Publikační činnost Centra energetických jednotek pro využití netradičních zdrojů energie (9370)

Permanent URI for this collectionhttp://hdl.handle.net/10084/89109

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Centra energetických jednotek pro využití netradičních zdrojů energie (9370) v časopisech registrovaných ve Web of Science od roku 2003 po současnost.
Do kolekce jsou zařazeny:
a) publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
b) publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

Bibliografické záznamy byly původně vytvořeny v kolekci Publikační činnost akademických pracovníků VŠB-TUO, která sleduje publikování akademických pracovníků od roku 1990.

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Now showing 1 - 20 out of 356 results

Experimental variable band hybrid current mode control for high power high frequency inverter in electro surgical applications
(IEEE, 2024) Mohsin Rafiq, Muhammad; Ullah, Nasim; Prokop, Lukáš; Mišák, Stanislav
Electrosurgical generators (ESGs) are vital during medical operations, providing high-frequency electrical currents for cutting tissue and coagulation in surgery. Maintaining precise control over output power is challenging due to variable tissue loads. Inconsistent regulation can lead to undesirable surgical outcomes. This paper addresses this challenge through a novel Variable band hybrid current mode control (VBHCMC) technique. The study explores the limitations of existing approaches, such as peak current mode control (PCMC), emphasizing the need for improving control methodologies. The proposed VBHCMC method ensures stable output power, addressing issues associated with PCMC. It dynamically adapts the hysteresis band for variable load impedances, enhancing stability. The significance of this approach lies in its ability to combine the benefits of peak and valley current mode controls while maintaining a nearly constant switching frequency, significantly reducing steady-state errors. Results demonstrate significant reduction in steady-state errors compared to conventional PCMC. The proposed controller provides an effective solution to challenges faced in regulating output power during surgical procedures, enhancing safety and precision. The results have been verified in the MATLAB/Simulink environment, Processor-in-Loop (PIL) simulation in PSIM and using hardware validation.
Hybrid optimal-FOPID based UPQC for reducing harmonics and compensate load power in renewable energy sources grid connected system
(PLOS, 2024) Devi, T. Anuradha; Rao, G. Srinivasa; Kumar, T. Anil; Goud, B. Srikanth; Reddy, Ch. Rami; Eutyche, Mbadjoun Wapet Daniel; Aymen, Flah; El-Bayedh, Claude Ziad; Kraiem, Habib; Blažek, Vojtěch
Integration of renewable energy sources (RES) to the grid in today's electrical system is being encouraged to meet the increase in demand of electrical power and also overcome the environmental related problems by reducing the usage of fossil fuels. Power Quality (PQ) is a critical problem that could have an effect on utilities and consumers. PQ issues in the modern electric power system were turned on by a linkage of RES, smart grid technologies and widespread usage of power electronics equipment. Unified Power Quality Conditioner (UPQC) is widely employed for solving issues with the distribution grid caused by anomalous voltage, current, or frequency. To enhance UPQC performance, Fractional Order Proportional Integral Derivative (FOPID) is developed; nevertheless, a number of tuning parameters restricts its performance. The best solution for the FOPID controller problem is found by using a Coati Optimization Algorithm (COA) and Osprey Optimization Algorithm (OOA) are combined to make a hybrid optimization CO-OA algorithm approach to mitigate these problems. This paper proposes an improved FOPID controller to reduce PQ problems while taking load power into account. In the suggested model, a RES is connected to the grid system to supply the necessary load demand during the PQ problems period. Through the use of an enhanced FOPID controller, both current and voltage PQ concerns are separately modified. The pulse signal of UPQC was done using the optimal controller, which analyzes the error value of reference value and actual value to generate pulses. The integrated design mitigates PQ issues in a system at non-linear load and linear load conditions. The proposed model provides THD of 12.15% and 0.82% at the sag period, 10.18% and 0.48% at the swell period, and 10.07% and 1.01% at the interruption period of non-linear load condition. A comparison between the FOPID controller and the traditional PI controller was additionally taken. The results showed that the recommended improved FOPID controller for UPQC has been successful in reducing the PQ challenges in the grid-connected RESs system.
