bluuebunny/crossref_metadata_2025 huggingface dataset:
An impressionist view of V Hydrae
Authors: Planquart L. , Paladini C. , Jorissen A. , Escorza A. , Pantin E. , Drevon J. , Aringer B. , Baron F. , Chiavassa A. , Cruzalèbes P. , Danchi W. , De Beck E. , Groenewegen M. A. T. , Höfner S. , Hron J. , Khouri T. , Lopez B. , Lykou F. , Montarges M. , Nardetto N. , Ohnaka K. , Olofsson H. , Rau G. , Rosales-Guzmán A. , Sanchez-Bermudez J. , Scicluna P. , Siess L. , Thévenin F. , Van Eck S. , Vlemmings W. H. T. , Weigelt G. , Wittkowski M.
Published: June 2024

Context. Asymptotic giant branch (AGB) stars enrich the interstellar medium through their mass loss. The mechanism(s) shaping the circumstellar environment of mass-losing stars is not clearly understood so far.

Aims. Our purpose is to study the effect of binary companions located within the first 10 stellar radii from the primary AGB star. In this work, we target the mass-losing carbon star V Hydrae (V Hya) and search for signatures of its companion in the dust-forming region of the atmosphere.

Methods. The star was observed in the L and N bands with the VLTI/MATISSE instrument at low spectral resolution. We reconstructed images of the photosphere and surroundings of V Hya using the two bands and compared our interferometric observables with VLTI/MIDI and VISIR archival data. To constrain the dust properties, we used the 1D radiative transfer code DUSTY to model the spectral energy distribution.

Results. The star is dominated by dust emission in the L- and N-bands. The MATISSE reconstructed images show asymmetric and elongated structures in both infrared bands. In the L band, we detected an elongated shape of approximately 15 mas that likely is of photospheric origin. In the N band, we found a 20 mas extension northeast from the star and perpendicular to the L-band elongated axis. The position angle and the size of the N-band extension match the prediction of the companion position at the MATISSE epoch. By comparing MATISSE N-band with MIDI data, we deduce that the elongation axis in the N-band has rotated since the previous interferometric measurements 13 yr ago, supporting the idea that the particle enhancement is related to the dusty clump moving along with the companion. The VISIR image confirms the presence of a large-scale dusty circumstellar envelope surrounding V Hya.

Conclusions. The MATISSE images unveil the presence of a dust enhancement at the position of the companion. This opens new doors for further analyses of the binary interaction with an AGB component.
Cataclysmic variables around the period-bounce: An eROSITA-enhanced multiwavelength catalog
Authors: Muñoz-Giraldo Daniela , Stelzer Beate , Schwope Axel
Published: June 2024

Context. Cataclysmic variables (CVs) with degenerate donors that have evolved past the period minimum are predicted to make up a great portion of the CV population, namely, between 40% and 80%. However, either due to shortcomings in the models or the intrinsic faintness of these strongly evolved systems, only a few of these so-called “period-bouncers” have been confidently identified thus far.

Aims. We compiled a multiwavelength catalog of period-bouncers and CVs around the period minimum from the literature to provide an in-depth characterization of the elusive subclass of period-bounce CVs that will support the identification of new candidates.

Methods. We combined recently published or archival multiwavelength data with new X-ray observations from the all-sky surveys carried out with the extended ROentgen Survey with an Imaging Telescope Array (eROSITA) on board the Spektrum-Roentgen-Gamma spacecraft (SRG). Our catalog comprises 192 CVs around the period minimum, chosen as likely period-bounce candidates based on reported short orbital periods and low donor mass. This sample helped us establish specific selection parameters, which were used to compile a “scorecard” that rates the likelihood that a particular system is a period-bouncer.

Results. Our “scorecard” correctly assigns high scores to the already confirmed period-bouncers in our literature catalog. It has also identified 103 additional strong period-bounce candidates in the literature that had not previously been classified as such. We established two selection cuts based on the X-ray-to-optical flux ratio (−1.21 ≤ log(Fx/Fopt) ≤ 0) and the typical X-ray luminosity (log(Lx,bol) ≤ 30.4 [erg s−1]) observed from the eight period-bouncers that have already been confirmed with eROSITA data. These X-ray selection cuts led to the updated categorization of seven systems as new period-bouncers, increasing their known population to 24 systems in total.

Conclusions. Our multiwavelength catalog of CVs around the period minimum drawn from the literature, together with X-ray data from eROSITA, has resulted in a ~40% increase in the population of period-bouncers. Both the catalog and “scorecard” we constructed will aid in future searches for new period-bounce candidates. These tools will contribute to the goal of resolving the discrepancy between the predicted high number of period-bouncers and the low number of these systems successfully observed to date.
MINCE
Authors: François P. , Cescutti G. , Bonifacio P. , Caffau E. , Monaco L. , Steffen M. , Puschnig J. , Calura F. , Cristallo S. , Di Marcantonio P. , Dobrovolskas V. , Franchini M. , Gallagher A. J. , Hansen C. J. , Korn A. , Kučinskas A. , Lallement R. , Lombardo L. , Lucertini F. , Magrini L. , Matas Pinto A. M. , Matteucci F. , Mucciarelli A. , Sbordone L. , Spite M. , Spitoni E. , Valentini M.
Published: June 2024

