Search Results (83)

The proliferation of photovoltaic energy in the electricity grid presents a significant challenge in terms of management, control, and optimization, especially due to its dependence on weather behavior and cloud passing. Even if there are a great number of articles centered on study cloud passing effects, such as voltage flickers, voltage fluctuations, or ramping events, the approaches are quite heterogeneous and lack a broader perspective. A key factor might be the limiting data sets, as wide power generation data sets often omit meteorological data and vice versa. This study uses an advanced monitoring system based on phasor measurement units (PMUs), developed by the authors. The monitoring system is installed at a photovoltaic plant and generates high-quality synchronous irradiance and power data, enabling the joint analysis of irradiance transients, solar power ramp rates, and voltage fluctuations. Therefore, the results of this article present a detailed analysis of the production parameters of photovoltaic plants, focusing on the effects of passing clouds on the photovoltaic plant’s power, current, and voltage. To that end, compression algorithms such as the Swinging Door Algorithm (SDA), commonly used to detect ramp events, were employed. It was found that SDA produces a similar ramp rate output with power and irradiance data, suggesting that both data sets may be complementary. In addition, voltage fluctuations attributable to passing clouds were analyzed. Full article

The widespread integration of renewable energy sources (RESs) into the grid through inertia-less power converters is reducing the overall system inertia leading to large frequency variations. To mitigate this issue, grid-forming (GFM) control strategies in bidirectional battery chargers have emerged as a promising solution, since the inertial response of synchronous generators (SGs) can be emulated by power converters. However, unlike SGs, which can withstand currents above their rated values, the output current of a power converter is limited to its nominal design value. Therefore, the estimation of the power delivered by the GFM power converter during frequency events, called Virtual Inertia (VI) support, is essential to prevent exceeding the rated current. This article analyzes the VI response of GFM power converters, classifying the dynamic behavior as underdamped, critically damped, or overdamped according to the selected inertia constant and damping coefficient, parameters of the GFM control strategy. Subsequently, the transient power response under step-shaped and ramp-shaped frequency deviations is quantified. The proposed analysis is validated using a 1.2 KW single-phase power converter. The simulation and experimental results confirm that the overdamped response under a ramp-shaped frequency event shows higher fidelity to the theorical model. Full article

To promote a more decentralized energy system, the European Commission introduced the concept of Renewable Energy Communities (RECs). Meanwhile, the increasing penetration of Electric Vehicles (EVs) may significantly increase peak power demand and consumption ramps when charging sessions are left uncontrolled. However, by integrating smart charging strategies, such as Vehicle-to-Grid (V2G), EV storage can actively support the energy balance within RECs. In this context, this work proposes a comprehensive and scalable model for leveraging smart charging capabilities in RECs. This approach focuses on an external cooperative framework to optimize incentive acquisition and reduce dependence on Medium Voltage (MV) grid substations. It adopts a hybrid strategy, combining Mixed-Integer Linear Programming (MILP) to solve the day-ahead global optimization problem with local rule-based controllers to manage power deviations. Simulation results for a six-month case study, using historical demand data and synthetic charging sessions generated from real-world events, demonstrate that V2G integration leads to a better alignment of overall power consumption with zonal pricing, smoother load curves with a 15.5% reduction in consumption ramps, and enhanced cooperation with a 90% increase in shared power redistributed inside the REC. Full article

In recent years, the increasing frequency of extreme weather events has led to a rise in unplanned unit outages, posing significant risks to the safe operation of power systems and underscoring the critical need for accurate prediction and effective mitigation of wind and solar power ramp events. Unlike traditional power forecasting, ramp event prediction must capture the abrupt output variations induced by short-term meteorological fluctuations. This review systematically examines recent advancements in the field, focusing on three principal areas: the definition and detection of ramp event characteristics, innovations in predictive model architectures, and strategies for precision optimization. Our analysis reveals that while detection algorithms for ramp events have matured and the overall predictive performance of power forecasting models has improved, existing approaches often struggle to capture localized ramp phenomena, resulting in persistent deviations. Moreover, current research highlights the necessity of developing evaluation systems tailored to the specific operational hazards of ramp events, rather than relying solely on conventional forecasting metrics. The integration of artificial intelligence has accelerated progress in both event prediction and error correction. However, significant challenges remain, particularly regarding the interpretability, generalizability, and real-time applicability of advanced models. Future research should prioritize the development of adaptive, ramp-specific evaluation frameworks, the fusion of physical and data-driven modeling techniques, and the deployment of multi-modal systems capable of leveraging heterogeneous data sources for robust, actionable ramp event forecasting. Full article

