Search Results (668)

This paper analyzes the availability of lithium resources required to support a global decarbonized energy system featuring electrical energy storage based on lithium iron phosphate (LFP) batteries. A net-zero carbon grid consisting of existing nuclear and hydro capacity, with the balance being a 50/50 mix of wind and solar power generation, is assumed to satisfy projected world electrical demand in 2050, incorporating the electrification of transportation. The battery electrical storage capacity needed to support this grid is estimated and translated into the required number of nominal 10 MWh LFP storage plants similar to the ones currently in operation. The total lithium required for the global storage system is determined from the number of nominal plants and the inventory of lithium in each plant. The energy required to refine this amount of lithium is accounted for in the estimation of the total lithium requirement. Comparison of the estimated lithium requirements with known global lithium resources indicates that a global storage system consisting only of LFP plants would require only around 12.3% of currently known lithium reserves in a high-economic-growth scenario. The overall cost for a global LFP-based grid-scale energy storage system is estimated to be approximately USD 17 trillion. Full article

The depletion of water resources caused by climate change and human activities is a pressing global issue. Lake Ereen is one of the ten natural landmarks of the Gobi-Altai of western Mongolia is included in the list of “important areas for birds” recognized by the international organization Birdlife. However, the construction of the Taishir Hydroelectric Power Station, aimed at supplying electricity to the western provinces of Mongolia, had a detrimental effect on the flow of the Zavkhan River, resulting in a drying-up and pollution of Lake Ereen, which relies on the river as its water source. This study assesses the pollution levels in Ereen Lake and determines the feasibility of its rehabilitation by redirecting the flow of the Zavkhan River. Field studies included the analysis of water quality, sediment contamination, and the composition of flora. The results show that the concentrations of ammonium, chlorine, fluorine, and sulfate in the lake water exceed the permissible levels set by the Mongolian standard. Analyses of elements from sediments revealed elevated levels of arsenic, chromium, and copper, exceeding international sediment quality guidelines and posing risks to biological organisms. Furthermore, several species of diatoms indicative of polluted water were discovered. Lake Ereen is currently in a eutrophic state and, based on a water quality index (WQI) of 49.4, also in a “polluted” state. Mass balance calculations and box model analysis determined the period of pollutant replacement for two restoration options: drying-up and complete removal of contaminated sediments and plants vs. dilution-flushing without direct interventions in the lake. We recommend the latter being the most efficient, eco-friendly, and cost-effective approach to rehabilitate Lake Ereen. Full article

This work proposes a new method to refill fuel cell electric vehicle hydrogen tanks from a storage system in hydrogen refueling stations. The new method uses the storage tanks in cascade to supply hydrogen to the refueling station dispensers. This method reduces the hydrogen compressor power requirement and the energy consumption for refilling the vehicle tank; therefore, the proposed alternative design for hydrogen refueling stations is feasible and compatible with low-intensity renewable energy sources like solar photovoltaic, wind farms, or micro-hydro plants. Additionally, the cascade method supplies higher pressure to the dispenser throughout the day, thus reducing the refueling time for specific vehicle driving ranges. The simulation shows that the energy saving using the cascade method achieves 9% to 45%, depending on the vehicle attendance. The hydrogen refueling station design supports a daily vehicle attendance of 9 to 36 with a complete refueling process coverage. The carried-out simulation proves that the vehicle tank achieves the maximum attainable pressure of 700 bars with a storage system of six tanks. The data analysis shows that the daily hourly hydrogen demand follows a sinusoidal function, providing a practical tool to predict the hydrogen demand for any vehicle attendance, allowing the planners and station designers to resize the elements to fulfill the new requirements. The proposed system is also applicable to hydrogen ICE vehicles. Full article

The efficiency decline of Francis turbines, a key component of hydroelectric power generation, presents a multifaceted challenge influenced by interconnected factors such as water quality, incidence angle, erosion, and runner wear. This paper is structured into two main sections to address these issues. The first section applies the Buckingham π theorem to establish a dimensional analysis (DA) framework, providing insights into the relationships among the operational variables and their impact on turbine wear and efficiency loss. Dimensional analysis offers a theoretical basis for understanding the relationships among operational variables and efficiency within the scope of this study. This understanding, in turn, informs the selection and interpretation of features for machine learning (ML) models aimed at the predictive maintenance of the target variable and important features for the next stage. The second section analyzes an extensive dataset collected from a Francis turbine in Colombia, a country that is heavily reliant on hydroelectric power. The dataset consisted of 60,501 samples recorded over 15 days, offering a robust basis for assessing turbine behavior under real-world operating conditions. An exploratory data analysis (EDA) was conducted by integrating linear regression and a time-series analysis to investigate efficiency dynamics. Key variables, including power output, water flow rate, and operational time, were extracted and analyzed to identify patterns and correlations affecting turbine performance. This study seeks to develop a comprehensive understanding of the factors driving Francis turbine efficiency loss and to propose strategies for mitigating wear-induced performance degradation. The synergy lies in DA’s ability to reduce dimensionality and identify meaningful features, which enhances the ML models’ interpretability, while ML leverages these features to model non-linear and time-dependent patterns that DA alone cannot address. This integrated approach results in a linear regression model with a performance (R²-Test = 0.994) and a time series using ARIMA with a performance (R²-Test = 0.999) that allows for the identification of better generalization, demonstrating the power of combining physical principles with advanced data analysis. The preliminary findings provide valuable insights into the dynamic interplay of operational parameters, contributing to the optimization of turbine operation, efficiency enhancement, and lifespan extension. Ultimately, this study supports the sustainability and economic viability of hydroelectric power generation by advancing tools for predictive maintenance and performance optimization. Full article