A comprehensive review of wind power integration and energy storage technologies for modern grid frequency regulation
(Elsevier, 2024) Ullah, Farhan; Zhang, Xuexia; Khan, Mansoor; Mastoi, Muhammad Shahid; Munir, Hafiz Mudassir; Flah, Aymen; Said, Yahia
Integrating wind power with energy storage technologies is crucial for frequency regulation in modern power systems, ensuring the reliable and cost-effective operation of power systems while promoting the widespread adoption of renewable energy sources. Power systems are changing rapidly, with increased renewable energy integration and evolving system architectures. These transformations bring forth challenges like low inertia and unpredictable behavior of generation and load components. As a result, frequency regulation (FR) becomes increasingly important to ensure grid stability. Energy Storage Systems (ESS) with their adaptable capabilities offer valuable solutions to enhance the adaptability and controllability of power systems, especially within wind farms. This research provides an updated analysis of critical frequency stability challenges, examines state-of-the-art control techniques, and investigates the barriers that hinder wind power integration. Moreover, it introduces emerging ESS technologies and explores their potential applications in supporting wind power integration. Furthermore, this paper offers suggestions and future research directions for scientists exploring the utilization of storage technologies in frequency regulation within power systems characterized by significant penetration of wind power.
Designing a multi-objective energy management system in multiple interconnected water and power microgrids based on the MOPSO algorithm
(Elsevier, 2024) Alkuhayli, Abdulaziz; Dashtdar, Masoud; Flah, Aymen; El-Bayeh, Claude Ziad; Blažek, Vojtěch; Prokop, Lukáš
In this paper, a method of the energy management system (EMS) in multiple microgrids considering the constraints of power flow based on the three-objective optimization model is presented. The studied model specifications, the variable speed pumps in the water network as well and the storage tanks are optimally planned as flexible resources to reduce operating costs and pollution. The proposed method is implemented hierarchically through two primary and secondary control layers. At the primary control level, each microgrid performs local planning for its subscribers and energy generation resources, and their excess or unsupplied power is determined. Then, by sending this information to the central energy management system (CEMS) at the secondary level, it determines the amount of energy exchange, taking into account the limitations of power flow. Energy storage systems (ESS) are also considered to maintain the balance between power generation by renewable energy sources and consumption load. Also, the demand response (DR) program has been used to smooth the load curve and reduce operating costs. Finally, in this article, the multi-objective particle swarm optimization (MOPSO) is used to solve the proposed three-objective problem with three cost functions generation, pollution, and pump operation. Additionally, sensitivity analysis was conducted with uncertainties of 25 % and 50 % in network generation units, exploring their impact on objective functions. The proposed model has been tested on the microgrid of a 33-bus test distribution and 15-node test water system and has been investigated for different cases. The simulation results prove the effectiveness of the integration of water and power network planning in reducing the operating cost and emission of pollution in such a way that the proposed control scheme properly controls the performance of microgrids and the network in interactions with each other and has a high level of robustness, stable behavior under different conditions and high quality of the power supply. In such a way that improvements of 41.1 %, 52.2 %, and 20.4 % in the defined objective functions and the evaluation using DM, SM, and MID indices further confirms the algorithm ' s enhanced performance in optimizing the specified objective functions by 51 %, 11 %, and 5.22 %, respectively.
