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Abstract The evolutionary algorithm of invasive weed optimization algorithm popularly known as the IWO has been used in this paper, to solve the unit commitment (UC) problem. This integer coded algorithm is based on the colonizing behavior of weed plants and has been developed to minimize the total generation cost over a scheduled time period while adhering to several constraints such as generation limits, meeting load demand, spinning reserves and minimum up and down time. The minimum up/down time constraints have been coded in a direct manner without using the penalty function method. The proposed algorithm was tested and validated using 10 units and 24 h system. The most important merit of the proposed methodology is high accuracy and good convergence speed as it is a derivative free algorithm. The simulation results of the proposed algorithm have been compared with the results of other tested algorithms for UC such as shuffled frog leaping, particle swarm optimization, genetic algorithm and Lagrangian relaxation and bacterial foraging algorithm.

The present work is dedicated to the steady-state analysis of electronic load controller (ELC) for three phase alternator. In an alternator employed in micro-hydro applications, the voltage is controlled by Automatic Voltage Controller (AVR) so here electronic load controller conforms itself to the control of frequency. It does so by diverting the difference between the rated power and consumer demand to the dump/ballast load for dissipation. The paper presents the mathematical and simulink model of Electronic Load Controller for three phase alternator. The developed mathematical model is first checked for its stability by employing Routh-Hurwitz criterion and then designed in MATLAB/Simulink which is then analyzed for its behavior under steady-state conditions. The controller is being modeled for proportional, proportional plus integral and proportional plus integral plus derivative control and the results are being compared and discussed.

The present research was mainly focused on the production of biodiesel from Annona squamosa oil using a synthesized Ni-doped CaO nanocatalyst. The optimization of the transesterification reaction parameters was studied through response surface methodology. The highest biodiesel yield of 99.1% was achieved with the optimized conditions of 7.86% catalyst concentration, 442 RPM, 15.19:1 molar ratio of methanol to oil, reaction temperature of 55.8°C and reaction time of 63.3 min. The results obtained from reaction kinetics study showed a good fit with a first-order kinetic model. The activation energy and R2value were determined to be 53.7 kJ/mol and 0.90, respectively. The synthesized Ni-doped CaO nanocatalyst was characterized using Scanning Electron Microscope with Energy Dispersive X-ray Spectroscopy which confirms the presence of nickel, calcium and oxygen. Also, the average size of the nanocatalyst was found to be 48.79 nm. The Fourier Transform–Infrared Spectroscopy results showed the occurrence of functional groups such as C-H and C = O bonds in the synthesized Ni-doped CaO nanocatalyst. The presence of fatty acid methyl esters in the produced biodiesel was analyzed through Gas Chromatography-Mass Spectrometry analysis. The obtained results from the current study provides the possibility and insights for sustainable biodiesel production and a greener environment.

Lithium-ion batteries have emerged as a promising choice for electric vehicle applications. However, thermal runaway and related catastrophic issues perplex the research community when batteries are subjected to varying charging/discharging and different ambient temperatures. In order to keep the batteries under a safe zone of temperature, battery thermal management occupies utmost importance and hence researchers are switching over to a combination of either two or three strategies since single stragaty could not meet effective thermal management. In a combined strategy, the use of phase change materials and is highly essential due to their inherent thermo-physical properties; both organic and inorganic types have been explored. To enhance the heat dissipation, the phase change materials, regarded as composite phase materials, are being added with graphite powder, nanomaterials, metal foams, and fins are being arranged to the battery cells. The present review enumerates the recent progress made in achieving good thermal performance with hybrid/integrated battery thermal systems with an emphasis on the use of composite phase change materials. The review revealed that the hybrid strategy is performing well, machine learning and advanced optimization methods are being applied to understand the state of health of batteries. Few works are focussed on the mitigation of thermal runaway propagation serving the composite phase change materials as effective flame retardants. The current status and challenges being faced in the use of LIBs is also briefed. It is essential to develop economical integrated battery thermal management systems with parasitic power losses that are compact and safe to attract many city dwellers to adopt pure electric vehicles besides meeting the mandate of sustainable development goals. The review is an attempt to provide a ready reckoner in the area of integrated battery thermal management involving composite phase materials.

AbstractNiFe2O4/polythiophene nanocomposite was synthesized by in situ chemical oxidative polymerization of thiophene in NiFe2O4 nanoparticles presence, whereas NiFe2O4 nanoparticles were prepared via coprecipitation method. Fourier transform infrared (FTIR), X‐ray diffraction (XRD), UV–Visible, and SEM, EDX techniques were used for characterization of the nanocomposite. The effect of various parameters such as adsorbent dose, contact time, initial dye concentration, and initial pH of solution on the adsorption of Janus green B (JG) and Fuchsin basic (FB) onto the nanocomposite was optimized by batch studies. The equilibrium uptake data ascribed well to the Langmuir model with maximum adsorption capacity of 143 and 498 mg/g at 303 K for JG and FB, respectively. The exceptional high adsorption capacity of NiFe2O4/polythiophene nanocomposite for JG and FB was ascribed to π‐π and electrostatic interactions. Kinetics studies pointed out that JG and FB removal followed pseudo‐second order model. The negative values of ΔH° (JG: –47.28; FB: −38.00 kJ/mol) and ΔG° (JG: −9.347 to −6.442; FB: −14.16 to – 12.85 kJ/mol) pointed out the feasibility, spontaneity, and exothermic nature of removal process. Negative value of ΔS° (JG: –0.125; FB: –0.078 kJ/mol) suggested decrease in randomness at the solid/liquid interface. The results showed that NiFe2O4/polythiophene is an appealing adsorbent for the uptake of JG and FB dyes from aquatic environment.

