operation and seamless data collection. In this article, a comprehensive review of recent literature on energy harvesting-based biosensors is presented. Various techniques and technologies are critically examined, including optical, mechanical, thermal, and wireless power transfer, focusing on their applications and optimization. Furthermore, the immense potential of these energy harvesting-driven biosensors is highlighted across diverse fields, such as medicine, environmental surveillance, and biosignal analysis. By exploring the integration of energy harvesting systems, this review underscores their pivotal role in advancing biosensor technology. These innovations promise improved efficiency, reduced environmental impact, and broader applicability, marking significant progress in the field of biosensors.

Data-driven MPPT techniques for optimizing vehicular fuel cell performance in hybrid DC microgrid

This paper aims to apply data-driven maximum power point tracking (MPPT) techniques specifically tailored for fuel cell vehicle (FCV) supported hybrid DC microgrids to enhance the power harvesting capability of fuel cell (FC) stacks. Compared to existing MPPT techniques, the current study focuses on developing and evaluating data-driven approaches for maximum power extraction by dynamically determining the operating point of FC power sources through a Zeta converter. An in-depth analysis is conducted by considering parameters such as efficiency, tracking accuracy, response time, and robustness to variations in load demand and operating conditions. The performance results validate that the developed three-layer neural network (TNN)-based MPPT gives better performance findings than Gaussian process regression (GPR), support vector regression (SVR), decision tree regression (DTR), and bagging ensemble decision tree (BEDT). In the performance evaluation phase, a vehicular FC with a rating of 1.26 kW is designed and operated within the temperature range of 320 K to 343 K for hydrogen pressure values ranging from 1 bar to 1.8 bar. For these operational conditions, the prediction accuracy value of the proposed TNN method is 99.6% while the performance values GPR, SVR, DTR, and BEDT are 99%, 98.6%, 97.2%, and 96%. In addition, system efficiency is increased by 0.98%, 1.25%, 2.51%, and 3.02% compared to GPR, SVR, DTR, and BEDT, respectively.

Hybrid strategy of flexibility regulation and economic energy management in the power system including renewable energy hubs based on coordination of transmission and distribution system operators

Energy management of energy hubs in the power system impacts both transmission and distribution networks and their operations. Hence, to enhance efficiency, there should be bilateral coordination between distribution and transmission networks. Moreover, thanks to including power sources, storage, and responsive loads, hubs can earn financial benefits from the energy and ancillary services market. Therefore, this paper presents the operation of distribution and transmission networks in the presence of flexible-renewable energy hubs based on transmission system operator (TSO)-distribution system operator (DSO) coordination according to the market clearing price modeling in energy and flexibility markets. The proposed scheme minimizes the sum of the expected operating costs of the networks and hubs minus the expected flexibility profit of the hubs. The scheme is constrained to optimal power flow equations of the networks, flexibility limit of the networks, and flexibility-operation model of renewable energy hubs located in transmission and distribution networks. The unscented transformation method is used to model the uncertainties of load, renewable sources, and stationary storage (aggregation of electric vehicles). Energy price and flexibility are among the dual variables of the problem. To simultaneously calculate these variables and the main variables of the problem, an integrated model of the suggested scheme based on the penalty function technique is extracted. Eventually, numerical results validate the capability of the scheme in enhancing the operation, economic, and flexibility status of the proposed scheme, in which renewable sources along with storage and responsive load in the energy hub can obtain 100 % flexibility conditions for the networks. They help enhance the economic and operation indices of distribution and transmission networks by about 26 %-44 % and 22 %-33 % compared to the case without hubs and renewable sources.