Numerical analysis on inlet position and orientation for enhanced thermal performance of a solar thermochemical reactor for two-step WS cycle for hydrogen production
(Springer Nature, 2024) Sharma, Jeet Prakash; Kumar, Ravinder; Ahmadi, Mohammad Hossein; Bekbolatova, Zhannat; Sarsenbayev, Yerlan; Najser, Jan; Blažek, Vojtěch; Prokop, Lukáš
This study presents the effect of inert gas flow inlet positioning and orientation on the conversion efficiency of the proposed solar thermochemical reactor for hydrogen production. The nitrogen gas was used as (i) a reducing agent, (ii) a cooling agent to control the porous matrix temperature and (iii) removing oxygen from the STCR chamber. The result of the study demonstrates that the highest average temperature yield of 1570 K occurred at an inlet position of 10 mm with a 75° inclination, while 1665 K was obtained at an inlet position of 10 mm with a 90° inclination. Additionally, a temperature of 1353 K was achieved at an inlet position of 12 mm with a 75° inclination, both radially (for 20 mm thickness) and axially (over 80 mm length) along the centerline of the STCR chamber (extending 125 mm in length). The optimized inlet positioning and orientation provided the improved design of the solar thermochemical reactor (STCR) chamber capable of achieving the uniform solar flux profile and high-temperature distribution in the porous media to successfully carry out the redox reactions and achieve high solar-to-fuel conversion efficiency.
Straw pyrolysis for use in electricity storage installations
(Elsevier, 2024) Chojnacki, Jerzy; Kielar, Jan; Najser, Jan; Frantík, Jaroslav; Najser, Tomáš; Mikeska, Marcel; Gaze, Błażej; Knutel, Bernard
A concept has been proposed for an installation designed to store excess electricity periodically occurring on the grid. Excess electricity will be used for straw pyrolysis. The main pyrolysis product, gas, will be used to generate electricity using a combustion generator to feed back power into the grid during periods of shortage. The resulting biochar from the pyrolysis can be introduced into the soil to improve soil quality and play a significant role in carbon sequestration. The system uses an electrically heated reactor with a screw conveyor. To preliminarily assess the feasibility of this system, experiments were carried out using wheat straw at temperatures of 300, 400, 500, 600, and 700 degrees C for the pyrolysis reactor. The resulting gas -to -feedstock mass ratio ranged from 29.04 % at 300 degrees C to 52.7 % at 700 degrees C reactor temperature, the biochar mass yield ratio to feedstock varied from 39.41 % to 27.36 % (at 700 degrees C), and the pyrolysis liquid ranged from 31.55 % to 27.36 % (at 700 degrees C). The pyrolytic liquid contained a high water content relative to its mass, reaching up to 95.2 % at 700 degrees C, rendering it less suitable as an energy feedstock. At a reactor temperature of 700 degrees C, the energy value of the gas produced from the feedstock was twice that of the electricity used for the pyrolysis process. These results suggest the feasibility and operation of the proposed installation.
Plastic particles in urban compost and their grain size distribution
(Elsevier, 2024) Brťková, Hana; Růžičková, Jana; Slamová, Karolina; Raclavská, Helena; Kucbel, Marek; Šafář, Michal; Gikas, Petros; Juchelková, Dagmar; Švédová, Barbora; Flodrová, Šárka
Gathering information on plastic particles in composts and the processes they undergo is important in terms of potentially limiting their further entry into the environment, for example, in improving the fertilising properties of soils. Microplastics (MPs) were determined in composts produced from urban greenery. They are present in decreasing order: polyethylene terephthalate, polystyrene, polyethylene, and polypropylene. The determination of polymers and additives used to improve their properties was performed by pyrolysis and gas chromatography with mass spectrometric detection (Py-GC/MS). Additives and microplastics are most concentrated in composts in the 0.315-0.63 and 0.63-1.25 mm grain size class, together with the carbon contained in the compost dry matter. Additives form 0.11-0.13% of MPs in dry matter of compost. The average concentration of microplastics in the particle size class from 0.63 to 1.25 mm is 2434 +/- 224 mg/kg; in the total sample of composts, it is 1368 +/- 286 mg/kg of P-MPs. For composts with particle size <2.5 mm, a relationship between the C/N ratio and the plastic particle concentration was statistically significant. It documents a similar behaviour of lignocellulose and plastic particles during the degradation processes. A relationship between the concentration of polymer markers and additives in the compost dry matter and their concentrations in the leachate has been demonstrated. The leachability from compost is higher for additives than for chemical compounds originating from the decomposition of the main components of MPs. The suitability of the use of the compost for agricultural purposes was monitored by the germination index (GI) for watercress. The lowest value of the GI was determined in the particle size class from 0.63 to 1.25 mm. The leachability of polymer markers and additives alone cannot explain the low GI value in this grain size class. The GI value is also influenced by the leachability of chemical compounds characterised by the value of dissolved organic carbon (DOC) and water-leachable nitrogen (N-w). A statistically significant dependence between DOC/N-w and the germination index value was found.
