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We investigate ten of the most recent tephra-fall deposits emplaced between ≤21 and 2 ka from the Pacheco stage of Misti volcano, Peru, to elucidate magma dynamics and explosive eruption triggers related to magma storage, recharge, and remobilization. Whole-rock, glass, and mineral textures and compositions indicate the presence of broadly felsic, intermediate, and mafic magmas in a chemically and thermally stratified magma storage system (Zones 1–3) that interact to differing extents prior to eruption. Intermediate magmas are defined by plagioclase + amphibole + two-pyroxenes + Fe-Ti oxides and phase equilibria indicate they formed at ~300 to 600 MPa and ~950°C to 1000°C. Intermediate magmas dominate the Pacheco stage and either erupted alone as hybridized magmas or mingled with minor volumes of cool felsic magmas (~800°C) in which only plagioclase + Fe-Ti oxides are stable. Felsic magmas do not exclusively comprise any tephra-fall deposit emplaced during the Pacheco stage but were remobilized by recharge and mixing with intermediate magmas in order to erupt. Furthermore, felsic-hosted amphibole cognate to the intermediate magmas are reacted despite the felsic magmas being water saturated, which suggests they are staged above the amphibole stability limit (≤200 MPa). The cryptic presence of mafic magmas is indicated by high-An plagioclase cores (An74–88), rare anhedral olivine (Fo77–80), and possibly high Mg# augite and amphibole (up to Mg# 84 and 77, respectively). The dearth of basalt to basaltic andesite melts recorded in erupted glasses and exclusivity of high-An plagioclase to crystal cores signals mafic magmas are staged deeper in the crust than the intermediate magmas. Periodic interactions between these magmas tracked via glass compositions and crystal exchange reveal an alternation between the production of mingled magmas and their eruption shortly after a recharge event, followed by a period of homogenization and eruption of hybridized magmas. As such, we identify magma recharge as a key mechanism by which half of the explosive eruptions were triggered in the Pacheco stage. A >100°C increase in Misti's fumarole temperatures from 1967 to 2018 coincident with changes in fumarolic gas compositions is consistent with degassing of a mafic recharge magma, signaling that Misti could produce similar explosive eruptions in the future. [ABSTRACT FROM AUTHOR]

Recent advances in high-power applications employing voltage source converters have been primarily fuelled by the emergence of the modular multilevel converter (MMC) and its derivatives. Model predictive control (MPC) has emerged as an effective way of controlling these converters because of its high response. However, the practical implementation of MPC encounters hurdles, particularly in MMCs featuring many sub-modules per arm. This research introduces an approach termed folding model predictive control (FMPC), coupled with a pre-processing sorting algorithm, tailored for modular multilevel converters. The objective is to alleviate a significant part of the computational burden associated with the control of these converters. The FMPC framework combines multiple control objectives, encompassing AC current, DC current, circulating current, arm energy, and leg energy, within a unified cost function. Both simulation studies and real-time hardware-in-the-loop (HIL) testing are conducted to verify the efficacy of the proposed FMPC. The findings underscore the FMPC's ability to deliver fast response and robust performance under both steady-state and dynamic operating conditions. Moreover, the FMPC adeptly mitigates circulating currents, reduces total harmonic distortion (THD%), and upholds capacitor voltage stability within acceptable thresholds, even in the presence of harmonic distortions in the AC grid. The practical applicability of MMCs, notwithstanding the presence of a large number of sub-modules (SMs) per arm, is facilitated by the significant reduction in switching states and computational overhead achieved through the FMPC approach. [ABSTRACT FROM AUTHOR]