Wind power ramping events refer to sustained unidirectional and large-magnitude fluctuations in wind power output over short durations, exhibiting distinct temporal characteristics and imposing significant impacts on power balance. To address the strong temporal dependency of wind power ramping events, a time-sequential outage model for conventional generators was derived and system operational states were sampled using non-sequential Monte Carlo simulation. Considering the frequency dynamics caused by active power imbalances, dynamic frequency security constraints were formulated. An optimal power flow model was developed to minimize wind curtailment and load shedding comprehensive losses, incorporating these dynamic frequency constraints. The optimal power flow model was employed to solve line power flows for sampled system states and compute comprehensive loss risk indices. Case studies on the IEEE RTS-79 system evaluated and compared operational risks across multiple scenarios, validating the effectiveness of the proposed methodology. Full article

The strong volatility of wind power presents persistent challenges to the stable operation of power systems, highlighting the critical need for accurate wind power forecasting to ensure system reliability. This study proposes a wind power prediction approach based on graph convolutional networks, incorporating ramp feature recognition and error correction mechanisms. First, an improved ramp event definition is applied to detect and classify wind power ramp events more accurately, thereby reducing misjudgments caused by short-term fluctuations. Then, a GCN-based model is developed to construct graph representations of various ramp scenarios, allowing for the effective modeling of their coupling relationships. This is integrated with a bidirectional long short-term memory network to enhance prediction performance during power fluctuation periods. Finally, a dynamic error feedback correction mechanism is introduced to iteratively refine the prediction results in real time. Experiments conducted on wind power data from a Belgian wind farm show that the proposed method significantly improves prediction stability and accuracy during ramp events, achieving an approximate 28% improvement compared to conventional models, and demonstrates strong multi-step forecasting capability. Full article

The current research presents an extension of the Pit-Stop Manufacturing framework. It addresses the challenges of managing complexity and uncertainty in the production ramp-up phase of manufacturing systems, bridging the gap in existing approaches that lack comprehensive, quantitative, and system-level solutions. This research integrates state-of-the-art methodologies, utilising such metrics as Overall Equipment Effectiveness and Effective Throughput Loss to enhance ramp-up management. The developed framework is represented by a conceptual model, which is translated into a digital product combining multiple artefacts for comprehensive ramp-up research, namely a digital twin of the production system, a Custom Experiment Manager for multiple simulation runs, and a Graph Solver that uses the stochastic dynamic programming approach to address the decision-making issues during the production system ramp-up evolution. This work provides a robust decision-support tool to optimise production transitions under dynamic conditions by combining stochastic dynamic programming and discrete event simulation. The framework enables manufacturers to model, simulate, and optimise system evolution, reducing throughput losses, improving equipment efficiency, and enhancing decision-making precision. This paper demonstrates the framework’s potential to streamline ramp-up processes and boost competitiveness in volatile manufacturing environments. Full article

A revision of the submarine instability processes offshore the Campania region is presented herein based on the literature data and Multibeam bathymetric and seismic profiles previously acquired by the CNR ISMAR of Naples (Italy). Among others, the objectives and perspectives of this research include the following: the chrono-stratigraphic framework of the submarine instability events and their correlation with the trigger geological processes, including the seismicity, the volcanism and the tectonic activity; density reversal has not been detected as a control factor; the implementation of technologies and database for the acquisition and the processing of morpho-bathymetric, seismo-stratigraphic and sedimentological data in the submarine slopes of Campania, characterized by submarine gravitational instabilities. Other main tasks include producing thematic geomorphological maps of the submarine slopes associated with instability phenomena. The principles of slope stability have been revised to be independent of the slope height. In submarine slopes mainly composed of sand, the stability depends on the slope inclination angle concerning the horizontal (β), equal or minor to the internal friction angle of loose sand (ϕ). Based on this research, it can be outlined that the submarine instability processes offshore of Campania mainly occur along the flanks of volcanic edifices, both emerged (Ischia) and submerged (Pentapalummo, Nisida, Miseno, Procida Channel), on steep, tectonically-controlled sedimentary slopes, (southern slope of Sorrento Peninsula, slope of the Policastro Gulf), and on ramps with a low gradient that surround wide continental shelves (Gulf of Salerno). Full article

