MATLAB Model Research Articles

Sulfate-driven microbial collaboration for synergistic remediation of chloroethene-heavy metal pollution

The treatment of heavy metal(loid) (HM) composite pollution has long posed a challenge for the bioremediation of organohalide-contaminated sites. Given the prevalent cohabitation of sulfate-reducing bacteria (SRB) with organohalide-respiring bacteria (OHRB), we proposed a sulfate-amendment strategy to achieve synergistic remediation of trichloroethene and diverse HMs [50μM of As(III), Ni(II), Cu(II), Pb(II)]. Correspondingly, 50–75 μM sulfate was introduced to HM inhibitory batches to investigate the enhancement effect of sulfate amendment on bio-dechlorination. Dechlorination kinetics and MATLAB modeling indicated that sulfate amendment comprehensively improved the reductive dechlorination performance in the presence of As(III), Ni(II), Pb(II) and mixed HMs, while no enhancement was observed under Cu(II) exposure. Additionally, sulfate introduction effectively accelerated the detoxification of Ni(II), Pb(II), Cu(II), and As(III), achieving removal efficiencies of 76.87 %, 64.01 %, 86.37 %, and 95.50 % within the first three days, respectively. Meanwhile, propionate dynamics and acetogenesis indicated enhanced carbon source and e-donor supply. 16S rRNA gene sequencing and metagenomic analysis results demonstrated that HM sequestration was accomplished jointly by SRB and HM-resistant bacteria via extracellular precipitation (metal sulfide) and intracellular sequestration, while their contribution depended on the specific coexisting HM species present. This study highlights the critical role of sulfate in the concurrent bioremediation of HM-organohalide composite contamination and provides insights for developing a cost-effective in-situ bioremediation strategy.

Optimizing nanosatellites Earth observation missions: Orbit design for global coverage and pre-launch cloud detection dataset preparation

Optimizing Earth observation nanosatellite missions requires careful orbit selection to ensure global coverage and high image quality. The main challenge is to define an optimal orbit that maximizes image quality while achieving comprehensive Earth coverage. To address this, an orbit definition model that accounts for the J2 perturbation was developed, evaluating key parameters such as swath width, spatial resolution, time resolution, and tilt angle. The model was applied within the context of a 3U university nanosatellite equipped with the Gecko imager. The analysis identified 551 km as the most suitable altitude for achieving comprehensive coverage. At this altitude, the swath width is 88.16 km, and the distance between adjacent ground tracks is 86.33 km, satisfying the condition for global coverage with nadir pointing. The revisit time is 31 days, ensuring regular coverage of the Earth's surface. Results were validated through Systems Tool Kit simulations, showing minimal differences compared to the MATLAB model, underscoring the model's accuracy and reliability. To further optimize the mission's effectiveness and bandwidth utilization, images captured in this orbit can be processed onboard to ensure that only relevant and useful data are transmitted to the ground station. To support this, a dataset of 900 images was generated at the optimal orbit altitude, specifically tailored for a cloud detection application using the Gecko imager. The findings validate the effectiveness of the proposed orbit design model and demonstrate the feasibility of pre-launch dataset preparation, paving the way for future onboard implementations and in-orbit real-time applications.

Analytical modeling of III-V heterojunction source-all-around vertical tunnel FET and its inverter circuit application

Abstract This paper presents a comprehensive analytical modeling framework for the III-V heterojunction source-all-around vertical tunnel field-effect transistor (SAA V-TFET). Using Kane's model, our approach involves solving Poisson's equations to obtain a continuous surface potential profile, followed by the derivation of drain current. These models demonstrate excellent accuracy across all operating regions, precisely predicting the potential profile, output, and transfer characteristics of SAA V-TFETs. We implemented the models in MATLAB and validated them against Sentaurus TCAD simulations. Furthermore, we present a comprehensive performance analysis of SAA V-TFET-based digital inverters.

