Search Results (276)

The transition from traditional synchronous generators to intermittent renewable sources, combined with increasingly variable and difficult-to-control energy demand, is creating a growing need for large-scale reserves and energy storage. At the same time, reduced system inertia and evolving electricity market regimes are emerging as important challenges that may affect grid stability, reliability, and economic performance. Advanced storage technologies, particularly those with fast ramping and high-response capabilities, offer a potential means of providing near-instantaneous support in response to unexpected system disturbances or market signals, thereby helping to mitigate inertia-related risks. This paper investigates four technologies: pumped hydroelectric storage, battery energy storage systems, synchronous condensers, and special protection schemes, with a focus on their capability to deliver rapid responses to large-scale disturbances. The analysis is conducted using a deliberately simplified power system model to provide qualitative insights into system behavior and control interactions. The results indicate that automation-enabled responses to system imbalances, including support from synchronous condensers and the rapid activation of additional generation, can enhance system performance under disturbance conditions within the considered framework. These findings demonstrate the feasibility and potential value of such approaches; however, further validation using higher-fidelity models and system-specific data is required to quantify their operational and economic impacts. Full article

With the advancement of digital hydropower stations, the requirements of real-time, high-precision industrial soft measurement of key power equipment operating status are attracting more and more attention. However, it is difficult to transfer energy to the monitoring sensor in strong electromagnetic environments. In this paper, a high-efficiency, high-power-density magnetic field energy harvester is proposed for monitoring sensors in hydropower stations, which captures the energy from the magnetic flux leakage of a hydroelectric generating set. Efficient magnetic energy capture is achieved by modeling material properties and optimizing the receiver’s magnetic core parameters via a Genetic Algorithm. The theoretical analysis of charging characteristics is given, and a Maximum Power Point Tracking (MPPT) control circuit is proposed, realizing high-efficiency energy conversion. Finally, an experimental planet is built. Under 70–130 Gs power-frequency magnetic fields, the system delivers 2.8–5.1 V open-circuit voltage, 66 mW maximum load power, and 6.5 mW/cm³ power density. Full article

This study empirically isolates the marginal CO₂ abatement efficiency of wind and solar power within the Greek electricity system, utilizing hourly dispatch data from August 2012 to December 2018—a period characterizing the grid’s “pre-saturation” technical potential. By employing an econometric framework to capture ex-post displacement dynamics, we identify a statistically significant but highly heterogeneous abatement impact across renewable technologies. Our analysis reveals that wind power consistently achieves higher carbon savings per MWh than solar photovoltaics, primarily by driving deeper displacement of carbon-intensive thermal baseload. Conversely, solar generation exhibits a stronger propensity to displace zero-carbon hydroelectric output and net imports, thereby dampening its domestic abatement efficiency. Furthermore, we demonstrate that the marginal emissions avoided are non-linear, fluctuating significantly with system load, interconnection flows, and renewable penetration levels. These findings establish an “unconstrained efficiency” benchmark for the Greek grid, providing the necessary counterfactual to evaluate the diminishing returns and curtailment penalties characterizing the high-penetration era of renewables. Full article

This paper investigates the evolution of the microstructure, mechanical performances, and corrosion resistance of selective laser melting (SLM) 304 steel under different intermittent stretching deformation step sizes, revealing the underlying evolution patterns. The results indicate that the intermittent deformation step size significantly affects the microstructure and performance of SLM 304 steel. Larger step sizes result in more complete molten pool contours, less deformation of grain and cellular structures, and a lower martensite volume fraction; smaller step sizes lead to distorted molten pools, fragmented grains, exacerbated cellular structure distortion, and increased martensite content. In terms of mechanical performances, tensile strength, nano-hardness, and elastic modulus decrease with increasing step size, while elongation increases accordingly. Corrosion resistance improves with larger step sizes, with specimens exhibiting more complete and thicker oxide films on the surface and superior pitting resistance; continuous stretching specimens exhibit the worst corrosion resistance, while the original specimens are the best. Intermittent deformation optimizes properties by regulating microstructure, providing a basis for the design of high-performance SLM 304 steel. This study provides theoretical support for the design and application of additive manufacturing stainless steel components, facilitating the engineering and industrial application of SLM technology in high-end equipment manufacturing. Full article