Context. Most of the studies on the determination of the chemical composition of metal-poor stars have been focused on the search of the most pristine stars, searching for the imprints of the ejecta of the first supernovae. Apart from the rare and very interesting r-enriched stars, few elements are measurable in the very metal-poor stars. On the other hand, a lot of work has been done also on the thin-disc and thick-disc abundance ratios in a metallicity range from [Fe/H]> −1.5 dex to solar. In the available literature, the intermediate metal-poor stars (−2.5<[Fe/H]< −1.5) have been frequently overlooked. The MINCE (Measuring at Intermediate metallicity Neutron-Capture Elements) project aims to gather the abundances of neutron-capture elements but also of light elements and iron peak elements in a large sample of giant stars in this metallicity range. The missing information has consequences for the precise study of the chemical enrichment of our Galaxy in particular for what concerns neutron-capture elements and it will be only partially covered by future multi object spectroscopic surveys such as WEAVE and 4MOST.

Aims. The aim of this work is to study the chemical evolution of galactic sub-components recently identified (i.e. Gaia Sausage Enceladus (GSE), Sequoia).

Methods. We used high signal-to-noise ratios, high-resolution spectra and standard 1D LTE spectrum synthesis to determine the detailed abundances.

Results. We could determine the abundances for up to 10 neutron-capture elements (Sr, Y, Zr, Ba, La, Ce, Pr, Nd, Sm and Eu) in 33 stars. The general trends of abundance ratios [n-capture element/Fe] versus [Fe/H] are in agreement with the results found in the literature. When our sample is divided in sub-groups depending on their kinematics, we found that the run of [Sr/Ba] versus [Ba/H] for the stars belonging to the GSE accretion event shows a tight anti-correlation. The results for the Sequoia stars, although based on a very limited sample, shows a [Sr/Ba] systematically higher than the [Sr/Ba] found in the GSE stars at a given [Ba/H] hinting at a different nucleosynthetic history. Stochastic chemical evolution models have been computed to understand the evolution of the GSE chemical composition of Sr and Ba. The first conclusions are that the GSE chemical evolution is similar to the evolution of a dwarf galaxy with galactic winds and inefficient star formation.

Conclusions. Detailed abundances of neutron-capture elements have been measured in high-resolution, high signal-to-noise spectra of intermediate metal-poor stars, the metallicity range covered by the MINCE project. These abundances have been compared to detailed stochastic models of galactic chemical evolution.
HESS J1745−290 spectrum explained by a transition in the diffusion regime of PeV cosmic rays in the Sgr A* accretion flow
Authors: Muena Claudio , Riquelme Mario , Reisenegger Andreas , Sandoval Astor
Published: June 2024

Context. The diffuse TeV gamma-ray emission detected in the inner ∼100 pc of the Galactic center suggests the existence of a central cosmic-ray accelerator reaching ∼PeV energies. It is interesting to associate this so-called “PeVatron” with the point source HESS J1745−290, whose position is consistent with that of the central supermassive black hole Sgr A*. However, the point source shows a spectral break at a few TeV that is not shown by the diffuse emission, challenging this association.

Aims. We seek to build an emission model for the point source that is consistent with both emissions being produced by the same population of relativistic protons continuously injected with a power-law spectrum up to ∼PeV energies near Sgr A*.

Methods. In our model, we assume that the point source is produced by hadronic collisions between the cosmic rays and the gas in the accretion flow of Sgr A*. The cosmic-ray density is calculated taking into consideration cosmic-ray transport due to diffusion and advection, while the properties of the gas are obtained from previous numerical simulations of the accretion flow.

Results. Our model succeeds in explaining both the point source and the diffuse emission with the same cosmic rays injected in the vicinity of Sgr A*, as long as the coherence length of the magnetic turbulence in the accretion flow is lc ∼ (1 − 3)×1014 cm. The spectral break of the point source appears naturally due to an energy-dependent transition in the way the cosmic rays diffuse within the inner ∼0.1 pc of the accretion flow (where most of the emission is produced).

Conclusions. Our model supports the idea that Sgr A* can be a PeVatron, whose accelerated cosmic rays give rise to both the point source and the diffuse emission. Future TeV telescopes such as CTAO will be able to test this model.
The new Herschel/PACS Point Source Catalogue
Authors: Marton G. , Gezer I. , Madarász M. , Dionatos O. , Audard M. , Roquette J. , Hernandez D. , Paladini R. , Altieri B.
Published: June 2024

Context. Herschel operated as an observatory, and therefore it did not cover the whole sky, but still observed ~8% of it. The first version of an overall Herschel/PACS Point Source Catalogue (PSC) was released in 2017. The data are still unique and are very important for research using far-infrared information, especially because no new far-infrared mission is foreseen for at least the next decade. In the framework of the NEMESIS project, we revisited all the photometric observations obtained by the PACS instrument on-board the Herschel space observatory, using more advanced techniques than before, including machine learning techniques.