Most of the nitrogen (N) accessible for life is trapped in dinitrogen (N2), the most stable atmospheric molecule. In order to be metabolized by living organisms, N2 has to be converted into biologically assimilable forms, so-called fixed N. Nowadays, nearly all the N-fixation is achieved through biological and anthropogenic processes. However, in early prebiotic environments of the Earth, N-fixation must have occurred via natural abiotic processes. One of the most invoked processes is electrical discharges, including from thunderstorms and lightning associated with volcanic eruptions. Despite the frequent occurrence of volcanic lightning during explosive eruptions and convincing laboratory experimentation, no evidence of substantial N-fixation has been found in any geological archive. Here, we report on the discovery of a significant amount of nitrate in volcanic deposits from Neogene caldera-forming eruptions, which are well correlated with the concentrations of species directly emitted by volcanoes (sulfur, chlorine). The multi-isotopic composition (δ18O, Δ17O) of the nitrates reveals that they originate from the atmospheric oxidation of nitrogen oxides formed by volcanic lightning. According to these first geological volcanic nitrate archive, we estimate that, on average, about 60 Tg of N can be fixed during a large explosive event. Our findings hint at a unique role potentially played by subaerial explosive eruptions in supplying essential ingredients for the emergence of life on Earth. [ABSTRACT FROM AUTHOR]

In some applications of microgrids and distributed generation, it is necessary to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an L C filter is usuallyconnected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltages and currents in these systems. However, these strategies have some drawbacks, particularly when multiple-input–multiple-output plants (MIMO) are controlled using single-input–single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross–coupling between different control loops and state variables. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an L C filter connected to a three-level neutral-point clamped converter. The strategy solves an optimisation problem to achieve control of the L C filter variables, i.e., currents and output voltages. Hardware-in-the-loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS–RT HIL platform and a dSPACE Microlab Box controller. In addition to the good dynamic performance of the proposed OSS–MPC, it is demonstrated using HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different operating conditions. [ABSTRACT FROM AUTHOR]

The Dual–Vector model predictive control (DV–MPC) method can improve the steady–state control performance of motor drives compared to using the single–vector method in one switching cycle. However, this performance enhancement generally increases the computational burden due to the exponential increase in the number of vector selections, lowering the system's dynamic response. Alternatively, limiting the vector combinations will sacrifice system steady–state performance. To address this issue, this paper proposes an enhanced DV–MPC method that can determine the optimal vector combinations along with their duration time within minimized calculation times. Compared to the existing DV–MPC methods, the proposed enhanced technique can achieve excellent steady–state performance while maintaining a low computational burden. These benefits have been demonstrated in the results from a 2.5k rpm permanent magnet synchronous motor drive. [ABSTRACT FROM AUTHOR]

A recent study published in Clinical & Translational Medicine examined the effects of polymerised type I collagen (PTIC) on the physiological recovery process from post-acute sequelae of COVID-19 (PASC) in different genders. The study found that PTIC reduced hyperinflammation associated with COVID-19 and led to a decrease in the correlation between physiological networks at baseline and post-treatment days. Women in the PTIC group exhibited a stronger response and faster recovery compared to men. The study suggests that PTIC may be beneficial for women with a robust physiological network, but further research is needed. [Extracted from the article]

There is a global trend to reduce emissions from cars through the adoption of other alternatives, such as electric vehicles (EVs). The increasing popularity of EVs has led to a growing demand for electric vehicle chargers. EV chargers are essential for charging the batteries of EVs. Since the EV charger stays connected to the grid for long periods of time to charge the EV battery, it must be able to handle disturbances in the power grid. The goal of this paper is to present an overview of the impact of grid events on EV battery chargers. As well as the impact of grid unbalances on EV chargers, this paper also provides an overview of the impact of grid faults on other, similar power electronics interfaced resources such as PV and energy storage systems. [ABSTRACT FROM AUTHOR]