Electricity production is one of the most significant sources of environmental pollution. Traditional energy sources involve environmental devastation associated with the extraction of fossil fuels, greenhouse gas emissions, dust, and the byproducts of ash and other harmful substances. Therefore, the choice of energy source directly impacts the environmental impact of technological processes. Obtaining energy from sources that do not generate such a significant negative impact on the environment, such as hydroelectric power plants or wind farms, is not always possible, as it depends on the location of a given enterprise near rivers or areas with regularly strong winds. Therefore, the aim of our study was to assess the environmental impact of switching the power source for the technological process of mass bottle packaging from grid-connected to photovoltaic power. To this end, a 1 MW photovoltaic PV installation was designed to replace traditional grid-connected power. The design was carried out using PVsyst 7.4 software. An analysis of the monthly yields from the PV installation showed that it could power the analyzed technological process independently for ten months of the year, excluding January and December. Using Simapro 9.6 software and the Ecoinvent database, an environmental impact analysis of the change in electricity source was conducted. The study showed that powering the process with energy from the proposed photovoltaic farm reduces the potential environmental impact by approximately 75% in terms of human health, approximately 65% in terms of ecosystems, and approximately 50% in terms of resources. Full article

This study employs CiteSpace 6.3 R1 software to conduct a quantitative analysis of 645 cavitation-related centrifugal pump publications from the Web of Science Core Collection database (2007–2025) using bibliometric methods. The analysis encompasses publication volume statistics, keyword co-occurrence analysis, and keyword clustering. The results indicate that research on centrifugal pump cavitation is currently in a phase of rapid development. The annual number of publications related to centrifugal pump cavitation shows an overall fluctuating upward trend, with Jiangsu University emerging as the leading research institution. The research hotspots include fault diagnosis, impeller design, numerical simulation, and validation, forming four major developmental pathways. Research on cavitation in centrifugal pumps has gradually shifted its focus from numerical simulation to practical engineering issues such as pressure pulsation and cavitation, with hot topics evolving at an accelerated pace. Future efforts must address challenges like cavitation monitoring and high-precision simulation to comprehensively enhance the anti-cavitation performance and operational reliability of centrifugal pumps. Full article

Hydroelectric power plants are renewable electricity generation assets that require high availability and reliability in their operation and maintenance. To justify improvement actions (modernization and investments), it is necessary to analyze the operation of the plant, the maintenance plan being implemented, and, naturally, the incidents and breakdowns that affect this asset. This paper presents research on hydroelectric power plant maintenance based on the development of a database of incidents and failures of such plants, considering the methodology of failure modes, effects and criticality analysis (FMECA) as well as the reliability-centered maintenance (RCM) methodology of the initial maintenance plan of a standard hydroelectric power plant. Different maintenance standards and analysis standards (IATF criticality of failure modes, UNE 13306, ISO 14224, etc.) were considered. The results reveal different improvement and optimization actions based on the current technological development, which can be applied to hydroelectric generation (Innovation 4.0), as well as actions to optimize the initial maintenance plan based on Maintenance 4.0. The technical justification for such improvements in hydropower generation highlights a key area of development in the expansion of renewable energies worldwide. Hydropower generation assets have contributed renewable energy to the system for many years; however, they now require redesign in their operation and maintenance. Full article

This study presents the use of a Battery Energy Storage System (BESS) and a thermal power plant to enhance Primary Frequency Regulation (PFR) in a power system. This integration seeks to mitigate operational challenges, such as the reduction in system inertia and frequency regulation, which are heightened when increasing renewable energy use in power grids with high hydroelectric generation. The proposed solution enables thermal generators to operate at optimal capacity, while the BESS provides a rapid frequency response, thereby enhancing operational efficiency and compliance with national standards. The process was structured in five stages: criteria definition, analysis, design, models, and evaluation. A comprehensive methodological approach was adopted, including dynamic system modeling and BESS sizing based on regulatory parameters. The method was tested with real data from a thermal plant under the conditions of the Colombian electricity market. The simulation results highlight the effectiveness of the proposed BESS, with a response time of approximately 0.6 s and regulation maintenance for over 30 s, reducing mechanical stress and preventing frequency overshoot. The control strategy was designed to maintain the energy neutrality of the BESS, thereby stabilizing its state of charge over the operational horizon. The results show that the BESS targets high-frequency transients and the generator focuses on low-frequency adjustments, managed by an Energy Management System (EMS) with a unified control approach. Full article

This study aims to clarify the influence mechanisms of core operating and structural parameters and provide targeted theoretical support for the optimized design and industrial application of metal hydride (MH) hydrogen storage systems. For this purpose, a two-dimensional axisymmetric numerical model was established to characterize the MH adsorption/desorption processes, which was validated by its consistency with previous experimental data. The innovation lies in clarifying the optimization sensitivity and priority of each parameter in the hydrogen adsorption and desorption processes and further revealing the intrinsic mechanism of parameter coupling on the system’s reaction and thermal performance. Results show that the initial temperature is most critical: 303 K shortens adsorption time by 30% (vs. 323 K), while 323 K cuts desorption time by 50%. Optimal adsorption pressure is 8–10 bar; 0.4 bar outlet pressure reduces desorption time by 37%. Enhancing heat transfer and thermal conductivity significantly shortens reaction times, while porosity has a limited impact. These findings advance the fundamental understanding of metal hydride systems and facilitate their transition from laboratory-scale research to industrial implementation. Full article

