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 365 results

Overview of the use of additives in biomass torrefaction processes: Their impact on products and properties
(Elsevier, 2024) Šafář, Michal; Chen, Wei-Hsin; Raclavská, Helena; Juchelková, Dagmar; Prokopová, Nikola; Rachmadona, Nova; Khoo, Kuan Shiong
Over the past few years, considerable attention has been devoted to enhancing the torrefaction process, exploring diverse additives to improve either the process itself or the characteristics of torrefaction products. This review examines the recent advancements in torrefaction processes conducted by different research groups for these purposes. A critical evaluation involving the usage of liquid- and solid-based additives in the torrefaction process can have diverse effects depending on the specific condition implied during the torrefaction process (e.g., biomass feedstock, process conditions, and desired outcomes). Therefore, various testing and evaluation procedures should be performed to determine the optimal type and quantity of additives for a specific torrefaction application. The influence of various additives on the torrefied products of different torrefaction processes is summarized in this review. In particular, the additives are systematically categorized, and the effects of the additives on the properties of the respective torrefaction products are also discussed.
Electric vehicle charging technologies, infrastructure expansion, grid integration strategies, and their role in promoting sustainable e-mobility
(Elsevier, 2024) Singh, Arvind R.; Vishnuram, Pradeep; Alagarsamy, Sureshkumar; Bajaj, Mohit; Blažek, Vojtěch; Damaj, Issam; Rathore, Rajkumar Singh; Al-Wesabi, Fahd N.; Othman, Kamal M.
The transport sector is experiencing a notable transition towards sustainability, propelled by technological progress, innovative materials, and a dedication to environmental preservation. This study explicitly examines the incorporation of electric vehicles (EVs) into the power grid, with a particular emphasis on passenger automobiles. Our analysis emphasises the vital importance of updated transport infrastructure in decreasing greenhouse gas emissions and aiding carbon reduction efforts in electricity networks. The analysis uncovers that adopting electric vehicles offers significant advantages, including enhanced grid efficiency and decreased emissions. However, it also brings issues concerning the design and operation of power systems at both the transmission and distribution levels. Key players are crucial in tackling these difficulties to improve electric vehicle integration into the grid. The study determines the most effective ways for distributing and providing electric vehicle charging infrastructure, and investigates the efforts made to establish common standards in order to solve current challenges. This research contributes to the advancement of sustainable mobility and energy systems by conducting a thorough examination of the impact of electric vehicles on power systems and offering appropriate integration solutions.
Backward neural network (BNN) based multilevel control for enhancing the quality of an islanded RES DC microgrid under variable communication network
(Elsevier, 2024) Anum, Hira; Hashmi, Muntazim Abbas; Shahid, Muhammad Umair; Munir, Hafiz Mudassir; Irfan, Muhammad; Veerendra, A. S.; Kanan, Mohammad; Flah, Aymen
Microgrids (MGs) and energy communities have been widely implemented, leading to the participation of multiple stakeholders in distribution networks. Insufficient information infrastructure, particularly in rural distribution networks, is leading to a growing number of operational blind areas in distribution networks. An optimization challenge is addressed in multi -feeder microgrid systems to handle load sharing and voltage management by implementing a backward neural network (BNN) as a robust control approach. The control technique consists of a neural network that optimizes the control strategy to calculate the operating directions for each distributed generating point. Neural networks improve control during communication connectivity issues to ensure the computation of operational directions. Traditional control of DC microgrids is susceptible to communication link delays. The proposed BNN technique can be expanded to encompass the entire multi -feeder network for precise load distribution and voltage management. The BNN results are achieved through mathematical analysis of different load conditions and uncertain line characteristics in a radial network of a multi -feeder microgrid, demonstrating the effectiveness of the proposed approach. The proposed BNN technique is more effective than conventional control in accurately distributing the load and regulating the feeder voltage, especially during communication failure.