Empowering power distribution: Unleashing the synergy of IoT and cloud computing for sustainable and efficient energy systems
(Elsevier, 2024) Rajagopalan, Arul; Swaminathan, Dhivya; Bajaj, Mohit; Damaj, Issam; Rathore, Rajkumar Singh; Singh, Arvind R.; Blažek, Vojtěch; Prokop, Lukáš
This article gives an in-depth review of the integration of the Internet of Things (IoT) and cloud computing in power systems (PS), to improve power distribution sustainability and efficiency. IoT provides seamless communication throughout the electrical grid by leveraging modern Information and Communication Technology (ICT) and embedded technologies, ushering in an information revolution. The Internet of Energy (IoE) emphasizes the convergence of ICT and energy generation, highlighting IoT's disruptive potential in the electric power industry. Cloud computing, on the other hand, effectively handles data processing, storage, and computational resources. Cloud of Things (CoT), the merging of IoT with cloud computing, provides huge processing capabilities and quick access to computer resources, enabling novel applications and analytics in power distribution. The influence of IoT and cloud-based applications in the distributed generation and renewable energy industries is demonstrated via case studies and real-world scenarios. The introduction of new parameters and optimization strategies highlights the potential for future developments in power technology. To achieve smooth integration and effective resource utilization, proposals for additional research in electric cars and grid-to-vehicle technologies have been made. The integration of CoT into PS has an enormous influence, opening the door for increased efficiency, sustainability, and reliability in the energy sector, as shown by the study's overall findings. Future generations will advance thanks to the CoT, which presents exciting potential for a more eco-friendly and technologically sophisticated energy landscape.
A novel approach to utilization vehicle to grid technology in microgrid environment
(Elsevier, 2024) Blažek, Vojtěch; Vantuch, Tomáš; Slanina, Zdeněk; Vysocký, Jan; Prokop, Lukáš; Mišák, Stanislav; Piecha, Marian; Walendziuk, Wojciech
This article presents a novel approach to the Vehicle To Grid (V2G) technology in a microgrid with a Demand Side Response (DSR) algorithm. The research describes the microgrid control system used on a physical testing platform. The platform simulates a small-scale microgrid with a photovoltaic plant (PV) as its primary stochastic energy source. The local control system is based on a Demand Side Response algorithm called Active Demand Side Management (ADSM). The ADSM algorithm is implemented with a non-dominated sorting genetic algorithm II (NSGA-2). The article presents the study of the microgrid operation using the results of two experiments. The first experiment includes three scenarios representing electricity consumption in three ordinary households, exploiting a small-scale microgrid during four seasons. Every scenario compares the microgrid’s insufficient energy with and without optimization, with an EV and without EV, and with the tariff mode (energy supply from the distribution network in a chosen time). The second experiment deals with the effect of the size of the static battery in the microgrid on insufficient energy and the efficiency of the optimization itself. The results reveal a fundamentally positive impact of optimizing the control system, which uses an EV, on the potential insufficient energy in the microgrid platform.