MIWO based MPPT of PV system for induction motor driven water pumping system

Renewable energy source-based Water Pumping Systems (WPSs) have gained popularity for drinking, agricultural, and industrial purposes. Locally situated standalone Photovoltaic (PV) powered WPS can provide a viable water supply solution, especially with induction motors (IM) due to their advantages over other motor types. However, solar PV energy output is greatly influenced by weather conditions, necessitating energy storage systems like batteries, which increase costs and require maintenance. This research proposes an efficient energy management system for a PV-powered IM-driven WPS that does not rely on batteries. The system handles Partial Shading Conditions (PSC) effectively, thanks to a sensorless speed controller combining a Modified Invasive Weed Optimization (MIWO) mechanism with the Perturb and Observe (P&O) method. This controller uses the inverter as an MPPT circuit, eliminating the need for a distinct converter to follow the MPP. The hybrid P&O-MIWO method's outcomes are compared with those of P&O hybridization with GA, PSO, and GWO to assess efficiency under various PSCs. TS-Fuzzy controllers are employed for voltage control at the DC-link and motor speed. The proposed system is analyzed across different scenarios and validated using a Simulink model in MATLAB. Results indicate that the hybrid P&O-MIWO mechanism enhances energy generation from the PV unit without relying on energy storage devices, providing a cost-effective solution for PV-based WPS implementation.

Integrating canonical correlation analysis with machine learning for power quality disturbance classification

Abstract Recently, the rapid growth of Renewable Energy Resources (RER) in power generation has resulted in the frequent occurrence of Power Quality Disturbances (PQDs) within the power system. The timely and accurate detection of these PQDs is critical for maintaining good power quality while integrating RER into hybrid power systems to make them more robust and stable. In this paper, a multi-view dimensionality reduction approach based on Canonical Correlation Analysis (CCA) is proposed to differentiate different types of PQDs. Here, a dataset of 29 types of PQDs which include nine single types and twenty multiple types of PQDs have been generated using their mathematical model in MATLAB for experimentation. CCA being a multi-view dimensionality reduction technique maximizes the correlation between two different views of the data. Here two cases of datasets have been considered for further exploration, Case 1: PQDs without noise and with 20 dB noise, Case 2: PQDs with 20 dB and 30 dB noise. Furthermore, to test the efficacy of CCA in both cases, the extracted features have been tested using four different classifiers, i.e., K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF). The performance of each of the classifiers has been tested on five different performance metrics such as precision, recall, F1 score, hamming loss, and accuracy, and the results show that the proposed technique of multi-view dimensionality reduction is capable of classifying the PQDs with two different views at a time.

Phase Field Coupled Finite Deformation Plasticity Formulation of Ductile Fracture With Nonlinear Kinematic Hardening and Modified Energy Release Function

ABSTRACTA ductile damage theory is presented by coupling the covariant formulation of finite deformation plasticity with the phase field modeling of fracture, including kinematic hardening for the ductile response of the materials. A phase field coupled nonlinear kinematic hardening equation is proposed in the reference configuration having equivalent representation through the Lie derivative of the kinematic hardening tensor by push‐forward operation in the spatial configuration, thus ensuring the satisfaction of frame invariance. To capture the correct physical response of the material by the phase field evolution equation, the fracture driving function, that is, the difference between the sum of elastic and plastic energies and threshold energy, after the damage initiation is modified by an energy release controlling function, which is an empirical relation of equivalent plastic strain. In defining the energy release controlling function, well‐defined points with physical significance in the experimental load versus displacement curve are used. To simulate the response of the material in relatively large time steps, a modified staggered scheme is presented, evaluating the fracture driving and energy release controlling functions from the previous converged step and using the updated phase field variable in the weak form of the momentum balance equation. To quantify different material parameters from available experimental results in the literature, the developed phase field coupled elasto‐plastic model uses a neural network optimization procedure consisting of neural network training together with optimization in MATLAB and finite element model evaluation in Abaqus user element subroutine UEL. Model capabilities are demonstrated by simulating the crack propagation in complex 3D geometries such as the second and third Sandia Fracture Challenges.