Background: Even though venetoclax in combination with azacitidine (VenAza) is considered a low-intensity regimen, its patients present a high incidence of cytopenia and infections during the first courses, making the initial management a challenging phase. Methods: This difficulty in our center led to the establishment of an At-Home (AH) program for ramp-up and follow-up patients during the VenAza combination induction phase focused on therapy administration, patient and caregiver education, and management of adverse events (AEs). A total of 70 patients with newly diagnosed acute myeloid leukemia (ND-AML) or relapsed/refractory AML (R/R AML) were treated with VenAza from March 2019 to May 2022. We compared outcomes between patients managed with a hospital-based (inpatient) approach and those managed through the AH program. Results: Despite most patients experiencing grade 3–4 cytopenias (96.9%), the incidence of serious infections and other AEs was comparable between both groups, with no significant difference in febrile neutropenia (42.3% vs. 27.8%, p = 0.38). Overall, the AH cohort demonstrated a significantly lower hospital readmission rate after ramp-up (29.5% vs. 84.6%, p = 0.001). Moreover, the inpatient cohort’s admission days were longer than in the AH cohort (13 vs. 8, p = 0.28). Conclusions: AH management was feasible and safe, leading to better resource use, enhanced patient comfort, and improved treatment compliance. The potential of AH programs for managing low-intensity chemotherapy regimens can reduce hospital admissions and subsequently improve patient and caregiver well-being. Full article

Power system flexibility is becoming increasingly critical in modern power systems due to the quick switch from fossil fuel-based power generation to renewables, old-fashioned infrastructures, and a sharp rise in demand. If a power system complies with financial restrictions and responds quickly to unforeseen shifts in supply and demand, it can be considered flexible. It can ramp up production during periods of high demand or increase it during unanticipated or scheduled events. The broad use of renewable energy in the power grid can provide environmental and economic benefits; nevertheless, renewables are highly stochastic in nature, with variability and uncertainty. New management with adequate planning and operation in the power system is necessary to address the challenges incorporated with the penetration of renewable energy. The primary aim of this review is to provide a comprehensive overview of power system flexibility, including appropriate definitions, parameters, requirements, resources, and future planning, in a compact way. Moreover, this paper potentially addresses the effects of various renewable penetrations on power system flexibility and how to overcome them. It also presents an emerging assessment and planning of influential flexibility solutions in modern power systems. This review’s scientific and engineering insights provide a clear vision of a smart, flexible power system with promised research direction and advancement. Full article

The evolution of Jurassic carbonates is globally significant for understanding the depositional framework, diagenetic phases and sedimentary characteristics of shallow marine shelf deposits. For this purpose, two outcrop sections of the Jurassic carbonates with a road distance of 121 km in the Trans Indus Ranges, NW Himalayas, were included in this study. Geological fieldwork was conducted for sedimentological data, and representative samples were collected for microfacies analysis and diagenetic evolution complemented by carbon and oxygen isotope analysis. Results show that eight microfacies were identified in both sections where mudstone microfacies was only present in the Chichali section, whereas wackestone and packstone facies widely existed in both sections. The diagenetic evolution interpreted that dolomitization and stylolization were pronounced in the Paniala section, while micritization and calcite cementation were prevalent in the Chichali section. The interpreted depositional setting implies the wide range from supratidal to outer ramp shallow marine for the Chichali section, suggesting a wide range and relatively deeper environment, alongside merely intertidal to middle ramp settings for Paniala section. Diagenetic evolution suggests marine to meteoric influence in the Chichali section, while burial and uplift phases were dominant in the Paniala section. The diagenetic events were also validated by the isotopic analysis, where most of the samples with values up to −4‰ VPDB δ¹⁸O, corresponding to a carbon isotope range of up to +4‰, were interpreted as the burial phase of diagenesis; meanwhile, a few samples with −2 δ¹³C and −7‰ VPDB δ¹⁸O isotope signatures were marked as meteoric influx in the Paniala section. This study indicates the diversity of the depositional environment and diagenetic heterogeneity by integration of thin sections using isotope data, which are quite applicable to shallow marine carbonates. Full article