Novel lossy compression method of noisy time series data with anomalies: Application to partial discharge monitoring in overhead power lines
(Elsevier, 2024) Klein, Lukáš; Dvorský, Jiří; Seidl, David; Prokop, Lukáš
In overhead power transmission lines, particularly in regions like natural parks where establishing a safe zone is difficult, the adoption of cross-linked polyethylene insulated covered conductors (CCs) helps prevent outages due to vegetation contact. However, these CCs are susceptible to partial discharge (PD) activity, which can degrade insulation and lead to system failures. Detecting and analyzing PD are essential for maintaining power system reliability and safety. A key challenge in PD monitoring is transmitting the large volumes of PD signal data over unreliable 2G networks, as existing compression methods either compromise on data integrity or are ineffective. This paper introduces a novel lossy compression technique utilizing an autoencoder with skip connections and correction data to address this issue. Unlike previous algorithms that struggle with noisy time series data and fail to preserve crucial anomaly information, our method reconstructs the signal without anomalies, which are subsequently restored using correction data. Achieving a compression factor of about 25 (reducing data to 4.1% of its original size), this approach maintains essential PD signal features for analysis. The effectiveness of our method is validated by three classification algorithms, showing promise for future fault detection, diagnosis, and memory space reduction. This innovative compression solution marks a significant advancement in PD data processing, offering a balanced trade-off between compression efficiency and data fidelity, and paving the way for enhanced remote monitoring in power transmission systems.
Reimagining E-mobility: A holistic business model for the electric vehicle charging ecosystem
(Elsevier, 2024) Sabyasachi, Sidharth; Singh, Arvind R.; Godse, Revati; Jaiswal, Supriya; Bajaj, Mohit; Srivastava, Ishan; Blažek, Vojtěch; Prokop, Lukáš; Mišák, Stanislav
Nowadays business has shifted from product-centric to customer-centric due to the industrial revolution. As a result, the customer’s problem and experience need to be studied and inspected thoroughly to find solutions. Charging stations implementing different charging technologies are reinforced in various topographical locations. Varied charging methods, including AC slow charging, AC fast charging, DC level 1 charging, DC level 2 charging, wireless charging is implemented so far to reduce the charging time. Various business models are established and reported by researchers to support the EV ecosystem. This paper presents one such business model for an electric vehicle (EV) charging system. Design Thinking is one of the problem-solving approaches discussed here. How to tackle the charging issues by implementing different technologies is also discussed. Different phases of Design Thinking are used to find the possible solution to the problems faced by customers. Different groups of customers’ problems and how the proposed solution can fulfil a major group of customers’ needs are discussed here.
A comprehensive bibliometric survey of micro-expression recognition system based on deep learning
(Elsevier, 2024) Ahmad, Adnan; Li, Zhao; Iqbal, Sheeraz; Aurangzeb, Muhammad; Tariq, Irfan; Flah, Ayman; Blažek, Vojtěch; Prokop, Lukáš
Micro-expressions (ME) are rapidly occurring expressions that reveal the true emotions that a human being is trying to hide, cover, or suppress. These expressions, which reveal a person's actual feelings, have a broad spectrum of applications in public safety and clinical diagnosis. This study provides a comprehensive review of the area of ME recognition. A bibliometric and network analysis techniques is used to compile all the available literature related to ME recognition. A total of 735 publications from the Web of Science (WOS) and Scopus databases were evaluated from December 2012 to December 2022 using all relevant keywords. The first round of data screening produced some basic information, which was further extracted for citation, coupling, co-authorship, co-occurrence, bibliographic, and co-citation analysis. Additionally, a thematic and descriptive analysis was executed to investigate the content of prior research findings, and research techniques used in the literature. The year wise publications indicated that the published literature between 2012 and 2017 was relatively low but however by 2021, a nearly 24-fold increment made it to 154 publications. The three topmost productive journals and conferences included IEEE Transactions on Affective Computing (n = 20 publications) followed by Neurocomputing (n = 17) and Multimedia tools and applications (n = 15). Zhao G was the most proficient author with 48 publications and the top influential country was China (620 publications). Publications by citations showed that each of the authors acquired citations ranging from 100 to 1225. While publications by organizations indicated that the University of Oulu had the most published papers (n = 51). Deep learning, facial expression recognition, and emotion recognition were among the most frequently used terms. It has been discovered that ME research was primarily classified in the discipline of engineering, with more contribution from China and Malaysia comparatively.