Microgrids represent a promising energy technology, because of the inclusion in them of clean and smart energy technologies. They also represent research challenges, including controllability, stability, and implementation. This article presents a dSPACE-control-platform-based implementation of a fixed-switching-frequency modulated model predictive control (M 2 PC) strategy, as an inner controller of a two-level, three-phase voltage source inverter (VSI) working in an islanded AC microgrid. The developed controller is hierarchical, as it includes a primary controller to share the load equally with the other power converter with its own local modulated predictive-based controller. All details of the implementation are given for establishing the dSPACE-based implementation of the control on a dSPACE ds1103 control platform, using MATLAB/Simulink for the controller design, I/O implementation and configuration with the embedded dSPACE's real-time interface in Simulink, and then using the ControlDesk software for monitoring and testing of the real plant. The latter consists of the VSI operating with  L C L  filters, and sharing an  R L  load with a paralleled VSI with exactly the same controller. Finally, the obtained experimental waveforms are shown, with our respective conclusions representing this work, which is a very valuable tool for helping microgrid researchers implement dSPACE-based real-time simulations. [ABSTRACT FROM AUTHOR]

This paper compares two finite-control-set model predictive control (FCS-MPC) strategies in the context of a grid-connected single-phase quasi-Z source inverter (SP-qZSI). Both schemes use discrete-time models of the inductor current and capacitor voltage for the DC side, as well as the output current on the AC side. To enhance the converter's performance, given the non-minimum phase characteristics of the DC side, a long prediction horizon is implemented for the predictive control. However, a horizon of this nature can be highly demanding in terms of processing load, rendering it inapplicable for some microcontrollers. To address this issue and mitigate the processing load, an alternative control strategy is presented that divides the total number of candidate solutions to be evaluated into smaller segments. The performance of the two control strategies is compared using total harmonic distortion (THD) and simulation times as evaluation metrics. The results indicate that the proposed strategy achieves significantly shorter simulation times than the compared control strategy when increasing the prediction horizon. Additionally, a reduction in the THD was observed in the proposed strategy, reaching an average of 2.8%, which is lower than the compared strategy that exhibited THD close to 3.5%. [ABSTRACT FROM AUTHOR]

Deciduous trees are well known for controlling solar gains in buildings, contributing to energy savings in a sector that consumes 35% of global energy. However, there is still a lack of information about the real thermal impact that deciduous trees have. This work proposes a new method that is cheap and easy to implement to quantify the shading efficiency of different types of deciduous trees in hot seasons. The results can be applied in energy evaluations of buildings. The trees selected belong to the central valley of Chile, which is characterized by hot summers and cold winters. The trees selected can also be found in other parts of the world. A spectrometer is used for measuring the amount of solar radiation (irradiance) that is present in the shadow of trees, measuring wavelengths between 339 nm and 750 nm (mostly within the visible light range). The full referential irradiance spectrum of the site is obtained by calibrating the standard ASTM G-173-03. At the site, the spectrometer is used to obtain the visible light range, while the infrared radiation (IR) and ultraviolet (UV) radiation ranges are obtained from the literature. Our results indicate that the analyzed deciduous trees reduce an average of 82% of the solar radiation. This information will help project designers during the building energy efficiency design phase by representative modeling of the solar radiation gains allowed by deciduous trees. [ABSTRACT FROM AUTHOR]

Pulsed electrolysis has become a promising research topic in recent decades due to advances in solid-state semiconductor devices. These technologies have enabled the design and construction of simpler, more efficient, and less costly high-voltage and high-frequency power converters. In this paper, we study high-voltage pulsed electrolysis considering variations in both power converter parameters and cell configuration. Experimental results are obtained for frequency variations ranging from 10 Hz to 1 MHz, voltage changes from 2 V to 500 V, and electrode separations from 0.1 to 2 mm. The results demonstrate that pulsed plasmolysis is a promising method for decomposing water for hydrogen production. [ABSTRACT FROM AUTHOR]