Hydrate formation and its influence on natural gas pipeline: Simulation study

Natural gas transportation is plagued with the twin problem of hydrate and corrosion that occurs when a hydrate prone gas is conveyed in such a manner that the pipeline operating conditions fall within hydrate formation region of the hydrate phase envelop. This study simultaneously studied this twin problem, establishing their interdependent using gas sample from Niger Delta that was meticulously simulated and analysed for hydrate formation possibilities with the aid of Unism software. CO2 corrosion was simulated using NORSOK M-506 standard model in matlab. Major factors considered are the relationship between corrosion rate and temperature, corrosion rate and PH, corrosion-temperature relationship for varying CO2 mole percent, and PH values. The result from this study established that both type I and type II hydrates could form at the operating conditions of 5OC and 60 bar. Rate of corrosion decreases and increases with increase in PH and temperature respectively to a certain temperature of approximately 78 OC, then a dip in rate of corrosion. Corrosion-temperature relationship for varying PH and CO2 mole percent shows a decrease in corrosion rate with an in increase in PH, and an increase with increase in CO2 mole percent, with a rise as high as 5,7 mm/year at a 3 mole percent. This value and trend portray a bad omen for the affected pipeline. This study recommends that natural gas to be transported by pipeline should be sweetened and processed to remove H2S, CO2 and mercaptans if present and also to satisfy maximum dew point specification.

Improving current-matching in textured perovskite/silicon tandem solar cells via a thickness control strategy

This study presents an analysis of a two-terminal tandem solar cell that integrates metal-doped, lead-free double Cs2AgBi0.75Sb0.25Br6 perovskite with silicon to enhance overall energy conversion efficiency. This study explores how the thicknesses of the top and bottom sub-cells affect current-matching in two-terminal tandem perovskite/silicon solar cells with two separate planar and textured configurations. Using numerical modeling in MATLAB, and considering dominant recombination effects, we calculated the performance parameters of the device. We investigated the optical and electrical properties of textured tandem structures, focusing on current- matching and the influence of layer thickness on device performance. Given the complexity, time, and expense involved in constructing tandem solar cells, being able to analytically determine the thickness at which current-matching occurs can be highly advantageous. This approach offers the benefit of providing a precise analytical relationship for this purpose. Our findings demonstrate that increasing the top cell thickness enhances current density and power conversion efficiency, but at the cost of the bottom cell’s efficiency due to increased light absorption. Moreover, we discovered a nearly linear behavior between the thickness of the top and bottom cells for achieving current-matching. The study highlights the critical balance required to optimize layer thicknesses, thereby improving the design and performance of tandem solar cells. These insights are significant as they pave the way for more efficient and cost-effective tandem solar cell designs in the future, potentially accelerating the adoption of advanced photovoltaic technologies. The results show good agreement with experimental data, validating our model.

Dynamics of tracked vehicles during nonuniform turning on level terrain and on slopes

This paper presents a detailed kinematic and dynamic model of nonuniform skid steering for tracked vehicles on level terrain and uniform skid steering slopes. The objective is to find the required forces applied on both tracks to achieve the desired turning, aiding in determining the needed engine power for effective turning operation. The vehicle kinematics during turning is presented, followed by a complete dynamic analysis that considers the effect of centrifugal and inertia forces, as well as adhesion with the ground. The dynamic analysis of turning on slopes is developed, where the cases of turning while moving uphill and downhill are considered. Moreover, simulation analysis using MATLAB model is conducted to investigate the main turning characteristics on both level terrain and slopes. The model can accurately predict the required forces on both tracks for effective turning, and can aid in the design of more efficient tracked vehicles. Generally, the findings of this study can inform the design of more efficient tracked vehicles by providing insights into the needed driving forces and the required power to achieve the desired radius of turning at a specific vehicle speed.

Optimizing COP by RSM and MATLAB model of mini refrigerator based on thermoelectric units driven by solar photovoltaic