Aims. Our aim was to build the most complete and most accurate Herschel/PACS catalogue to date. Our primary goal was to increase the number of real sources, and decrease the number of spurious sources identified on a strongly variable background, which is due to the thermal emission of the interstellar dust, mostly located in star-forming regions. Our goal was to build a blind catalogue, meaning that source extraction is conducted without relying on prior detections at various wavelengths, allowing us to detect sources never catalogued before.

Methods. The methods for data analysis have evolved continuously since the first release of a uniform Herschel/PACS catalogue. We define a hybrid strategy that includes classical and machine learning source identification and characterisation methods that optimise faint-source detection, providing catalogues at much higher completeness levels than before. Quality assessment also involves machine learning techniques. Our source extraction methodology facilitates a systematic and impartial comparison of sensitivity levels across various Herschel fields, a task that was typically beyond the scope of individual programmes.

Results. We created a high-reliability and a rejected source catalogue for each PACS passband: 70, 100, and 160 μm. With the high-reliability catalogue, we managed to significantly increase the completeness in all bands, especially at 70 μm. At the same time, while the number of high-reliability detections decreased, the number of sources matching with existing catalogues increased, suggesting that the purity is also higher than before. The photometric accuracy of our pipeline is ~1% based on comparison with the standard star models.
Faraday tomography of LoTSS-DR2 data
Authors: Erceg Ana , Jelić Vibor , Haverkorn Marijke , Gajović Lovorka , Hardcastle Martin , Shimwell Timothy W. , Tasse Cyril
Published: June 2024

Context. The LOw-Frequency ARray (LOFAR) provides a unique opportunity to probe the magneto-ionised structure of our Galactic neighbourhood with great resolution. In this work, we present a new mosaic created with the second release of LOFAR Two-Metre Sky Survey data (LoTSS-DR2), which probes polarised synchrotron emission in the high-latitude inner Galaxy. This is the third paper in a series whose main goal is understanding the LOFAR Faraday tomographic data at low radio frequencies and utilising it to explore the intricate structure of the local interstellar medium (ISM).

Aims. Our objective is to characterise the observed emission through multi-tracer analysis to better understand the volume and the structures that may be observed with LOFAR. Furthermore, we exploit Faraday depth as a unique tool to probe the diffuse magnetised structure in the local ISM.

Methods. We produced a mosaic Faraday cube of LoTSS-DR2 data by applying a rotation measure synthesis algorithm. From the cube, we constructed Faraday moment maps to characterise the nature of spectra. Additionally, we quantified the linear depolarisation canals using the Rolling Hough transform and used them to search for alignment with other data sets. Utilising LoTSS-DR2 observations alongside complementary data sets including Planck polarisation data, HI emission maps, and starlight polarisation measurements, we explored conditions along observed lines of sight and estimated the distance to the Faraday structures.

Results. The Faraday cube reveals a remarkably ordered structure across two-thirds of the observed area, whose orientation aligns well with that of both the HI filaments and the magnetic field. We estimate the minimum distance to the Faraday structures to be between 40 and 80 pc, which puts them in the vicinity of the Local Bubble wall. The emission is organised in a large gradient in Faraday depth whose origin we associate with the curved wall of the Local Bubble.

Conclusions. Comparing our data with a model of the Local Bubble wall, we conclude that we might be probing a contribution of the medium inside the Local Bubble cavity as well, corresponding to the complex of local interstellar clouds. Moreover, we propose a toy model incorporating an ionised front of finite thickness into the Local Bubble wall, as a curved, cold neutral shell alone is insufficient to produce the observed gradient. We explore possible magnetic field strengths, as well as the possible distribution of the neutral and ionised medium inside the wall, within the constraints of the observed Faraday depth.
Estimating the mass-to-distance ratio for a set of megamaser AGN black holes by employing a general relativistic method
Authors: González-Juárez A. , Momennia M. , Villalobos-Ramírez A. , Herrera-Aguilar A.
Published: June 2024

Context. Motivated by the recent achievements of a full general relativistic method in determining black hole (BH) parameters, we continue to estimate the mass-to-distance ratio of the supermassive BHs hosted at the core of the active galactic nuclei (AGNs) of the megamaser galaxies NGC 1320, NGC 1194, NGC 5495, and Mrk 1029.

Aims. Our aim is to study the properties of super massive BHs at the centers of the selected AGNs by using a full general relativistic method that allows us to address the potential detection of relativistic effects within such astrophysical systems.

Methods. In order to perform statistical estimations with publicly available observational data, we used a general relativistic model that describes BH rotation curves and further employed a Bayesian fitting method.