Multi-objective energy management in a renewable and EV-integrated microgrid using an iterative map-based self-adaptive crystal structure algorithm
(Springer Nature, 2024) Rajagopalan, Arul; Nagarajan, Karthik; Bajaj, Mohit; Uthayakumar, Sowmmiya; Prokop, Lukáš; Blažek, Vojtěch
The use of plug-in hybrid electric vehicles (PHEVs) provides a way to address energy and environmental issues. Integrating a large number of PHEVs with advanced control and storage capabilities can enhance the flexibility of the distribution grid. This study proposes an innovative energy management strategy (EMS) using an Iterative map-based self-adaptive crystal structure algorithm (SaCryStAl) specifically designed for microgrids with renewable energy sources (RESs) and PHEVs. The goal is to optimize multi-objective scheduling for a microgrid with wind turbines, micro-turbines, fuel cells, solar photovoltaic systems, and batteries to balance power and store excess energy. The aim is to minimize microgrid operating costs while considering environmental impacts. The optimization problem is framed as a multi-objective problem with nonlinear constraints, using fuzzy logic to aid decision-making. In the first scenario, the microgrid is optimized with all RESs installed within predetermined boundaries, in addition to grid connection. In the second scenario, the microgrid operates with a wind turbine at rated power. The third case study involves integrating plug-in hybrid electric vehicles (PHEVs) into the microgrid in three charging modes: coordinated, smart, and uncoordinated, utilizing standard and rated RES power. The SaCryStAl algorithm showed superior performance in operation cost, emissions, and execution time compared to traditional CryStAl and other recent optimization methods. The proposed SaCryStAl algorithm achieved optimal solutions in the first scenario for cost and emissions at 177.29 ct and 469.92 kg, respectively, within a reasonable time frame. In the second scenario, it yielded optimal cost and emissions values of 112.02 ct and 196.15 kg, respectively. Lastly, in the third scenario, the SaCryStAl algorithm achieves optimal cost values of 319.9301 ct, 160.9827 ct and 128.2815 ct for uncoordinated charging, coordinated charging and smart charging modes respectively. Optimization results reveal that the proposed SaCryStAl outperformed other evolutionary optimization algorithms, such as differential evolution, CryStAl, Grey Wolf Optimizer, particle swarm optimization, and genetic algorithm, as confirmed through test cases.
Improved robust model predictive control for PMSM using backstepping control and incorporating integral action with experimental validation
(Elsevier, 2024) Djouadi, Hafidh; Ouari, Kamel; Belkhier, Youcef; Lehouche, Hocine; Bajaj, Mohit; Blažek, Vojtěch
The DC motor is being rapidly replaced in the industry by the permanent magnet synchronous motor (PMSM), which has a number of benefits over it. Nonlinear equations are used to describe the dynamics of the PMSM. It is susceptible to unidentified external disturbances (load), and its properties change over time. These constraints make it more difficult to exercise control. To overcome the non-linearities and the aforementioned shortcomings, non-linear controls are necessary. This manuscript refers to the development of a sturdy high-caliber position tracking controller that incorporates integral action for PMSM. A predictive control law for the speed loop is established, combined with the backstepping control law for the inner loop. The overall strategy can be divided into two distinct elements. The initial stage involves the derivation of a reference electromagnetic torque computed through the generalized non-linear predictive control method. Subsequently, the controller law is formulated utilizing the robust backstepping control technique. One of the cardinal merits of this method lies in its exemption from the requirement of measuring and observing the external disturbances and parametric uncertainties. The efficacy of this cutting-edge control approach is rigorously evaluated in simulation with MATLAB/Simulink environment and experimentally using OPAL-RT, under diverse operating conditions. The findings demonstrate steadfast resilience amidst external disruptions and adjustments to parameters, while ensuring swift convergence, a testament to its robustness and reliability.
