We compared the efficacy of the Indian Farmers Fertilizer Cooperative (IFFCO) liquid nano urea formulation (NUF) and conventional urea on the model plant Arabidopsis thaliana. NUF and equimolar bulk urea were applied to vermiculite-grown one-month-old plants as 0.4% foliar sprays. NUF resulted in a 0.4&nbsp;g increase in biomass, 0.5 mg g− 1 in chlorophyll, 0.17 mmol g− 1 in nitrogen, and 28.8 mg g− 1 in amino acid content of the leaves, compared to bulk urea. NUF’s zeta potential of -54.7 mV and particle size of ≃27.7&nbsp;nm, measured by dynamic light scattering and transmission electron microscopy, is suitable for stomatal uptake. A differential gene expression analysis of NUF versus urea-treated plants showed significantly higher expression levels of 211 genes (log2fold-change &gt; 0.5, FDR &lt; 0.05) involved in the biosynthesis of carbohydrates, amino acids, nucleotides, lipids, phytohormones, and secondary metabolites, cell wall biosynthesis and modification, growth and developmental processes, cell cycle, and stress response than bulk urea. On the other hand, 1,286 genes (log2fold-change &lt; -0.5) involved in cell death, abscission, senescence, nitrogen transport and metabolism, and biotic stress response showed lower expression levels upon NUF application than bulk urea. These suggest that although NUF suppresses nitrogen uptake genes, it enhances growth by higher induction of essential biomolecule synthesis and growth-promoting genes, than bulk urea. This research advances current knowledge in sustainable agriculture by elucidating the molecular mechanisms through which nano urea enhances plant productivity compared to bulk urea, potentially reducing fertilizer use.

Department of Bioscience & Bioengineering

IIT Jodhpur

Plant Growth Regulation

Foliar application of nano Urea enhances vegetative growth of Arabidopsis thaliana over equimolar bulk urea through higher induction of biosynthesis genes but suppression of nitrogen uptake and senescence genes.

Increasing climatic concerns have resulted in a drastic shift towards renewable energy resources. The resources like solar, wind are intermittent and result in power generation uncertainties. Conversely rising carbon emissions from transport sector and depleting fossil-based fuels have prompted the automotive industry to embrace Electric Vehicles (EVs) with batteries on wheels. When connected to grid, these vehicles can provide an effective solution for power balance in the scenario of islanded microgrids for ancillary services such as frequency and voltage regulation, power quality mitigation, etc. This work proposes a novel Automatic Voltage Regulator (AVR) integrated Virtual Synchronous Generator (VSG) based control of plugin electric vehicles (PEVs) for ancillary services support under load and EV dynamics individually and integrated. The control framework combines the AVR's regulation capabilities with the VSG's inertia and damping characteristics, enhancing grid stability and reliability. The proposed approach is implemented on a modified IEEE 14-bus system under various case studies, which include changes in load [resistive (R) or resistive-inductive (RL)], variations in number of connected EVs, combined changes in load &amp; EVs both, solar PV intermittency due to sudden cloud cover in the MATLAB environment. The results of the proposed control technique are superior to that of the conventional (droop) control technique, achieving steady state error (SSE), peak overshoot (PO) and settling time (ST) remain below 0.22, 3% and 400 ms respectively. The comparative analysis validates the robustness and stability of the proposed control technique, marking a significant advancement in ancillary services support.

Department of Electrical Engineering

Automatic Voltage Regulator integrated Virtual Synchronous Generator control of plugin electric vehicles for ancillary services support

The increased operational stresses and the aging effect have increased the instances of device malfunctions and failures in the grid. The malfunction/ failure of critical devices such as instrument transformers, breakers, etc cause unwanted supply disruptions and composite system outages. These device-level malfunctions produce unique dynamic signatures, which can be detected/segregated at phasor measurement units (PMUs) using localized data analytics with low processing delays. This work focuses on the detection and identification of ferroresonance (FR) type failures in capacitive voltage transformers (CVTs) in high-voltage transmission systems at the PMU level. For this, firstly the effect of CVT-FR on phasor measurements through frequency response characterization and sensitivity analysis is observed. Thereafter, a divergent density estimation supported intrinsic mode function method is proposed to distinguish FR events from system-level disturbances like faults, generation loss, etc., in the phasor measurements. The divergent density estimation captures the statistical distribution of intrinsic mode functions (IMFs) under perturbation and acquires unique mode signatures corresponding to FR. IMFs are obtained by applying empirical mode decomposition on the raw phasor trends. The proposed method is tested with simulated cases for different CVT models in Matlab/Simulink and real system data in the Eastern region of the India grid.

IEEE Transactions on Industry Applications

Phasor-based Identification of CVT ferroresonance with Divergent Density Distribution of Intrinsic Modes

Department of Chemical Engineering

Department of Computer Science & Engineering

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