Islanding detection and power quality diagnosis of wind power integrated microgrid with reduced feature trained novel optimized random decision forest
(Wiley, 2024) Mishra, Sairam; Mallick, Ranjan K.; Gadanayak, Debadatta A.; Nayak, Pravati; Flah, Aymen; El-Bayeh, Claude Ziad; Kraiem, Habib; Prokop, Lukáš
Distributed generations (DGs) have been increasingly addressing the ongoing power deficit in the electricity market. However, a significant concern in DG-integrated microgrids is the detection of accidental islanding. To tackle this issue, this article proposes a cost-friendly, novel data-driven passive islanding detection scheme named EEMD-HOBRC, combining noise-assisted ensemble empirical mode decomposition (EEMD) and a hybrid optimization-based random forest classifier (HOBRFC). The detection scheme employs a diverse set of features extracted from both raw and EEMD decomposed signals. Essential features are selected using the binary grey wolf optimizer (BGWO) to reduce computational burden. To further improve classification accuracy, the parameters of the random forest classifier are optimized through a hybrid particle swarm and reformed grey wolf optimization (PSRGWO) technique with Cohen's kappa index as the cost function. The proposed technique is rigorously validated in two different multi-DG environments, encompassing islanding and various nonislanding events. The results demonstrate the effectiveness of the approach in terms of enhanced accuracy, detection time, and performance under both noisy and noise-free conditions. The accuracy of detection under ideal and high noise scenarios is found to be 99.88% and 99.2%, respectively, with maximum detection time of 34.27 ms. Comparative analysis with other algorithms also supports the superiority of the proposed technique. Finally, the method is successfully applied to shrink the nondetection zone (NDZ) with minimal power mismatch, further enhancing its utility in practical applications.
Sustainable power management in light electric vehicles with hybrid energy storage and machine learning control
(Springer Nature, 2024) Punyavathi, R.; Pandian, A.; Singh, Arvind R.; Bajaj, Mohit; Tuka, Milkias Berhanu; Blažek, Vojtěch
This paper presents a cutting-edge Sustainable Power Management System for Light Electric Vehicles (LEVs) using a Hybrid Energy Storage Solution (HESS) integrated with Machine Learning (ML)-enhanced control. The system's central feature is its ability to harness renewable energy sources, such as Photovoltaic (PV) panels and supercapacitors, which overcome traditional battery-dependent constraints. The proposed control algorithm orchestrates power sharing among the battery, supercapacitor, and PV sources, optimizing the utilization of available renewable energy and ensuring stringent voltage regulation of the DC bus. Notably, the ML-based control ensures precise torque and speed regulation, resulting in significantly reduced torque ripple and transient response times. In practical terms, the system maintains the DC bus voltage within a mere 2.7% deviation from the nominal value under various operating conditions, a substantial improvement over existing systems. Furthermore, the supercapacitor excels at managing rapid variations in load power, while the battery adjusts smoothly to meet the demands. Simulation results confirm the system's robust performance. The HESS effectively maintains voltage stability, even under the most challenging conditions. Additionally, its torque response is exceptionally robust, with negligible steady-state torque ripple and fast transient response times. The system also handles speed reversal commands efficiently, a vital feature for real-world applications. By showcasing these capabilities, the paper lays the groundwork for a more sustainable and efficient future for LEVs, suggesting pathways for scalable and advanced electric mobility solutions.