The integration of new energy into the grid has significantly intensified power grid operational pressure, posing higher demands on hydropower system regulation. As a key unit for power grid load tracking and stability maintenance, parameter mismatch of the PID governor is prone to inducing system bifurcation, thus leading to oscillatory instability, which has emerged as a critical challenge affecting the reliable consumption and sustainable supply of new energy. To address this challenge, a hydroelectric power generation system (HPGS) model in the infinite-bus power system is established. Bifurcation analysis is employed to quantitatively identify the critical thresholds of PID parameters that cause HPGS instability. Based on this, system dynamic response processes under critical thresholds are clarified using time-domain analysis. Furthermore, the potential oscillation instability mechanism is revealed using eigenvalue analysis, and suggestions for PID parameter selection are provided. Key quantitative results indicate that variations in proportional gain, kp, induce five limit point bifurcations. The system enters an unstable region when k_p exceeds 2.467, whereas operation within the range below 0.891 is conducive to system stability. A supercritical Hopf bifurcation arises when integral gain k_i reaches 0.925, so strict restrictions should be imposed on k_i to avoid operating around this critical value. Two supercritical Hopf bifurcations that may trigger system oscillatory instability are identified during differential gain k_d changing, and it should be regulated to a level below 5.188 to ensure system stability. By integrating bifurcation analysis, time-domain analysis, and eigenvalue analysis, this study effectively improves the accuracy of characterizing system dynamic behaviors, providing a clear quantitative basis for PID parameter optimization and bifurcation suppression, as well as laying a theoretical foundation for hydropower system stable operation and the efficient absorption of new energy. Full article

To address the power and energy balancing challenges faced by high-penetration renewable energy systems under long-term intermittent output conditions, this study proposes a multi-source, multi-timescale collaborative dispatch strategy (2MT-S) integrating wind, solar, hydro, thermal, and hydrogen energy resources. First, a long-term-to-day-ahead coupled scheduling framework is established based on intermittent output duration forecasts (3-day/10-day). By integrating seasonal hydrogen storage and pumped-storage hydroelectric plants, this framework achieves comprehensive coordination among electrochemical storage, thermal power, and other flexible resources. Second, a multi-time-horizon optimization model is developed to simultaneously minimize system operating costs and load curtailment costs. This model dynamically adjusts day-ahead scheduling boundary conditions based on long-term and short-term scheduling results, enabling cross-period resource complementarity during wind and photovoltaic generation troughs. Finally, comparative analysis on an enhanced IEEE 30-bus system demonstrates that compared to traditional day-ahead scheduling, this strategy significantly reduces renewable energy curtailment rates and load curtailment volumes during sustained low-generation periods, fully validating its significant advantages in enhancing power supply reliability and economic benefits. Full article

Sustained demand growth and the increasing share of renewable energy sources pose challenges for the operation of modern electrical systems. The variability in wind and solar photovoltaic generation causes temporary imbalances between supply and demand, requiring the incorporation of energy management and storage strategies to guarantee supply. In this context, the need arises to develop optimization models that allow for efficient energy dispatch, minimizing costs and promoting the appropriate use of both conventional and renewable resources. This study formulated a time block dispatch optimization model implemented in the IEEE 24-node system, integrating thermal, hydroelectric, photovoltaic, wind, and energy storage systems. The methodology was based on DC power flows and was developed in MATLAB R2024b, incorporating nodal balance constraints, transmission and generation capacity limits, as well as the operating conditions of the storage systems. The model allowed for the evaluation of both energy and economic performance, validating its behavior under conditions of peak demand and renewable variability. The results demonstrate that the inclusion of energy storage systems allows for a reduction in high-cost thermal generation, optimizing demand coverage with a greater share of renewable energy. An average storage efficiency of 85.5% was achieved, and total system costs were reduced by USD 40,392.39 per day, equivalent to annual savings of USD 14.75 million. Furthermore, power flows remained below 85% of transmission capacity, confirming the proper operation of the grid. In this sense, the model fulfills the proposed objectives and proves to be a tool for energy planning and the technical-economic integration of storage in electrical networks. Full article

