Search Results (10)

Islanded photovoltaic microgrids with limited inertial support can undergo steep frequency excursions after sudden generation loss or abrupt load changes. This paper develops and evaluates a synthetic inertia strategy supported by a supercapacitor energy storage unit for fast frequency containment in this type of system. The proposed approach commands rapid active-power injection or absorption from the measured rate of change of frequency, thereby emulating the immediate inertial contribution usually associated with rotating machines while preserving a simple and physically interpretable control structure. The supercapacitor is represented through a resistance–capacitance model that includes equivalent series resistance and is interfaced through a bidirectional buck–boost power converter subject to practical current, voltage, and power limits. Rather than claiming a fundamentally new storage-support concept, the contribution of this paper lies in providing a transparent and constraint-consistent benchmark that integrates measured operating profiles, explicit supercapacitor limits, hybrid frequency–RoCoF support, and stress-aware comparative assessment under a common set of plant assumptions. The methodology is assessed in time-domain simulations under representative benchmark disturbances, including an approximately ten percent photovoltaic generation loss, a ten percent load increase, and a combined event. Performance is evaluated through the peak rate of change of frequency, frequency nadir, integral error indices, time outside the admissible band, and supercapacitor stress indicators such as current peaks, voltage depletion, and energy throughput. An additional non-ideal assessment is also included to examine the behavior of the RoCoF-based support law under bounded frequency-measurement perturbations and delayed control action. A complementary variability-driven case based on a highly fluctuating measured irradiance window is also used to examine the behavior of the adaptive energy-management mechanism under repeated photovoltaic-power variations. A local small-signal analysis is also included to show that the selected gain region is dynamically plausible in the unsaturated regime. The results show that the proposed adaptive hybrid strategy improves the overall frequency response while maintaining admissible supercapacitor operation, thus providing a stronger methodological basis for rapid frequency support in islanded photovoltaic microgrids. Full article

Traditional virtual synchronous generator (VSG) control in photovoltaic–storage systems struggles with severe dynamic deterioration under high-impedance weak grid conditions. Through small-signal modeling, this paper analytically reveals that increased grid inductance forces the system’s dominant poles to migrate significantly toward the real axis, inducing a critical “overdamped hysteresis” that degrades transient tracking speed and oscillation attenuation. To break these physical constraints, an improved exponential synergistic adaptive control strategy is proposed. By establishing a synergistic optimization mechanism between the virtual inertia and damping coefficients via a square-root coupled exponential function, the proposed method achieves precise multi-parameter coordination. During the initial phase of disturbances, it triggers an explosive parameter surge to provide “stiff” transient support, strictly limiting frequency deviations and the rate of change of frequency (RoCoF). During the recovery phase, it drives a precipitous parameter decay to actively neutralize the overdamped coupling effect, forcibly pulling the migrated poles back to the ideal underdamped region. Rigorous switching-model simulations demonstrate that, compared to conventional fixed-parameter and power function-based adaptive methods, the proposed synergistic strategy significantly improves transient performance. Quantitatively, during load steps, it restricts the frequency nadir to 49.85 Hz (compared to 49.73 Hz for fixed parameters). During extreme grid stiffness transitions (SCR drops), it completely eliminates active power tracking hysteresis by reducing the settling time to just 0.26 s and aggressively clamps AC overcurrent peaks from 38 A down to 31 A. Supported by coordinated PV–storage energy management, the proposed method offers a highly robust grid-forming framework for renewable-dominated weak power grids. Supported by coordinated PV–storage energy management, the proposed method offers a highly robust grid-forming framework for renewable-dominated weak power grids. Full article

This paper proposes a regional inertia estimation method in power systems using ambient data measured by phasor measurement units (PMUs). The proposed method employs band-pass filtering to suppress the low-frequency influence of mechanical power and to attenuate high-frequency noise and discrepancies between rotor speed and electrical frequency. By utilizing a simple first-order AutoRegressive Moving Average with eXogenous input (ARMAX) model, this process allows the inertia constant to be directly identified. This method requires no prior model order selection, rotor speed estimation, or computation of the rate of change of frequency (RoCoF). The proposed method was validated through simulation on three benchmark systems: the Kundur two-area system, the IEEE Australian simplified 14-generator system, and the IEEE 39-bus system. The method achieved area-level inertia estimates within approximately ±5% error across all test cases, exhibiting consistent performance despite variations in disturbance models and system configurations. The estimation also maintained stable performance with short data windows of a few minutes, demonstrating its suitability for near real-time monitoring applications. Full article