Adsorption of ammonium, nitrate, and phosphate on hydrochars and biochars
(MDPI, 2024) Trazzi, Paulo Andre; Vashishtha, Mayank; Najser, Jan; Schmalenberger, Achim; Kannuchamy, Vasanth Kumar; Leahy, James J.; Kwapiński, Witold
Biochar (BC) and hydrochar (HC) have attracted considerable attention owing to their versatile characteristics and proven effectiveness in diverse technical fields. Solid BC is generated as a result of the dry carbonisation process of pyrolysis, in contrast to the slurry HC, which is produced during the hydrothermal carbonisation process. In this study, we evaluated the adsorption potential of two hydrochar samples (HCs) and three biochar samples (BCs) produced from sugar cane bagasse. The adsorption capacity of these samples was tested for ammonium, nitrate, and phosphate ions under various conditions. The BCs and HCs were subjected to characterisation using a CHNS/O analyser, the zeta potential, and Fourier transform infrared (FTIR). Elevating the pyrolysis temperature of the biochar resulted in changes in the fixed carbon and ash contents, while the volatile matter and H/C and O/C atomic ratios decreased. As the residence time increased, the H/C ratio and volatile matter content of the hydrochars (HCs) decreased. However, the fixed carbon content, ash content, and O/C and C/N ratios exhibited an increase. Thermodynamics, adsorption isotherms, and pH were also taken into consideration. The FTIR spectra analysis indicated that the carboxyl and ester functional groups present in both the BCs and HCs displayed reduced peak intensities subsequent to the adsorption of the three ions. While the adsorption was exothermic, we noticed that the adsorption capacity increased with temperature. The results indicate that sorption was homogenous across all binding sites, as evidenced by the optimal fit to the Langmuir isotherm. The research findings indicate that the adsorption capacity of various BC and HC adsorbents is significantly influenced by the surface area of the adsorbents in the case of nitrate and phosphate, but in the case of ammonia, adsorption is dictated by the functional polar groups present on the adsorbent surface.
Optimizing grid-connected PV systems with novel super-twisting sliding mode controllers for real-time power management
(Springer Nature, 2024) Mohapatra, Bhabasis; Sahu, Binod Kumar; Pati, Swagat; Bajaj, Mohit; Blažek, Vojtěch; Prokop, Lukáš; Mišák, Stanislav
Over the past years, the use of renewable energy sources (RESs) has grown significantly as a means of providing clean energy to counteract the devastating effects of climate change. Reducing energy costs and pollution have been the primary causes of the rise in solar photovoltaic (PV) system integrations with the grid in recent years. A load that is locally connected to a GCPV requires both active and reactive power control. In order to control both active and reactive power, MAs and advanced controllers are essential. Researchers have used one of the recently developed MAs, known as the CAOA, which is based on mathematical arithmetic operators to tackle a few real-world optimization problems. Some disadvantages of CAOA include its natural tendency to converge to a local optimum and its limited capacity for exploration. By merging the PSO and CAOA methodologies, this article suggests the IAOA. To show how applicable IAOA is, its performance has been evaluated using four benchmark functions. The implementation of an IAOA-based ST-SMC for active and reactive power control is addressed in this article, which offers an innovative approach of research. In comparison to PSO-based ST-SMC and CAOA-based ST-SMC, the proposed IAOA-based ST-SMC appears to be superior, with settling time for active and reactive power control at a minimum of 0.01012 s and 0.5075 s. A real-time OPAL-RT 4510 simulator is used to validate the performance results of a 40 kW GCPV system after it has been investigated in the MATLAB environment.
Extendable high gain low current/high pulse modified quadratic–SEPIC converter for water treatment applications
(Springer Nature, 2024) Sumathy, P.; Navamani, J. Divya; Ali, Jagabar Sathik Mohamed; Lavanya, A.; Vishnuram, Pradeep; Bajaj, Mohit; Mohammadi, Shir Ahmad Dost; Prokop, Lukáš
Substantial attention has been drawn over the past few years by high step-up dc-dc converters owing to their applications in a wide range. Apart from renewable energy applications, high voltage/ high pulse converters are efficiently used in water treatment applications. The converter suggested a combination of Quadratic and SEPIC converters with a diode-capacitor cell. This topology generates high-voltage repetitive pulses with a single semiconductor switch and reduced component count. The stress across the components is less than the high-gain converters reported in the literature. The topology has an extendable feature by increasing the number of diode-capacitor cells without affecting the stress. The superiority of the high pulse generating topology is validated with a similar converter in the literature. This paper discusses the nL5 simulator results for the proposed rated topology required for water treatment. A scaled-down 50 W prototype is tested for various input voltages to generate high voltage pulse, and the analytical study is validated.