Software Defined Networking (SDN) is a communication alternative to increase the scalability and resilience of microgrid hierarchical control. The common architecture has a centralized and monolithic topology, where the controller is highly susceptible to latency problems, resiliency, and scalability issues. This paper proposes a novel and intelligent control network to improve the performance of microgrid communications, solving the typical drawback of monolithic SDN controllers. The SDN controller's functionalities are segregated into microservices groups and distributed through a bare-metal Kubernetes cluster. Results are presented from PLECS hardware in the loop simulation to validate the seamless transition between standard hierarchical control to the SDN networked microgrid. The microservices significantly impact the performance of the SDN controller, decreasing the latency by 10.76% compared with a monolithic architecture. Furthermore, the proposed approach demonstrates a 42.23% decrease in packet loss versus monolithic topologies and a 53.41% reduction in recovery time during failures. Combining Kubernetes with SDN microservices can eliminate the single point of failure in hierarchical control, improve application recovery time, and enhance containerization benefits, including security and portability. This proposal represents a reference framework for future edge computing and intelligent control approaches in networked microgrids. [ABSTRACT FROM AUTHOR]

The effects of partial shading or dust accumulation on the panels of photovoltaic systems connected to the grid can generate a considerable reduction in energy performance, being necessary to provide the appropriate voltage to the grid regardless of the irradiance level. This paper addresses this problem and presents a comprehensive control strategy and its implementation for a grid-connected microinverter composed of a push–pull converter followed by an H-bridge inverter. In the push–pull converter, a hybrid MPPT algorithm and a PI control enable work in the MPP of the PV panel. In the H-bridge inverter, a cascade control consisting of a PI control and a predictive control allows the connection to the grid. A proof-of-concept prototype is implemented in order to validate the proposal. Experimental tests were performed by connecting the microinverter to a PV panel and a programmable photovoltaic panel emulator to check the MPPT performance. Furthermore, partial shading conditions were simulated on the dc source to check if the global maximum power point is reached. Experimental results demonstrate the feasibility of the topology and the control approach, obtaining MPPT performance in the topology above 99% at different power and voltage levels on the MPPT, even in the presence of partial shading conditions. [ABSTRACT FROM AUTHOR]

This paper investigates space‐vector‐modulation (SVM) technique that uses only rotating space vectors to drive a direct matrix converter (DMC) with zero common‐mode voltage (CMV). Two methods for controlling grid power factor have been proposed in the literature for such a drive. Until now, analysis has been limited to balanced grid conditions. However, total harmonic distortion (THD) of grid currents significantly increases under unbalanced conditions. Hence, the aims of this paper are: (1) derivation of DMC model consisting of general equations for output voltages and input currents, written in the complex form. (2) Analysis and comparison of two existing methods for grid power factor control under balanced grid conditions, by using the previously derived model. (3) Proposal of extended versions of both methods in order to improve converter's performance under unbalanced grid conditions. The proposed control strategy aims to achieve sinusoidal currents and maintain the same power factor on the grid side while completely compensating grid unbalance on the load side. (4) Determination of the maximum transfer ratio under balanced and unbalanced grid conditions. Experimental results with Hardware In the Loop (HIL) are provided to verify the theoretical analysis and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Finite Set Model Predictive Control (FS-MPC) is a widely used technique in power electronic converter applications. One challenge in FS-MPC implementation is selecting appropriate weighting factors, as there is currently no established methodology for finding the best values. An alternative approach is to consider cost functions without weighting factors, as used by the Sequential Model Predictive Control (SMPC). In this paper, the performance of SMPC applied to induction motors is analyzed. The SMPC strategy involves sequentially evaluating simple cost functions by considering a limited number of available switching states for the power electronic converter. This number is the control parameter of the SMPC. The parameter's domains and a selection criteria based on THD were established in this investigation. The power converter topologies studied include the Voltage Source Inverter (VSI) and the Neutral Point Clamped three-level (3L-NPC). Simulations performed in PLECS software and Hardware-in-the-Loop (HIL) tests using an RT Box for valid parameters satisfy the characteristics of the classical predictive control, such as good control variables tracking and high dynamic response. For a VSI converter, increasing the control parameter results in reduced harmonic distortion, while for an NPC converter, optimal results are achieved with control parameter values within a specific range. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-switching-frequency modulated model predictive control (M 2 PC) is established for a two-level three-phase voltage source inverter (VSI) working in an islanded AC microgrid. These small-scale power systems are composed by two or more VSIs which interface DGs, controlling the voltage amplitude and frequency in the system, and simultaneously sharing the load active and reactive power. Generally, these operational characteristics are achieved using hierarchical linear control loops, but with challenging limitations such as slow transient reaction to disturbances and high proneness to be affected by parameter modifications. Model predictive control may solve these issues. Nevertheless, the most used and developed predictive control scheme, the finite-set model predictive control (FS-MPC), presents the drawback of having the harmonic spectrum spread over all the frequencies. This brings issues with coupling between the different hierarchical control levels of the whole microgrid system, and eventually, when designing the filters for main-grid connection. This paper aims to solve these issues by developing the fixed-switching-frequency M 2 PC working with higher-level control loops for operation in an islanded AC microgrid. These advantages are proved in an AC microgrid configuration where methodology for paralleling multiple M 2 PC-regulated VSIs is described, with rapid transient response, inherent stability, and fully decentralised operation of individual VSIs, achieving proper load power sharing, eliminating circular currents, and proper waveforms for output currents and capacitor voltages. All these achievements have been confirmed via simulation and experimental verification. [ABSTRACT FROM AUTHOR]