Inducers play a critical role in pump operation by providing a preliminary pressure boost to suppress cavitation. The size of the tip clearance directly influences a pump’s operational efficiency. To investigate the impact of tip clearance on a pump’s hydraulic performance and its behavior under cavitation conditions, this study combines experimental and numerical simulation approaches. Numerical computations of the full flow field, including the inducer and a two-stage impeller, were performed for five liquefied natural gas (LNG) cryogenic inducers with different tip clearances. The accuracy of the numerical simulation results was validated by comparing them with the experimentally obtained hydraulic performance curves. The results yield cavitation performance curves, pressure distributions at incipient cavitation, vapor volume fraction contours, and leakage flow streamlines for various tip clearances. The impact of tip clearance on the overall hydraulic performance and cavitation behavior of the LNG inducer was systematically examined, with particular attention given to the microscopic evolution of the Tip Leakage Vortex (TLV) during the initial stages of cavitation. The experimental results indicate that for every 0.2 mm increase in the inducer tip clearance, the pump head decreases by approximately 1 m, the efficiency drops by about 0.2%, and the tip leakage flow rate increases by approximately 5 m³/h. Furthermore, under cavitation conditions, the cavitation area expands as the tip clearance increases. A critical clearance value, δ, exists within the range of 0.4 mm to 0.6 mm, which governs the development pattern of the TLV. When the clearance is smaller than δ, the TLV forms more rapidly, and cavitation development is significantly more sensitive to increases in tip clearance. Conversely, when the clearance exceeds δ, the formation of the TLV is delayed, and cavitation progression becomes less responsive to further increases in tip clearance. Full article

Predicting dam inflow is critical for human life safety, water resource management, and hydroelectric power generation. While machine learning (ML) models address complex, nonlinear hydrological problems, quantum machine learning (QML) offers greater potential to overcome classical computational limits. This study compares a hybrid quantum neural network (HQNN) with the following two classical models: bidirectional CNN-LSTM and support vector regression (SVR). These models were evaluated to predict monthly inflow to the Mile Mughan Dam, a transboundary hydroelectric and irrigation dam located on the Aras River between Azerbaijan and Iran, using a 14-year dataset (2010–2023) under two scenarios. In total, 70% of data was used for training and 30% for testing. The first scenario encompassed meteorological variables plus three months of inflow lags, and the second included inflow lags only. Model performance was assessed using Coefficient of Determination (R²), Root Mean Squared Error (RMSE), Nash–Sutcliffe efficiency (NSE), Mean Absolute Percentage Error (MAPE), and graphical plots. HQNN showed superior performance across all metrics. In Scenario 1, HQNN achieved R² = 0.915, RMSE = 37.318 MCM, NSE = 0.908, MAPE = 8.343%; CNN-BiLSTM had R² = 0.867, RMSE = 46.506 MCM, NSE = 0.858, MAPE = 10.795%; SVR had R² = 0.846, RMSE = 52.372 MCM, NSE = 0.821, MAPE = 12.772%. In Scenario 2, HQNN maintained strong performance (R² = 0.855, RMSE = 48.56 MCM, NSE = 0.845, MAPE = 9.979%) and outperformed CNN-BiLSTM (R² = 0.810, RMSE = 56.126 MCM, NSE = 0.793, MAPE = 11.456%) and SVR (R² = 0.801, RMSE = 60.336 MCM, NSE = 0.761, MAPE = 12.901%). In Scenario 1 and Scenario 2, HQNN increased the prediction accuracy by 19.76% and 13.47%, respectively, compared to the CNN-BiLSTM model. These results confirm HQNN’s reliability in both multivariate and univariate modeling. Full article

The dynamics of chemical components in sediment porewater are crucial for marine ecological research, resource assessment, and environmental monitoring. A scientific sampling strategy is key to obtaining high-quality porewater. This study aims to explore the effects of circular sampling hole size and layout on sampling effectiveness to optimize the sampling strategy. First, this study analyzed the flow field from time and spatial flow. Then, a simulation model was built using COMSOL Multiphysics 6.2 to simulate changes in the flow field, Darcy velocity, and effective sampling depth under different conditions. The results showed that the sampling holes finished sampling earlier due to being close to the open boundary; small sample hole sizes could suppress this time lag but reduce efficiency, and the effective sampling range increased exponentially with volume. When R = 5 mm, D = 150 mm, and V = 10 mL, interference between adjacent layers was effectively avoided, balancing timeliness and sample representativeness. Laboratory experiments and sea trials validated the effectiveness of the sampling strategy. This study provides theoretical and practical guidance for deep-sea porewater sampling technology, supporting marine scientific research. Full article