Passion fruit (Passiflora edulis) is an economically important fruit worldwide. However, heat stress severely threatens its production, particularly in tropical and subtropical regions. To elucidate the molecular and metabolic mechanisms underlying heat tolerance, comparative physiological, transcriptomic, and metabolomic analyses were conducted between two yellow passion fruit cultivars: heat-tolerant ‘Summer Queen’ (F2) and heat-sensitive ‘Qinmi 9’ (QM9). Physiological evaluations demonstrated that QM9 exhibited significantly lower heat tolerance than F2, manifesting as severe leaf wilting, impaired photosynthetic efficiency, and elevated reactive oxygen species (ROS) accumulation. F2 exhibited distinct metabolic and transcriptional adaptations under heat stress, particularly in purine metabolism and flavonoid biosynthesis. Metabolites such as glutamine, xanthine, luteoloside, and trifolin were enriched in F2, alongside the upregulation of genes like adenosine kinase (AK), xanthine dehydrogenase (XDH), guanine deaminase (GDA), and flavonoid 3′-hydroxylase (F3′H). Weighted gene co-expression network analysis (WGCNA) highlighted strong associations between these pathways and transcription factors (e.g., MYB, HSF, WRKY), suggesting their pivotal roles in heat adaptation. Exogenous application of xanthine and trifolin markedly enhanced heat tolerance in passion fruit. Furthermore, knockdown of PeGDA and PeXDH markedly altered the heat tolerance of F2. These findings reveal that elevated metabolites in purine metabolism and flavonoid biosynthesis enhance heat tolerance in passion fruit, offering new insights into the molecular mechanisms of heat tolerance and potential targets for breeding climate-resilient passion fruit varieties. Full article

Long-chain acyl-CoA synthetase (LACS) is a crucial enzyme involved in cellular lipid metabolism, playing a significant role in plant development and adaptation to environmental stress. However, our understanding of the CaLACS gene family in pepper remains limited. In this study, we identified nine members of the CaLACS gene in the ‘UCD-10X-F1’ pepper genome and named them CaLACS1-CaLACS9 based on their chromosomal distribution. Phylogenetic analysis revealed that the subfamily I-A includes CaLACS1, CaLACS3, and CaLACS7; the subfamily I-C contains CaLACS2; the subfamily II comprises CaLACS4 and CaLACS8; and the subfamily III consists of the remaining members. Collinearity analysis showed that there were twelve collinear pairs between six CaLACS genes and five AtLACS genes, and two fragment replication gene pairs in the nine CaLACS genes of pepper. Furthermore, numerous cis-acting elements associated with stress response, hormonal regulation, development, and light response were identified in the promoter regions of the CaLACS genes. RNA-seq analysis indicated that CaLACS genes exhibit tissue specificity and are widely expressed in pepper leaves following treatment with exogenous plant hormones, and under conditions of cold, heat, drought, and salt stress. Additionally, virus-induced gene silencing (VIGS) technology was employed to further investigate the roles of CaLACS6 and CaLACS9. Silencing these target genes in pepper seedlings increased their sensitivity to cold stress, as evidenced by the accumulation of reactive oxygen species (ROS), reduced antioxidant defense capacity, and decreased expression levels of cold-responsive and ROS-related genes. The findings of this study provide valuable insights into the functional roles of the CaLACS gene family and highlight CaLACS6 and CaLACS9 as promising candidate genes for enhancing cold tolerance in pepper. Full article

GNSS-LEO radio links from Precise Orbital Determination (POD) and Radio Occultation (RO) antennas have been used increasingly in characterizing the global 3D distribution and variability of ionospheric electron density (N_e). In this study, we developed an optimal estimation (OE) method to retrieve N_e profiles from the slant total electron content (hTEC) measurements acquired by the GNSS-POD links at negative elevation angles (ε < 0°). Although both OE and onion-peeling (OP) methods use the Abel weighting function in the N_e inversion, they are significantly different in terms of performance in the lower ionosphere. The new OE results can overcome the large N_e oscillations, sometimes negative values, seen in the OP retrievals in the E-region ionosphere. In the companion paper in this Special Issue, the HmF2 and NmF2 from the OE retrieval are validated against ground-based ionosondes and radar observations, showing generally good agreements in NmF2 from all sites. Nighttime hmF2 measurements tend to agree better than the daytime when the ionosonde heights tend to be slightly lower. The OE algorithm has been applied to all GNSS-POD data acquired from the COSMIC-1 (2006–2019), COSMIC-2 (2019–present), and Spire (2019–present) constellations, showing a consistent ionospheric N_e morphology. The unprecedented spatiotemporal sampling of the ionosphere from these constellations now allows a detailed analysis of the frequency–wavenumber spectra for the N_e variability at different heights. In the lower ionosphere (~150 km), we found significant spectral power in DE1, DW6, DW4, SW5, and SE4 wave components, in addition to well-known DW1, SW2, and DE3 waves. In the upper ionosphere (~450 km), additional wave components are still present, including DE4, DW4, DW6, SE4, and SW4. The co-existence of eastward- and westward-propagating wave4 components implies the presence of a stationary wave4 (SPW4), as suggested by other earlier studies. Further improvements to the OE method are proposed, including a tomographic inversion technique that leverages the asymmetric sampling about the tangent point associated with GNSS-LEO links. Full article