Results. We estimated the mass-to-distance ratio of the aforementioned BHs, their position and the recessional redshifts of the host galaxies produced by both peculiar motion and cosmological expansion of the Universe. Finally, we calculated the gravitational redshift of the closest maser to the BH for each AGN. This gravitational redshift is a general relativistic effect produced by the gravitational field of the BH properly included in the modelling.
Detection and characterization of detached tidal dwarf galaxies
Authors: Zaragoza-Cardiel Javier , Smith Beverly J. , Jones Mark G. , Giroux Mark L. , Toner Shawn , Alzate Jairo A. , Fernández-Arenas David , Mayya Divakara , Ortiz-León Gisela , Portilla Mauricio
Published: June 2024

Tidal interactions between galaxies often give rise to tidal tails, which can harbor concentrations of stars and interstellar gas resembling dwarf galaxies. Some of these tidal dwarf galaxies (TDGs) have the potential to detach from their parent galaxies and become independent entities, but their long-term survival is uncertain. In this study, we conducted a search for detached TDGs associated with a sample of 39 interacting galaxy pairs in the local Universe using infrared, ultraviolet, and optical images. We employed IR colors and UV/optical/IR spectral energy distributions to identify potential interlopers, such as foreground stars or background quasars. Through spectroscopic observations using the Boller and Chivens spectrograph at San Pedro Mártir Observatory, we confirmed that six candidate TDGs are at the same redshift as their putative parent galaxy pairs. We identified and measured emission lines in the optical spectra and calculated nebular oxygen abundances, which range from log(O/H) = 8.10 ± 0.01 to 8.51 ± 0.02. We have serendipitously discovered an additional detached TDG candidate in Arp72 using available spectra from SDSS. Utilizing the photometric data and the CIGALE code for stellar population and dust emission fitting, we derived the stellar masses, stellar population ages, and stellar metallicities for these detached TDGs. Compared to standard mass-metallicity relations for dwarf galaxies, five of the seven candidates have higher than expected metallicities, confirming their tidal origins. One of the seven candidates remains unclear due to large uncertainties in metallicity, and another has stellar and nebular metallicities compatible with those of a preexisting dwarf galaxy. The latter object is relatively compact in the optical relative to its stellar mass, in contrast to the other candidate TDGs, which have large diameters for their stellar masses compared to most dwarf galaxies. The derived stellar population ages range from 100 Myr to 900 Myr, while the inferred stellar masses are between 2 × 106 M⊙ and 8 × 107 M⊙. Four of the six TDGs are associated with the gas-rich M51-like pair Arp 72, one TDG is associated with a second M51-like pair Arp 86, and another is associated with Arp 65, an approximately equal mass pair. In spite of the relatively low stellar masses of these TDGs, they have survived for at least 100–900 Myrs, suggesting that they are stable and in dynamical equilibrium. We conclude that encounters with a relatively low-mass companion (1/10th–1/4th of the mass of the primary) can also produce long-lasting TDGs.
Sequential giant planet formation initiated by disc substructure
Authors: Lau Tommy Chi Ho , Birnstiel Til , Drążkowska Joanna , Stammler Sebastian Markus
Published: June 2024

Context. Planet formation models are necessary to understand the origins of diverse planetary systems. Circumstellar disc substructures have been proposed as preferred locations of planet formation, but a complete formation scenario has not been covered by a single model so far.

Aims. We aim to study the formation of giant planets facilitated by disc substructure and starting with sub-micron-sized dust.

Methods. We connect dust coagulation and drift, planetesimal formation, N-body gravity, pebble accretion, planet migration, planetary gas accretion, and gap opening in one consistent modelling framework.

Results. We find rapid formation of multiple gas giants from the initial disc substructure. The migration trap near the substructure allows for the formation of cold gas giants. A new pressure maximum is created at the outer edge of the planetary gap, which triggers the next generation of planet formation resulting in a compact chain of giant planets. A high planet formation efficiency is achieved, as the first gas giants are effective at preventing dust from drifting further inwards, which preserves material for planet formation.

Conclusions. Sequential planet formation is a promising framework to explain the formation of chains of gas and ice giants.
Merger seismology: Distinguishing massive merger products from genuine single stars using asteroseismology
Authors: Henneco J. , Schneider F. R. N. , Hekker S. , Aerts C.
Published: June 2024

Products of stellar mergers are predicted to be common in stellar populations and can potentially explain stars with peculiar properties. When the merger occurs after the initially more massive star has evolved into the Hertzsprung gap, the merger product may remain in the blue part of the Hertzsprung–Russell diagram for millions of years. Such objects could, therefore, explain the overabundance of observed blue stars, such as blue supergiants. However, it is currently not straightforward to distinguish merger products from genuine single stars or other stars with similar surface diagnostics. In this work, we made detailed asteroseismic comparisons between models of massive post-main-sequence merger products and genuine single stars to identify which asteroseismic diagnostics can be used to distinguish them. In doing so, we developed tools for the relatively young field of merger seismology. Genuine single stars in the Hertzsprung gap are fully radiative, while merger products have a convective He-burning core and convective H-burning shell while occupying similar locations in the Hertzsprung–Russell diagram. These major structural differences are reflected in lower asymptotic period spacing values for merger products and the appearance of deep dips in their period spacing patterns. Our genuine single-star models with masses above roughly 11.4 solar masses develop short-lived intermediate convective zones during their Hertzsprung gap evolution. This also leads to deep dips in their period spacing patterns. Because of the lack of a convective core, merger products and genuine single stars can be distinguished based on their asymptotic period spacing value in this mass range. We performed the comparisons with and without the effects of slow rotation included in the pulsation equations and conclude that the two types of stars are seismically distinguishable in both cases. The observability of the distinguishing asteroseismic features of merger products can now be assessed and exploited in practice.
Zircon and apatite U-Pb geochronology of the Paleoproterozoic (Eburnean) basement and late Neoproterozoic (Pan-African) metamorphism and magmatism from Port-Béni, Armorican Massif (France)
Authors: Poujol Marc , Hallot Erwan , Abiven Baptiste , Poulizac Aymeric
Published: June 2024