AbstractEnergy scarcity in the world and the pollutants resulting from excessive use of conventional energy aroused the need for sustainable alternatives that are environment friendly. A multi-use thermoelectric refrigerator powered by solar energy to obtain the lowest consumption with the highest efficiency. The designed refrigerator is based on the Peltier effect using Peltier units where a temperature difference is created between the junctions by applying a voltage difference across the junction. This study investigates the performance of a refrigerator cooling system powered by a photovoltaic (PV) system. The research aims to assess the efficiency, effectiveness, and feasibility of utilizing solar energy to drive refrigeration, particularly in off-grid or environmentally conscious applications. Through a comprehensive experimental setup and data analysis, the study examines energy consumption, cooling efficiency, and overall system performance under varying conditions. The findings contribute valuable insights into the potential of PV-powered refrigerators as sustainable cooling solutions. It relies on a control unit that measures the resulting temperature to determine the appropriate connection mode to give the highest cooling efficiency. The average solar radiation when operating for 8 h, for the different seasons of the year was 149.5, 67.5, 119.3, and 118.3 w/m2 in summer, winter, spring, and fall, respectively. The average cooling energy consumption was 107.25, 137.04, 107, and 138.08 w for temperatures (20 ± 1, 15 ± 1, 20 ± 2, and 15 ± 2) °C respectively that proof solar radiation is sufficient to produce energy for the summer of cooling temperatures up to 15 °C, while in the spring and fall it is sufficient to 20 °C. The Fast not Eco mode is the least energy consuming and the fastest cooling, it can be used for rapid cooling at a short time less than an hour. The best mode in the case of continuous operation is the case of as next Eco mode cooling temperature of 20 ± 0.1 °C. The MATLAB Simulink model was developed to reduce the design cycle and facilitate the integration of solar photovoltaic with the TEC. The optimal operating point is identified through simulation and validated through experimental analysis, the optimal COP was 71.089% by Response surface methodology (RSM).

Parametric correction in the control system of the electric propulsion of autonomous underwater vehicles affected by random inputs

The paper deals with the problem of controlling a DC propulsion motor of an autonomous underwater vehicle using a bidirectional non-isolated DC-DC converter. An automatic speed control system with a parametric controller was developed in the Matlab / Simulink package. To reduce energy conversion stages, dc-dc converters are often used to control dc motors AUV. The result of the work is an adaptive control system for the speed of the AUV propeller, which would provide high accuracy for a wide range of speeds and at the same time limit the maximum current and voltage at the armature. The indicators of the quality of performance in various modes of operation were determined, maps of the controller settings were compiled, and parametric correction was introduced. The operation of the system is analyzed and drawbacks are eliminated, such as voltage surges when switching from one speed to another, a decrease in overshoot and settling time. The performance of the system is analyzed under the conditions of random inputs from the propeller. The description of the laboratory stand for the study of the control system is given. A description of the laboratory study of the operation of the "DC converter—engine" system under conditions of random fluctuations in the moments on the motor shaft is given. It is shown that the proposed system has shown itself well under laboratory conditions and the experimental results are consistent with modeling in Matlab / Simulink.

Photocatalytic antibiotic degradation in coated open microchannels by applying 2D and 3D flow modeling with kinetics

The accumulation of active pharmaceutical ingredients in the aqueous environment is a serious problem that will become even more concerning in the future. In this work, the photocatalytic degradation of ciprofloxacin (CIP) in aqueous solution was assessed over P25-TiO2 coated open microchannels with gravity-driven flow under UV-A irradiation. The deposition of different amounts of TiO2 in the microchannels was carried out via a facile, self-developed procedure. The degradation kinetics of ciprofloxacin was described via the Langmuir-Hinshelwood mechanism. Since the flow characteristics in the microchannel had influence on the concentration distribution of CIP in the microchannel, the coupled momentum and mass conservation law was solved numerically in MATLAB 2023a (2D case) as well as in ANYS Fluent 2023 R1 (2D and 3D cases). Although the implemented 2D model in MATLAB 2023a allowed the preliminary estimation of the selected kinetic parameters, namely adsorption equilibrium constant and specific Langmuir-Hinshelwood rate constant, the sensitivity of the model was not satisfactory which was attributed to the empirical correlations used for the estimation of the external mass transfer coefficient. The 2D and 3D models in ANSYS Fluent 2023 R1 predicted efficiently the outlet concentration of ciprofloxacin for different inlet CIP concentrations and liquid phase flow rates. Therefore, the as developed 2D and 3D models in ANSYS Fluent 2023 R1 can be used for the design of reactors containing coated microchannels with gravity-driven flow for photocatalytic degradation of active pharmaceutical ingredients.