On mechanism of the synthesis of boron-doped graphitic carbon nitride
(Elsevier, 2024) Cvejn, Daniel; Starukh, Halyna; Koštejn, Martin; Peikertová, Pavlína; Praus, Petr
B-doped graphitic carbon nitrides (B-CNs) represent a promising class of materials that are potentially useful in a variety of applications. Their properties depend on the nature of the B-doping, which in turn is highly dependent on the particular chemical mechanism of B-doping formation. With this in mind, we present here the study of Bdoping achieved by the co-calcination of CN-precursor (cyanoguanidine) and B-dopant (boric acid). In this study, the structural theory of the B-CN materials produced from different ratios of CN precursor and Bdopant was derived. Our proposed structure is supported by elemental analysis, X-ray diffraction, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and nuclear magnetic resonance. Based on our results, heptazine carbon replacing tetravalent B- species near the =N+=C--N- structural unit is the dominant pattern of B doping in our co-calcined materials. The identification of the nature of the B-doping allowed us to infer the mechanism of its formation in the chemical reactions taking place during calcination.
Improving load frequency controller tuning with rat swarm optimization and porpoising feature detection for enhanced power system stability
(Springer Nature, 2024) Gopi, Pasala; Alluraiah, N. Chinna; Kumar, Pujari Harish; Bajaj, Mohit; Blažek, Vojtěch; Prokop, Lukáš
Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as "Porpoising". This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.
Iron-modified Cu/γ-alumina catalyst for the selective hydrogenolysis of glycerol
(Elsevier, 2024) Skuhrovcová, Lenka; Kolena, Jiří; Frolich, Karel; Kocík, Jaroslav; Mück, Jáchym; Gholami, Zahra
This study introduces a novel Cu-based catalyst for the selective hydrogenolysis of glycerol to 1,2-propanediol, synthesized by impregnating mesoporous gamma-alumina with Cu and Fe. Characterization was performed using various analytical methods, and tests were conducted in a tubular continuous reactor under specific conditions. Iron was found to have multiple modifying effects, influencing the modification of Cu clusters on the catalyst surface and the radial Cu concentration profile inside the particles. A low Fe/Cu ratio resulted in an almost eggshell Cu profile, whereas higher Fe levels produced a more uniform distribution. Interestingly, minor Fe additions led to larger Cu clusters, while higher amounts resulted in smaller clusters and decreased glycerol conversion. The effect of Fe on Cu clusters size, acid sites concentration, and Cu radial profile, as well as the influence of these parameters on the glycerol conversion and selectivity towards 1,2-PD are discussed in this study.
Electric vehicle charging by use of renewable energy technologies: A comprehensive and updated review
(Elsevier, 2024) Nazari, Mohammad Alhuyi; Blažek, Vojtěch; Prokop, Lukáš; Mišák, Stanislav; Prabaharan, Natarajan
The majority of the vehicles in the world consuming fossil fuels that causes emissions of harmful greenhouse gases. In order to mitigate the emissions regarding the transport sector, Electric Vehicles (EVs) have attracted attentions. One of the main concerns in the development of EVs is supply of required power for the charging stations. Renewable energy systems would be clean and attractive options for supply of required power of charging stations. In recent years, several studies have investigated applications of renewable energy systems for charging stations of EV and analyzed different aspects of these technologies. This article reviews the research works on the design, optimization and performance investigation of charging stations coupled with renewable energy systems. Studies on EV charging systems powered by stand-alone or hybrid renewable energy systems are considered in the present article. According to the reviewed works, significant potential of renewable energy systems for supply of charging stations can be concluded. Different factors such as the applied technology and components, meteorological data of the installation site and operating condition influence the performance of these systems. Furthermore, it can be concluded that control design system can influence various aspects of EV charging technologies powered by renewable energy systems such as share of renewables in the grid -connected configurations and performance reliability. Challenges and opportunities associated with the development of these systems are provided in the current works and some recommendations are highlighted for the forthcoming studies and projects.
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.

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