By re-examining the historical outcrops of Port-Béni located in the Trégor unit of the North Armorican Cadomian belt, the present work delivers four new ages that provide additional constraints on the Proterozoic history of northern Brittany. It is established that granitic, porphyritic rocks crystallized at the end of the Rhyacian (Paleoproterozoic), 2038 ± 12 Ma ago, before being transformed into orthogneisses at a late Neoproterozoic (Ediacaran) age of 621 ± 2 Ma, which is a minimum age, given the retrograde alteration these rocks underwent. The age of ca. 1.8 Ga previously proposed for the protolith of the Port-Béni orthogneiss should be discarded, and these two new ages are consistent with most of those yielded so far by the other Icartian (i.e., Eburnean) basement relics from the Armorican Massif. The gneissic basement was then intruded and disrupted into xenoliths by a granodioritic magma that crystallized 604.5 ± 2.0 Ma ago. This age, slightly younger than previously thought, corresponds to the emplacement age of one of the main units of the North Trégor batholith − the Pleubian-Talbert unit −, part of the Trégor volcano-plutonic complex, which may have built up over a longer period than that indicated by the uncertainty associated with this age. Caution should be exercised in extrapolating this age to that of the whole complex. Finally, doleritic dykes, possibly resulting in two swarms previously thought to be Paleozoic in age, have crosscut this complex. One of the latest yielded an age of 597 ± 15 Ma, indicating that the Trégor doleritic dyking episodes also occurred during the late Neoproterozoic, in between ca. 605 Ma and ca. 580 Ma. As the doleritic dykes are of tholeiitic composition, which distinguishes them from the earlier calc-alkaline magmas, they suggest that the intra-arc extension, documented in the southern, adjacent Saint-Brieuc unit of the belt, also affected the Trégor unit. They may likely have fed northern equivalents of the lava flows from the Paimpol Formation (exposed in between the Saint-Brieuc and the Trégor units), when magma production became moderately influenced by the Cadomian (i.e., Pan-African) subduction and mostly dominated by extension, possibly as a result of a steepening of a north-dipping subduction slab. Indeed, a re-examination of the available geochemical and geochronological data in the light of our new results documents that arc-magma production moved progressively from north (Trégor unit) to south (Saint-Brieuc unit) over time, in the interval 605-580 Ma.
Improvement of Power Quality Using SMES in PV, Wind, Battery, FC and Electrolyzer based AC Standalone Microgrid
Authors: Rani R Hannah Jessie , Saraswat Pankaj , Chaudhary Pavan , Kulhar Kuldeep Singh
Published: June 2024

This paper presents a stand-alone hybrid energy system that utilizes Wind, Solar, Fuel Cell (FC), Superconducting magnetic energy storage (SMES) and Electrolyzer. A novel control methodology has been created to guarantee that the dc-link voltage stays at its designated value by regulating the converters linked to the FC and electrolyzer. The dc-link reference voltage signal is generated by a constant voltage algorithm of a maximum power point tracker (MPPT) for the photovoltaic system (PVS). Consequently, the converters linked to the FC and electrolyzers not only control the dc voltage but also function as an MPPT, removing the necessity for an extra MPPT circuit for the PVS. By properly controlling the dynamics of the FC and electrolyzer, the SMES can charge/discharge instantaneously while the FC/electrolyzer can feed/consume power in a steady state. The proposed control methodology of the dc voltage is simple and requires only a few measurements. Furthermore, a PWM inverter controller was created to uphold voltages at their designated reference level. Extensive simulation results carried out using Simulink on MATLAB platform have demonstrated that the controllers function effectively in both transient and steady state situations.
Power Quality Improvement of PV-Battery based Hybrid Standalone AC Microgrid
Authors: Mathur Mala , R Kavitha , Saraswat Pankaj , Kulhar Kuldeep Singh
Published: June 2024

Electricity generation through Photovoltaic (PV) for power supply in rural areas is one of the best solution to solve many problems. The standalone power supply by using PV system is attracting by many scholars. However, storage systems like batteries are mandatory to maintain energy management as well as power quality in PV based standalone systems due to random variations in both solar irradiance as well as load. However, the operation of AC loads requires an inverter. Similarly, a bidirectional DC to DC converter is necessary to handle the discharging and charging process of the battery based on the power difference between generation and load. Even during nighttime when there is no power available from PV panels, the battery must supply the power demanded by the loads. To ensure high-quality power supply at the load bus, a novel control system for the inverter has been implemented. Additionally, this paper proposes a novel energy management system to maintain power balance between generation and load. A maximum power point tracker (MPPT) converter has also been integrated into the PV system using the perturbed and observe (P&O) algorithm. Extensive results, obtained through the MATLAB/Simulink package, are presented to demonstrate the significance of the proposed controllers under various operating conditions. The performance of the proposed control schemes remains satisfactory even when the standalone system undergoes various changes.
LSTM-ANN based DTC of Induction Motor with 5 Level Inverter
Authors: Singh Satendra , Kannagi A. , Goswami Laxmi , Yadav Dhananjay Kumar
Published: June 2024