A novel multi-objective optimization scheme of electric turbo compressor system in hydrogen fuel cell for reducing energy consumption and axial thrust

Electric turbo compressor (ETC) can recover the exhaust energy and reduce the motor power consumption, which is the future development of the air management system for fuel cell. However, the large imbalances of axial thrust and energy between the compressor and turbine leads to low reliability and efficiency of ETC. In this study, a multi-objective optimization scheme was proposed to explore the lowest ETC axial thrust and electric power consumption. First, the coupled model including compressor, turbine and axial thrust sub-models were established in MATLAB. To verify the model, computational fluid dynamics(CFD) model were established in ANSYS CFX and experimental tests were carried out. The electric power differences between the MATLAB model and experiment is within 4.36 % and the axial thrust deviations between the MATLAB and CFD model is within 5.46 %.Then, eight geometric parameters of compressor and turbine rotors are selected as independent optimization variables. NSGA-ΙΙ multi-objective optimization algorithm was adopted to search for low axial thrust and power consumption solutions. Finally, the optimization results show that the efficiency of the compressor and turbine is increased by 6.39 % and 2.75 % at design point, respectively. The electric power consumed by the motor is reduced by 7.80 % and the axial thrust of the ETC is reduced by 18.83 %.

PDE models for vegetation biomass and autotoxicity

Numerical techniques are widely used to simulate population dynamics in space. In vegetation dynamics, these techniques are very useful to investigate how plants grow, compete for resources, and react to environmental factors within the ecosystem. Plant–soil feedback (PSF) refers to the process where plants or a community alter the biotic and abiotic characteristics of soil that affects the growth of plants or community subsequently growing in that soil. During the last three decades, PSF has been recognized as an important driver for the emergence of vegetation patterns. The importance of studying such vegetation patterns is that they provide an insight into potential ecological changes and illustrate the flexibility and resilience of an ecosystem. Despite the fact that water depletion was once thought to be a major factor in the development of vegetation patterns the existence of patterns in ecosystems without water limitations serves as evidence that this is not the case. In this study, we examine how negative plant–soil feedback contributes to the dynamics of plant biomass. We provide a comparison of different reaction–diffusion PDE models explaining the dynamics of plant biomass in the presence of autotoxicity produced by litter decomposition. We introduce different growth terms, including logistic and exponential, along with additional factors such as extra mortality and inhibitor terms, and develop six distinct models to investigate their individual and combined effects on biomass toxicity distribution. By applying appropriate numerical techniques, we solve the proposed reaction–diffusion PDE models in MATLAB to predict the impact of soil toxicity on plant biomass.

A Novel Method for Estimating the Thermal Performance of Multi-Block Wall Systems Using Thermal Impedance Z-Value under Transient Uncontrolled Heat Transfer Conditions

Climate change is one of the biggest challenges today. An increasing population accelerates the construction of concrete houses and the use of air conditioners, thereby leading to an increase in energy consumption. When the walls of buildings are well-designed and insulated, energy consumption can be reduced. Therefore, it is important to measure the thermal performance of wall systems accurately. The existing traditional methods of measuring R- and U-values provide acceptable solutions for steady-state controlled, uncontrolled or transient state-controlled conditions. However, a need to develop a novel approach for transient state-uncontrolled realistic conditions has been identified. The present study involves both experimental and numerical investigations. An in situ model room with dimensions of 1.60 m × 1.73 m × 1.50 m was built for the experimental work, and a series of experiments were conducted. For numerical work, two models using Ansys Fluent 2021/2022 and MATLAB Simulink 2021/2022 were developed. The real-time experimental data were fed into numerical models to predict the thermal behavior of the wall system. The results include the evaluation of a concept called ‘Time-Lag’ for all three models. ‘Time-Lag’ is the time taken for the heat energy to flow across the wall system. The Time-Lag for the experimental model was 8 h 45 min, while for MATLAB and Ansys models, it was 8 h 22 min. (average) and 7 h 30 min, respectively. Minor variations validate the accuracy of the numerical models. Further, a novel method using a new parameter in building systems called ‘thermal impedance Z-value’ was developed to estimate the real-time thermal performance of walls using MATLAB Simulink. The Z-value measures the ability of a wall system to resist the flow of heat (thermal resistance, R-value) combined with its ability to store heat energy (thermal capacitance, Cth-value). It is evaluated for steady-state and dynamic (transient) systems. For the steady-state system, the Z-values on the outer and inner walls were 18.2683 K/W and 18.6761 K/W, respectively with a minor difference of 0.4078 K/W at the end of 72 h. For the dynamic system, the Z-value did not reach a constant value and fluctuated in a particular pattern during 24 h of the solar cycle with average values of 3.2969 K/W on the outer and 1.2886 K/W on the inner walls at the end of 72 h, thus presenting more accurate and realistic thermal performance results of a wall system.