The land transportation is a cause of noise in cities, thus breaking the natural balance and bringing with it physiological and mental illnesses, as well as occupational accidents. In this sense, the objective of the research was to estimate the sound pressure in land terminals in the city of Jaen, Peru, using data mining algorithms. The methodology consisted in environmentally monitoring six terminals in the city of Jaen, during 2019, using a class 1 sound level meter; the exploratory analysis of the collected variables that influence the noise of the terminals (minimum and maximum sound pressure level, number of light and heavy vehicles, and equivalent sound pressure level) was performed, which were grouped into three groups of variables for the purpose of using data mining algorithms. Three algorithms were used, namely, artificial neural network, linear regression, and M5Rules, using the free software Weka. Considering all variables, the M5Rules method performed the best, because the value of the mean absolute error (0.7462), the root mean square error (1.0575), and uncertainty analysis (0.09) was the smallest compared to the other two methods. However, for the two remaining groups of variables, the linear regression model showed the lowest mean absolute error and mean square root of the error; in addition to presenting coefficients of determination close to one. The algorithms show good behavior when estimating the sound pressure of the terminals in the city of Jaen. [ABSTRACT FROM AUTHOR]

This article reviews the main methodologies employed for the optimal location, sizing, and operation of Distributed Generators (DGs) and Energy Storage Systems (ESSs) in electrical networks. For such purpose, we first analyzed the devices that comprise a microgrid (MG) in an environment with Distributed Energy Resources (DERs) and their modes of operation. Following that, we examined the planning and operation of each DER considered in this study (DGs and ESSs). Finally, we addressed the joint integration of DGs and ESSs into MGs. From this literature review, we were able to identify both the objective functions and constraints that are most commonly used to formulate the problem of the optimal integration and operation of DGs and ESSs in MGs. Moreover, this review allowed us to identify the methodologies that have been employed for such integration, as well as the current needs in the field. With this information, the purpose is to develop new mathematical formulations and approaches for the optimal integration and operation of DERs into MGs that provide financial and operational benefits. [ABSTRACT FROM AUTHOR]

Power electronic devices play an important role in energy conversion. Among the options, matrix converters, in combination with predictive control, represent a good alternative for the power conversion stage. Although several reviews have been undertaken on this topic, they have been conducted in a non-systematic manner, without indicating how the studies considered were chosen. This paper presents results from a systematic literature review on predictive control applied to matrix converters that included 142 primary papers, which were selected after applying a defined protocol with clear inclusion and exclusion criteria. The study provides a detailed classification of predictive control methods and strategies applied to different matrix converter topologies. Research findings require to be understood in combination to develop a common understanding of the topic and ensure that future research effort is based on solid premises. In light of this, this study identifies and characterizes different predictive control techniques and matrix converter topologies through systematic literature review. The results of the review indicate that interest in the area is increasing. A number of open questions in the field are discussed. [ABSTRACT FROM AUTHOR]