Medium voltage drives especially induction motor drives are mostly using in industries for many applications. The precious intelligent control of induction motors are high required in nuclear power generation units. Direct torque control (DTC) of induction motors is commonly selected for achieving smooth speed torque characteristics as compared with other existing control techniques. However, conventional DTC suffers from many issues because of maintaining constant reference flux in all the speed regions. Hence two ANN controllers based novel DTC is implemented in this paper. Three phase five level neutral point clamped (5L-NPC) inverter is used to drive the induction motor. The dc-link is established through 36 pulse rectifier. Moreover, photovoltaic (PV) system along with battery bank is also integrated to provide continuous power supply during off grid. An unchanging dc-link voltage is achieved by utilizing a bidirectional dc-dc circuit that is connected between the dc-link and the battery. The proposed control of dc-dc bidirectional circuit can further reduce the ripples and oscillations in dc-link produced by 36 pulse rectifier during unbalanced grid voltages. Realistic responses are presented in this paper by establishing hardware – in the – loop (HIL) with the help of OPAL-RT modules. The HIL based results are discussed under various case studies in this paper.
Comparative Review on Energy Management for Hybrid Electric Vehicles in Smart Cities
Authors: Singh B.P. , Srivastava Manish , H Adarsha , Kumar Arvind
Published: June 2024

This paper reviews different ways to manage energy in Hybrid Electric Vehicles (HEVs) for smart cities by looking at three separate studies. Initially, it explores a structured approach to solving energy management issues in HEVs, comparing three known methods and highlighting one that can be used in real-time. Next, it discusses a creative use of Petri Nets (PNs) for managing energy, either on its own or with the Global Positioning System (GPS). This part points out the benefits of using GPS to manage energy better during different driving conditions. Lastly, the paper talks about the need to improve energy management in a specific type of HEV to address current environmental and energy challenges. It mentions the use of a Genetic Algorithm (GA) to improve energy management strategies, aiming to extend the life of the vehicle’s fuel cell and improve energy efficiency. Through these discussions, this review aims to provide a clear understanding of how energy management in HEVs can be improved in smart city settings.
Advancements in Solar-Powered UAV Design Leveraging Machine Learning: A Comprehensive Review
Authors: R Hariharan , Saxena Archana , Dhote Vijay , S Srisathirapathy , Almusawi Muntather , Raja Kumar Jambi Ratna
Published: June 2024

Unmanned Aerial Vehicles (UAVs), commonly known as drones, have seen significant innovations in recent years. Among these innovations, the integration of solar power and machine learning has opened up new horizons for enhancing UAV capabilities. This review article provides a comprehensive overview of the state-of-the-art in solarpowered UAV design and its synergy with machine learning techniques. We delve into the various aspects of solar-powered UAVs, from their design principles and energy harvesting technologies to their applications across different domains, all while emphasizing the pivotal role that machine learning plays in optimizing their performance and expanding their functionality. By examining recent advancements and challenges, this review aims to shed light on the future prospects of this transformative technology.
A Review on Condition Monitoring of Wind Turbines Using Machine Learning Techniques
Authors: Muralidharan P. , Thakur Gaurav , M Shalini , Sharma Vikalp , Abootharmahmoodshakir  , Dhablia Anishkumar
Published: June 2024

This document examines the most up-to-date research on the application of machine learning (ML) techniques in monitoring the conditions of wind turbines. The focus is on classification methods, which are used to identify different types of faults. The analysis revealed that the majority of the research utilizes Supervisory Control and Data Acquisition (SCADA) information, with neural networks, support vector machines, and decision trees being the most prevalent machine learning algorithms. The review also identifies several areas for future research, such as the development of more robust ML models that can handle noisy data and the use of ML methods for prognosis (predicting future faults).
Market Orient Wind Energy Regulation Model for Efficient Power Distribution in Power Grid Networks
Authors: Pillai Anu G.
Published: June 2024

The power regulation and distribution in smart cities has been well studied. There exists number of methods around the problem. Some of the method uses the voltage availability in the grids of power system and some of them use the cost of energy in the power grids. However, the methods suffer to achieve higher performance in power distribution and regulation. To handle this issue, an efficient Market Orient Wind Energy Regulation Model (MWERM) is presented in this article. The model monitors the production voltage in the power distribution system and market requirement at specific time. Based on that the method computes Market Requirement Factor (MRF) and Market Remuneration Factor (MReF) to compute the Market Energy Cost (MEC). The above factors are measured for various consumers and based on that the method identifies the energy distributor and perform regulation accordingly. The proposed method improves the performance of power distribution and regulation.
Predicting Wind Energy: Machine Learning from Daily Wind Data
Authors: Subramani K. , J Sharon Sophia , Habelalmateen Mohammed I. , Singh Rajesh , Pahade Akhilesh , Ikhar Sharayu
Published: June 2024