Optimizing parameters in swarm intelligence using reinforcement learning: An application of Proximal Policy Optimization to the iSOMA algorithm
(Elsevier, 2024) Klein, Lukáš; Zelinka, Ivan; Seidl, David
This paper presents a new algorithm for optimizing parameters in swarm algorithm using reinforcement learning. The algorithm, called iSOMA-RL, is based on the iSOMA algorithm, a population-based optimization algorithm that mimics the competition-cooperation behavior of creatures to find the optimal solution. By using reinforcement learning, iSOMA-RL can dynamically and continuously optimize parameters, which can play a crucial role in determining the performance of the algorithm but are often difficult to determine. The reinforcement learning technique used is the state -of -the -art Proximal Policy Optimization (PPO), which has been successful in many areas. The algorithm was compared to the original iSOMA algorithm and other algorithms from the SOMA family, showing better performance with only constant increase in computational complexity depending on number of function evaluations. Also we examine different sets of parameters to optimize and different reward functions. We also did comparison to widely used and state -of -the -art algorithms to illustrate improvement in performance over the original iSOMA algorithm.
Pyrolysis of natural rubber-cellulose composites: isoconversional kinetic analysis based on thermogravimetric data
(Springer Nature, 2024) Dobrovská, Jana; Skalková, Petra; Drozdová, Ľubomíra; Labaj, Ivan; Zlá, Simona; Dubec, Andrej; Kawuloková, Monika
Despite the current growing interest in rubber composites with natural organic fillers, there is a lack of kinetic analyses that describe the decomposition of these materials during pyrolysis. For this reason, the main objective of this study was the kinetic analysis and determination of formal kinetic parameters for the pyrolytic decomposition of NR-CEL composites with different cellulose content (0, 30, 45, and 55 phr). Thermogravimetric measurements were made at heating rates of 2, 4, 6, 8, 10, and 20 degrees C min-1 in the temperature range of 20-600 degrees C. First, Friedman and KAS model-free methods were applied. Therefore, model-based methods and the model-fitting procedure were used to find the optimal multi-step kinetic model. The proposed final model consists of two parallel processes, which are kinetically independent: A -> B -> C and D -> E -> F. For each step, a kinetic triplet was calculated: the apparent activation energy, the pre-exponential factor, and the kinetic parameters of the extended empirical Prout-Tompkins model. The master plots method was used to determine the kinetic decomposition mechanism of the individual steps. It was found that step A -> B has the shape of an nth-order model, step B -> C mainly follows the diffusion model, the mechanism of step D -> E transfers from a random scission kinetics model to an nth-order model with an increasing amount of CEL, and step E -> F obeys the chain scission mechanism.
The case study of the surface roughness influence at additively manufactured ejector and orifice plate and its impact on fluid flow
(Taylor & Francis, 2024) Šmída, Zdeněk; Výtisk, Jan; Jadlovec, Marek; Lukeš, Roman; Honus, Stanislav; Vrtek, Mojmír; Nesser, Bassel
Energy consumption and economic growth are strongly linked. In connection, great emphasis is nowadays placed on the accuracy and efficiency of machines and measuring equipment. This study compares the effect of surface roughness on airflow through a gas ejector and a centric orifice plate. Both devices are made from the same material but using two different methods of manufacturing, conventional and additive manufacturing. The study compares, experimentally and with numerical simulation, the subcritical ejector by adjusting the distance between the nozzle outlet and the mixing chamber outlet in the range of 16.9 mm, during the primary inlet pressure control from 10 to 50 kPa. The orifice is evaluated experimentally for different pressures from 0.6 to 7 bar(g). The study evaluates the level of substitutability of conventionally manufactured devices by those produced using the additive method. At design condition, the additively manufactured ejector exhibits a 12.97% lower ejection coefficient, i.e. lower effectivity. After control optimization, the decrease is reduced to 11.66%. For the additively manufactured orifice, the measured value of the pressure difference at nominal parameters deviated by 2.17%. In the case of the orifice, substitution is possible, assuming the calibration, but the orifice has a higher-pressure loss.

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