The development of efficient, low‐cost, non‐noble metal‐oxide‐based nanohybrid materials for overall water splitting is a critical strategy for enhancing clean energy use and addressing environmental issues. In this study, an interfacial engineering strategy for the development of bimetallic Co–Ni nanoparticles on graphitic carbon nitride (g‐C3N4) using ultrasonication followed by coprecipitation is conveyed. These nanoparticles demonstrate high efficacy as bifunctional electrocatalysts for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline conditions. Co–Ni nanoparticles on graphitic carbon nitride demonstrate an increased surface area via ultrasonication and subsequent coprecipitation. The g‐C3N4 combined with Co–Ni nanoparticles leads to the development of bifunctional catalysts that exhibit significant efficiency in both HER and OER, and their interfacial properties are investigated for the first time. The chemical composition and morphology of g‐C3N4 integrated with Co–Ni nanoparticles significantly influence the modulation of redox‐active sites and the facilitation of electron transfer, resulting in improved splitting efficiency. The interactions between the Co–Ni bimetal and g‐C3N4 demonstrate exceptional electrochemical performance for water splitting. Consequently, the 20% 20–Co–Ni–graphitic carbon nitride electrode demonstrated superior HER performance, comparable to the other electrodes. In the results, it is indicated that an increased molar ratio of Co and Ni incorporated in graphitic carbon nitride significantly improves HER performance.

In a study of the electrochemical behavior of low-cyanide silver plating baths and of the properties of the deposits obtained, it was found that the current-potential curve obtained with a solid electrode showed a two-step reduction wave, the height of the first being 1/5 that of the second. Analysis of the results of polarographic and rotating disk electrode measurmenents sugests that the rate-controlling steps wereAgCN+e-_??_Ag+CN-……(1)Ag(CN)2-+e-_??_Ag+2CN-……(2)for the first and second waves respectively. The Tafel plots of the two waves showed linear relationships at their rising portions, and the reactions are accordingly concluded to be slow chargetransfer controlled.In baths to which selenocyanate ion was added, the increase in current was markedly greater for the second wave than for the first, and the wave was shifted to the positive side. Potential decay curves for the baths containing selenocyanate ion obtained by the current interrupter method showed lower differential capacities than those for baths that were free of selenocyanate ion. This indicates that the selenocyanate ions were adsorbed preferentially at the electrode, suppress the adsorption of cyanide ions and enhancing the silver deposition reaction.Deposits obtained by jet plating were matt at current densities lower than 50A/dm2, and their appearance was not affected by the addition of selenocyanate ion. At above 50A/dm2, deposits obtained from selenocyanate-free baths were burnt, but deposits obtained from baths with selenocyanate ion added were mirror-bright with a strong (200) orientation up to around 150A/dm2.

Rainfed agriculture (1.25 billion hectares out of 1.55 billion hectares arable area) plays an important role globally in improving livelihoods and food security as it covers 63 per cent of total agriculture in Asia and 97 per cent in Africa. These areas are not only the hotspots of poverty but are also food insecure, hotspots of malnutrition, water scarcity, prone to severe land degradation and more vulnerable to the impacts of climate change.1 With increasing demand for food production to meet the needs of the growing population (9 billion by 2050), growing incomes and changing food habits, water scarcity will also intensify. The per-capita availability of water has declined considerably; for example, in India water availability was 1,820 cubic metres per person in 2001 compared to 5,177 cubic metres in 1951, and it is expected to decrease further to 1,341 cubic metres by 2025 and 1140 cubic metres by 2050.

AbstractRecently, modern power systems depend heavily on MicroGrids (MGs), which can accommodate Distributed Energy Resources (DERs) economically and with high flexibility. MGs integrated with DERs can assist in enhancing energy security, significant cost savings, and reduction in emission of greenhouse gases. In this paper, the assessment of operating performance of proposed MG system with DERs is employed to investigate the multi‐objective problems of cost optimization and economic scheduling. A grid‐connected Micro‐grid (MG) combined with solar photovoltaic (PV), wind turbine (WT), fuel cell (FC), and Battery Energy Storage System (BESS) is implemented to model the problem. This proposed model is considered as a test system for cost optimization and battery charging/discharging optimization. The developed framework is presented as multi‐objective function with constraints that can be tackled using an effective optimization technique. The above stochastic multi‐objective problem is optimized using various commonly used Physics based Meta‐heuristic techniques such as Simulated Annealing (SA), Harmony Search (HS), Slime Mold Algorithm (SMA), Gravitational Search Algorithm (GSA), Black Hole Optimization (BHO), Sine Cosine Algorithm (SCA), Multiverse optimization (MVO) and Lightning Search Algorithm (LSA). The assessment of the aforementioned physics‐based optimization techniques used on the proposed MG test system is compared using the results. According to the analysis, Black Hole Optimization (BHO) and Lightning Search Algorithm (LSA) both provide greater cost savings overall and for battery charging, respectively. The suggested optimization methods will take the BESS charging/discharging pattern and total cost savings into account.