This paper offers a comprehensive review of the advancements in the realm of renewable energy, specifically focusing on solid oxide fuel cells and electrolysers for green hydrogen production. The review delves into the significance of wind energy as a pivotal renewable energy source and underscores the importance of precise forecasting for efficient energy management and distribution. The integration of machine learning-based approaches, such as Support Vector Regression and Random Forest Regression, has shown promising results in enhancing the accuracy of wind energy production forecasts. Furthermore, the paper explores the broader landscape of renewable energy generation forecasting, emphasizing the rising prominence of machine learning and deep learning techniques. As the penetration of renewable energy sources into the electricity grid intensifies, the need for accurate forecasting becomes paramount. Traditional methods, while valuable, have encountered limitations, paving the way for advanced algorithms capable of deciphering intricate data relationships. The review also touches upon the inherent challenges and prospective research avenues in the domain, including addressing uncertainties in renewable energy generation, ensuring data availability, and enhancing model interpretability. The overarching goal remains the seamless integration of renewable sources into the grid, propelling us towards a greener future.
Neural Network Models for Wind Power Forecasting in Smart Cities- A review
Authors: Faujdar Pramod Kumar , Bargavi Manju , Awasthi Aishwary , Kulhar Kuldeep Singh
Published: June 2024

Urbanization’s relentless advance intensifies the quest for sustainable energy sources, with smart cities leading the shift toward sustainability. In these innovative urban landscapes, wind power is pivotal in the clean energy paradigm. Efficient wind energy utilization hinges on accurate wind power forecasting, essential for energy management and grid stability. This review explores the use of neural network models for wind power forecasting in smart cities, driven by wind power’s growing importance in urban energy strategies and the expanding role of artificial neural networks (ANNs) in wind power prediction. Wind power integration mitigates greenhouse gas emissions and enhances energy resilience in urban settings. However, wind’s inherently variable nature necessitates precise forecasting. The surge in ANN use for wind power forecasting is another key driver of this review, as ANNs excel at modelling complex relationships in data. This review highlights the synergy between wind power forecasting and neural network models, emphasizing ANNs’ vital role in enhancing the accuracy of wind power predictions in urban environments. It covers neural network fundamentals, data preprocessing, diverse neural network architectures, and their applicability in short-term and long-term wind power forecasting. It also delves into training, validation methods, performance assessment metrics, challenges, and prospects. As smart cities champion urban sustainability, neural network models for wind power forecasting are poised to revolutionize urban energy systems, making them cleaner, more efficient, and more resilient.
Strategic Integration of Wind Energy in Smart Cities: Complementing Hydropower Capabilities
Authors: Jaison Feon , Wadhwa Durgesh , Chaudhary Pavan , Kulhar Kuldeep Singh
Published: June 2024

The urgency of sustainable urban development has propelled wind energy and hydropower to the forefront of smart city initiatives. This article explores the strategic integration of wind energy and hydropower in urban settings, emphasizing their potential to mutually reinforce each other. Wind energy, derived from atmospheric kinetic power, and hydropower, generated by the gravitational force of flowing water, offer distinct advantages. When thoughtfully combined, they enhance energy stability, grid reliability, and peak energy demand fulfillment. The primary advantage of this integration lies in the natural synchronicity of wind and hydropower, addressing the intermittent nature of renewable energy sources. This collaboration reduces greenhouse gas emissions, environmental impact, and enhances energy security, economic growth, and urban resilience. Through case studies and innovations, this review underlines the promising future of wind-hydropower integration in smart cities, underscoring the need for continued innovation, policy support, education, awareness, and partnerships. In summary, strategic wind and hydropower integration has the potential to be a cornerstone of smart city development and the global shift to cleaner, more resilient energy sources.
Optimized Solar Potential Maximization Model for Improved Power Stability in Photovoltaic systems
Authors: Biradar Vijayalaxmi
Published: June 2024

The power stability in power distribution systems are well studied. There exist numbers of models towards maintaining the power stability which consider the residual energy of PV systems. However, there are not efficient in maintaining the power stability and suffer to achieve higher efficiency in potential maximization. Towards maintaining higher potential maximization, an efficient Optimized Solar Potential Maximization Model (OSPMM) is presented in this article. The model considers the factors like Mean Voltage Generation, Mean Voltage Supply and Residual Voltage as the key in the selection of PV system towards power stability. To perform this, the method monitors the incoming voltage produced by various PV systems and collects such factors mentioned above. According to the factors identified, the method estimates Potential Maximization Support (PMS) for various PV systems. Based on the value of PMS, the method selects the PV system towards maintaining power stability. The proposed approach improves the performance of solar potential maximization and power stability maximization.
A Fuzzy Inference Model for Efficient Power Stabilization Model in PV Systems
Authors: Madhavrao Deshmukh Shailesh , Mahobia Ravi Prakash
Published: June 2024