This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. The core of the suggested modeling approach is the Wind Spatial Extrapolation model (WiSpEx). Measured vertical wind profile data are used as the inlet for stationary CFD simulations to reconstruct the wind flow over a wind farm (WF). This wind field reconstruction helps operators obtain the wind speed and available wind energy at the hub height of the installed WTs, enabling the estimation of their energy production. WT power output is calculated by accounting for the average time it takes for the turbine to adjust its power output in response to changes in wind speed. The proposed method is evaluated with data from two WTs (E40-500, NM 750/48). The wind speed dataset used for this study contains ramp events and wind speeds that range in magnitude from 3 m/s to 18 m/s. The results show that the proposed method can achieve a Symmetric Mean Absolute Percentage Error (SMAPE) of 8.44% for E40-500 and 9.26% for NM 750/48, even with significant simplifications, while the SMAPE of the persistence model is above 15.03% for E40-500 and 16.12% for NM 750/48. Each forecast requires less than two minutes of computational time on a low-cost commercial platform. This performance is comparable to state-of-the-art methods and significantly faster than time-dependent simulations. Such simulations necessitate excessive computational resources, making them impractical for online forecasting. Full article

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment. Full article

Background/Objectives: The aim of this study was to investigate the feasibility and safety of neuromuscular electrical stimulation (NMES) in patients on extracorporeal membrane oxygenation (ECMO) and thoroughly assess any potential adverse events. Methods: We conducted a prospective observational study assessing safety and feasibility, including 16 ICU patients on ECMO support who were admitted to the cardiac surgery ICU from January 2022 to December 2023. The majority of patients were females (63%) on veno-arterial (VA)-ECMO (81%), while the main cause was cardiogenic shock (81%) compared to respiratory failure. Patients underwent a 45 min NMES session while on ECMO support that included a warm-up phase of 5 min, a main phase of 35 min, and a recovery phase of 5 min. NMES was implemented on vastus lateralis, vastus medialis, gastrocnemius, and peroneus longus muscles of both lower extremities. Two stimulators delivered biphasic, symmetric impulses of 75 Hz, with a 400 μsec pulse duration, 5 sec on (1.6 sec ramp up and 0.8 sec ramp down) and 21 sec off. The intensity levels aimed to cause visible contractions and be well tolerated. Primary outcomes of this study were feasibility and safety, evaluated by whether NMES sessions were successfully achieved, and by any adverse events and complications. Secondary outcomes included indices of rhabdomyolysis from biochemical blood tests 24 h after the application of NMES. Results: All patients successfully completed their NMES session, with no adverse events or complications. The majority of patients achieved type 4 and 5 qualities of muscle contraction. Conclusions: NMES is a safe and feasible exercise methodology for patients supported with ECMO. Full article

Natural events (floods, earthquakes, landslides, etc.) may significantly damage archaeological sites, and therefore reducing their exposure to such events represents a priority for protective and conservation activities. The archaeological Sanctuary of Pachacamac (SP; 2nd–16th century CE; Peru) covers an area of 465 hectares and includes roads, enclosures, huacas with ramps, temples, and palaces located along the central coast of Peru. This area is affected by heavy rain and winds related to the El Niño–Southern Oscillation and to intense solar radiation. We use a 30 cm resolution Digital Surface Model obtained from orthophotogrammetric data and perform a morphometric analysis using geomorphological, hydrological, and climatic quantitative parameters. Our aim is to identify the zones exposed to water flow or stagnation during rainfall, as well as the exposure to winds and solar radiation. The calculated parameters are subsequently processed with an object-based image analysis approach to identify areas with higher climate exposure. We show that the SP architectural layout controls the exposure to water stagnation or flow in the form of rainfall, whereas exposure to wind and solar radiation mainly depends on the topography of an area (e.g., the presence of hills and plains). The methodological approach proposed here may be applied and extended to other archaeological sites. Full article