Comparative study on the impact of different E-J relations on the performance of resistive superconducting fault current limiters under high and low impedance faults in cryo-electric aircraft

To achieve the goal of zero emission in aviation, it is critical to advance electric aircraft technologies, especially in short to medium range flights. Superconducting fault current limiters (SFCLs) have shown promising potential in electric aircraft system as a protection solution to limit the peak of fault current. Many research works focused on the SFCL performance under low impedance faults, where the fault current is much higher than the nominal current and the SFCL will transit to normal (metal) state quickly. However, there are limited reports on investigating the SFCL reacting to high impedance faults for electric aircraft system, where the SFCL does not abruptly transit to normal state. In this paper, we built an electric-thermal coupled model in MATLAB which simulates the behaviour of a resistive type SFCL both under low and high impedance faults. We investigated three mathematical relations of local electric field E and local current density J representing the transition from superconducting state to normal state, both under high and low impedance fault. The three mathematical relations are classic E-J power-law, modified E-J power-law and two- stage E-J power law. The electric-thermal model of the SFCL incorporating all these three types of mathematical relations, respectively, have been used to calculate the SFCL responses under high and low impedance faults, and compared with each other, as well as testing results. The limited fault current, voltage drop, resistance and temperature variations in the SFCL are observed and analysed. The results have shown that the proposed SFCL model is able to accurately characterise a resistive type SFCL under both high impedance and low impedance fault.

Dynamic spectroscopic and optical characterization and modeling of bovine serum albumin corona during interaction with N-hydroxysulfo-succinimide-covalently functionalized gold nanourchins.

In this study, bovine serum albumin (BSA) is used as a globular protein model to examine the conformational changes that occur during the interaction of BSA with N-hydroxysulfo-succinimide (sodium salt)-functionalized gold nanourchins (GNUs), for which dynamic spectroscopic techniques are employed. The results showed that the absorbance of phosphate-buffered saline-BSA at 278 nm decreased when a GNU was added to the solution due to adsorption, and it decreased further when the GNU was increased. The intensity and width of the peak of local surface plasmon resonance increased, indicating the effect of corona formation. Dynamic UV-vis spectroscopy and scattering revealed a nonlinear behavior of BSA-GNU interaction. The bioplasmonic solution resulted in higher transmission and scattering than the BSA solution. Fourier transform-near-infrared spectra exhibited several bands due to overtones and combinations of the amide group and different proportions of α-helix and β-sheet components in BSA before and after the addition of the GNU. Time-resolved fluorescence spectroscopy demonstrated an initial increase in blueshifted emission, followed by a redshifted quenching of two major peaks of Tyr and tryptophan (Trp). The binding and dissociation constants were determined as Kb = 2.17 × 1010 M-1 and Kd = 4.6 × 10-11, respectively, using the Stern-Volmer relation. Both the dynamic CMOS-based imaging and the cadmium sulfide sensors demonstrated a nonlinear response of bioplasmonic solution. By increasing the GNU, the resistance of the solution decreased in the order of A > S1 > S3, where S3 exhibited the highest initial transmission with a longer desorption time. MATLAB modeling showed 80% surface coverage by the protein in 15 s at 0.05M, equivalent to a thickness of 1.7 nm, which was in agreement with the value determined by using the Stokes-Einstein relation.