The power stabilization in photovoltaic systems is well studied. There exist number of approaches in stabilizing the output power of PV systems. The most approaches concern about the input power and residual energy of capacitors. Still they suffer to achieve higher performance in power stabilization. To handle this issue, an efficient Fuzzy inference based Power stabilization model (FIPSM) is presented in this paper. The model is focused on utilizing residual energy on different circuits and avoiding higher drain of energy on any of the circuit. The model fabricated with MOFSET device in each circuit which monitors the input and output voltage of any circuit. As the model has number of circuits framed in serial connection, the method generates fuzzy rules based on the conditions of different circuits for different input voltage with output voltage required. At each duty cycle, the method reads the input voltage and identifies set of circuits were in sleep or charging mode. With the list of circuits, the method computes the Fuzzy Inference Voltage Stabilization Support (FIVSS) for various circuits. Based on the value of FIVSS, the method identifies a unique or a subset of circuits to support stabilization. The proposed model improves the performance of power stabilization in photovoltaic systems.
Machine Learning Integration for Enhanced Solar Power Generation Forecasting
Authors: Winster Praveenraj D. David , A Madeswaran , Pastariya Rishab , Sharma Deepti , Abootharmahmoodshakir Kassem , Dhablia Anishkumar
Published: June 2024

This paper reviews the advancements in machine learning techniques for enhanced solar power generation forecasting. Solar energy, a potent alternative to traditional energy sources, is inherently intermittent due to its weather-dependent nature. Accurate forecasting of photovoltaic power generation (PVPG) is paramount for the stability and reliability of power systems. The review delves into a deep learning framework that leverages the long short-term memory (LSTM) network for precise PVPG forecasting. A novel approach, the physics-constrained LSTM (PCLSTM), is introduced, addressing the limitations of conventional machine learning algorithms that rely heavily on vast data. The PC-LSTM model showcases superior forecasting capabilities, especially with sparse data, outperforming standard LSTM and other traditional methods. Furthermore, the paper examines a comprehensive study from Morocco, comparing six machine learning algorithms for solar energy production forecasting. The study underscores the Artificial Neural Network (ANN) as the most effective predictive model, offering optimal parameters for real-world applications. Such advancements not only bolster the accuracy of solar energy forecasting but also pave the way for sustainable energy solutions, emphasizing the integration of these findings in practical applications like predictive maintenance of PV power plants.
Novel control of standalone “Photovoltaic (PV) based Induction Motor Driven Water Pumping System” without battery
Authors: Sharma Ratish , Naval Preeti , Sharma Bhuvnesh , Singh Kulhar Kuldeep
Published: June 2024

Water pumping system powered by PV without using battery bank is attracting by many scholars. Using of batteries can increase the overall system cost during the operation. A novel control algorithm must be incorporated to manage energy balance between load and generation since power produced from solar cells depends on solar irradiance. In order to lift the water from ground, a motor – pump set is used where power is fed by PV systems through proper converter. Generally induction motors are commonly using in water pumping systems. A direct torque control is applied on three phase induction motor in this paper. Three different configurations were discussed in this paper. In order to eliminate an extra converter for MPPT operation of the PV panels, the proposed method is forced the inverter to acts as a MPPT converter of the PV system. Various results are presented in this paper to validate the proposed method.
Seamless Control Method for Wind-PV-Battery Operated Water Pumping Model
Authors: Ezhilarasan G. , Sikka Rishi , Yadav Dhananjay Kumar , Kulhar Kuldeep Singh
Published: June 2024

Water pumping model (WPM) is essential part in modern days for human’s daily activities. The WPM powered by renewable energy power sources (REPS) can reduce the pollution as well as a best solution for many other problems. Implementation of a backup power source through REPS for WPM can also help in decreasing the peak load on the utility grid. Proper sizing of a hybrid power supply system (HPSS) can ensure a consistent water supply to consumers. The wind and photovoltaic modules (PVMs) based HPSSs are two major REPS which commonly used in worldwide. Nevertheless, an energy storage mechanism is required to uphold energy equilibrium within the system due to the unpredictable fluctuations in both irradiance and wind speed. Hence, required number of batteries needs to be integrated to the system with the help of proper converter to make continuous water supply without any interrupt. Adequate space is available for the installation of PVMs and wind systems on both apartments and overhead water tanks in various rural and urban locations. Therefore hybrid PVMs-Wind-Battery based WPM is useful on such places. However, to achieve the best effective and efficient operation of the system, proper coordinated energy management coordination should be developed among wind, PVMs, motor, pump and battery bank unit (BBU). Therefore, a centralized novel energy management approach is designed in this paper. A PMDC generator is included in wind system and PMDC motor is coupled with water pump to reduce losses. Maximum power point tracker circuits (MPPTC) are utilized for optimizing the performance of both wind turbines and PVMs. The two MPPTCs have been combined into a shared dc-link. The BBU is connected to the dc-link via a bidirectional circuit. The bidirectional circuit will maintain voltage at dc-link to drive the PMDC motor corresponding to higher efficiency point. OPAL-RT devices have been designed to showcase outcomes across different operational modes through Hardware-in-Loop technology.