In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia. Full article

Annona muricata Linn. is a common plant found in the warmest regions of South and Central America and its use in traditional medicine has been reported for the treatment of various illnesses. In the current study, we investigate the antioxidant and anti-inflammatory activities of crude extract and fractions from A. muricata L. leaves in isolated murine phagocytic immune cells as well as experimental LPS-induced acute lung injury (ALI). In a luminol-dependent chemiluminescence assay, we showed that ethyl acetate (EtOAc.f) and n-butanol (BuOH.f) fractions—both rich in polyphenols—reduced the generation of reactive oxygen species (ROS) by neutrophils stimulated with opsonized zymosan; similar results were found in culture of bone marrow-derived macrophages (BMDMs). By evaluating anti-inflammatory activity in BMDMs, EtOAc.f and BuOH.f reduced secretion of IL-6 and expression of the co-stimulatory molecule CD40. Furthermore, in LPS-induced ALI, oral administration of EtOAc.f reduced myeloperoxidase (MPO) activity in lung tissue. In addition, on a mechanism dependent on glutathione levels, the oxidative damage was also attenuated. These findings revealed direct antioxidant and anti-inflammatory activities of polyphenols-rich fractions of A. muricata L. leaves on neutrophils and macrophages. Moreover, the reduced oxidative damage and levels of inflammatory markers in experimental ALI suggest that these fractions might be explored for the development of new therapies for inflammatory conditions. Full article

Italian autochthonous turkey breeds are an important reservoir of genetic biodiversity that should be maintained with an in vivo approach. The aim of this study, part of the TuBAvI national project on biodiversity, was to use run of homozygosity (ROH), together with others statistical approaches (e.g., Wright’s F-statistics, principal component analysis, ADMIXTURE analysis), to investigate the genomic diversity in several heritage turkey breeds. We performed a genome-wide characterization of ROH-rich regions in seven autochthonous turkey breeds, i.e., Brianzolo (Brzl), Bronzato Comune Italiano (BrCI), Bronzato dei Colli Euganei (CoEu), Parma e Piacenza (PrPc), Nero d’Italia (NeIt), Ermellinato di Rovigo (ErRo) and Romagnolo (Roma). ROHs were detected based on a 650K SNP genotyping. ROH_islands were identified as homozygous ROH regions shared by at least 75% of birds (within breed). Annotation of genes was performed with DAVID. The admixture analyses revealed that six breeds are unique populations while the Roma breed consists in an admixture of founder populations. Effective population size estimated on genomic data shows a numeric contraction. ROH_islands harbour genes that may be interesting for target selection in commercial populations also. Among them the PTGS2 and PLA2G4A genes on chr10 were related to reproduction efficiency. This is the first study mapping genetic variation in autochthonous turkey populations. Breeds were genetically different among them, with the Roma breed proving to be a mixture of the other breeds. The ROH_islands identified harboured genes peculiar to the selection that occurred in heritage breeds. Finally, this study releases previously undisclosed information on existing genetic variation in the turkey species. Full article

The high rate of change of frequency (RoCoF) issue incurred by the integration of renewable energy sources (RESs) into a modern power system significantly threatens the grid security, and thus needs to be carefully examined in the operational planning. However, severe fluctuation of regional frequency responses concerned by system operators could be concealed by the conventional assessment based on aggregated system frequency response. Moreover, the occurrence probability of a high RoCoF issue is actually a very vital factor during the system planner’s decision-making. Therefore, a fast-algorithmic evaluation method is proposed to determine the probabilistic distribution of regional RoCoF for the operational planning of a RES penetrated power system. First, an analytical sensitivity (AS) that quantifies the relationship between the regional RoCoF and the stochastic output of the RES is derived based on the generator and network information. Then a linear sensitivity-based analytical method (LSM) is established to calculate the regional RoCoF and the corresponding probabilistic distribution, which takes much less computational time when comparing with the scenario-based simulation (SBS) and involves much less complicated calculation procedure when comparing with the cumulant-based method (CBM). The effectiveness and efficiency of the proposed method are verified in a modified 16-machine 5-area IEEE benchmark system by numerical SBS and analytical CBM. Full article