Climate-adaptive battery solutions for renewable microgrids: A case study in Indian coastal and inland regions

The utilization of renewable energy has the potential to alleviate global warming, reduce carbon emissions in the environment, and offer sustainable energy solutions to remote regions. Presently, 13 % of the worldwide population resides in isolated inland and coastal areas where electricity remains inaccessible. Consequently, implementing microgrids powered by renewable energy sources becomes essential to enhance electricity accessibility in these remote locations. This study aims to identify efficient and cost-effective renewable energy technologies suitable for deployment inland and coastal areas. The techno-economic feasibility of renewable energy systems is being evaluated in two distinct locations: Yadavole (inland) and Uppada (coastal) villages in the Indian state of Andhra Pradesh. The energy analysis encompasses various sources, including photovoltaic, diesel generators, wind turbines, flywheels, and batteries (Li-ion and lead-acid). The HOMER software conducts all necessary modeling and simulations for economic analysis and optimal system sizing. According to the simulation results, the most viable microgrid configurations for the inland region, Yadavole, are photovoltaic/diesel and generator/Li-ion. In contrast, for the coastal region, Uppada, photovoltaic/diesel, and generator/lead-acid configurations prove to be the most promising configurations. Moreover, a MATLAB model of the proposed system is created to analyze energy quality. Given the superior performance of Li-ion batteries in elevated temperatures typically found inland, this study recommends a diversified range of battery solutions. Specifically, Li-ion batteries are recommended for inland areas, while lead-acid batteries are recommended for coastal regions. This approach aims to efficiently store renewable power by the specific climatic conditions of each area. It is crucial to systematically analyze region-specific renewable energy technologies to provide valuable insight to stakeholders involved in investment and energy policy decisions.

Analysis and improvement of power quality in the onboard electrical power systems within a self-propelled floating crane

This research addresses electromagnetic compatibility and power quality (EMC and PQ) challenges in shipboard electric power systems (SEPS) with dynamic positioning (DP) capabilities, focusing on the self-propelled floating crane (SPFC) “EXPERT 3.” Our goal is to enhance methodologies for evaluating power quality indicators (PQI) related to voltage and current waveform distortions, specifically in converter-based propulsion complexes (CBPCs) featuring variable-frequency regulated asynchronous drives (VFDs). We investigate harmonic current and voltage distortions, reactive power generation, and power factor (PF) in SEPS “EXPERT 3″ during the operation of VFDs with conventional semiconductor power converters (SPCs). A refined MATLAB model considers equipment and cable network parameters, validating distortion indicators at ship synchronous generators (SGs). PQI compliance with international maritime standards is verified at the point of common coupling (PCC) for various VFD configurations with pulse width modulated (PWM) SPCs and filter-compensating devices (FCDs). We propose an improved controlled FCD (CFCD) incorporating a resonance filter (RF) and a controllable reactor compensator (CRC). CFCD efficiency in various VFD configurations is experimentally validated. We analyze harmonic distortions of voltage and current, including high-frequency (HF) commutations in VFDs with input thyristor-based rectifiers (TBRs), considering parasitic ”phase-hull“ capacitances of cable line segments (CLS). Our study examines harmonics in CBPC-based SEPS in two sub-frequency ranges: low-frequency (LF) − 0 to 2 kHz and high-frequency (HF) − 2 kHz to 500 kHz.© 2017 Elsevier Inc. All rights reserved.

FOMCON Toolbox-Based Direct Approximation of Fractional Order Systems Using Gaze Cues Learning-Based Grey Wolf Optimizer

This study discusses a new method for the fractional-order system reduction. It offers an adaptable framework for approximating various fractional-order systems (FOSs), including commensurate and non-commensurate. The fractional-order modeling and control (FOMCON) toolbox in MATLAB and the gaze cues learning-based grey wolf optimizer (GGWO) technique form the basis of the recommended method. The fundamental advantage of the offered method is that it does not need intermediate steps, a mathematical substitution, or an operator-based approximation for the order reduction of a commensurate and non-commensurate FOS. The cost function is set up so that the sum of the integral squared differences in step responses and the root mean squared differences in Bode magnitude plots between the original FOS and the reduced models is as tiny as possible. Two case studies support the suggested method. The simulation results show that the reduced approximations constructed using the methodology under consideration have step and Bode responses more in line with the actual FOS. The effectiveness of the advocated strategy is further shown by contrasting several performance metrics with some of the contemporary approaches disseminated in academic journals.