This article presents the simulation results of inter-turn short circuits in the stator winding of a permanent magnet synchronous generator (PMSG) dedicated for small hydroelectric power plants. During the calculations, a field–circuit model is used via ANSYS software. The simulations were performed for both a fault-free generator and faulty generator with various degrees of short-circuited turns under various operating conditions. The degree of stator winding damage is modeled by changing the number of shorted turns in one phase. The studied generator has a two-layer stator winding made of winding wire. In addition, it is made of three parallel branches. In this way, a more difficult-to-detect condition is simulated. We analyzed the influences of short-circuit fault on the magnetic field and their impact on generator behavior. The analysis of the obtained results indicates the possibility of using the measurement of the stator current histogram, higher-order harmonics of the stator current, back electromotive force (back EMF), phase current growth, and power factor fluctuations for early detection of an inter-turn short circuit. Full article

Credit supervision of practitioners in the water conservancy construction market, a vital pillar of national infrastructure development, significantly impacts project safety and the maintenance of order in the industry. From the perspective of indirect supervision, this study constructs a tripartite evolutionary game model involving government departments, enterprises, and practitioners to analyze the dynamic evolution mechanism of credit supervision. By examining the strategic interactions among the three parties under different regulatory scenarios, we identify key factors influencing the stable equilibrium of evolution and verify the theoretical conclusions through numerical simulations. The study yields several key insights. First, while government regulation and social supervision can substantially increase the likelihood of practitioners’ integrity, relying solely on administrative regulation has an efficiency limit. Second, the effectiveness of the reward and punishment mechanism of the direct manager plays a crucial leveraging role in credit evolution. Lastly, under differentiated regulatory strategies, high-credit practitioners respond more strongly to long-term cost optimization, while low-credit practitioners are more effectively deterred by short-term, high-intensity disciplinary actions. Based on these findings, this study proposes a systematic governance framework of “regulatory model innovation–corporate responsibility enhancement–social supervision deepening.” Unlike previous studies, this framework adopts a comprehensive approach from three dimensions: regulatory model innovation, corporate responsibility enhancement, and social supervision deepening. It offers a more holistic and systematic solution for refining the credit system in the water conservancy construction market, providing both theoretical support and practical approaches. Full article

With the evolution of hydroelectric generators toward larger capacity and higher rotational speeds, the significa++nt increase in power density has rendered rotor cooling technology a critical bottleneck restricting performance enhancement. Addressing the need for feasibility verification and thermodynamic characteristic analysis of evaporative cooling applied to rotors, this study innovatively proposes an internal-cooling-based evaporative cooling architecture for rotor windings. By establishing a single-channel experimental platform for a rotor evaporative cooling system, the key parameters of the system circulation flow under varying centrifugal accelerations and thermal loads are obtained, revealing the flow mechanism of the cooling system. The experimental results demonstrate that the novel architecture has outstanding heat dissipation performance. Furthermore, the experimental findings reveal that the flow characteristics of the medium are governed by the coupled effect of centrifugal acceleration and thermal load; the flow rate decreases with increasing centrifugal acceleration and increases with rising thermal load. Centrifugal acceleration reduces frictional losses in the heating pipe, leading to a decrease in the inlet–outlet pressure difference. Through the integration of experimental data with classic formulas, this study refines the friction factor model, with the modified formula showing a discrepancy of −10% to +5% compared with the experimental results. Finally, the experiment was rerun to verify the universality of the modified friction factor. Full article

As a pivotal technology and infrastructure component for modern power systems, energy storage has experienced significant advancement in recent years. A fundamental prerequisite for designing future energy storage facilities lies in the systematic evaluation of energy conversion capabilities across diverse storage technologies. This study conducted a comparative analysis between pumped hydroelectric storage (PHS) and compressed air energy storage (CAES), defining the concepts of height exergy and temperature exergy. Height exergy is the maximum work capacity of a liquid due to height differences, while temperature exergy is the maximum work capacity of a gas due to temperature differences. The temperature exergy represents innovation in thermodynamic analysis; it is derived from internal exergy and proven through the Maxwell relation and the decoupling method of internal exergy, offering a more efficient method for calculating energy storage capacity in CAES systems. Mathematical models of height exergy and temperature exergy were established based on their respective forms. A unified calculation formula was derived, and their respective characteristics were analyzed. In order to show the meaning of temperature exergy more clearly and intuitively, a height exergy model of temperature exergy was established through analogy analysis, and it was concluded that the shape of the reservoir was a cone when comparing water volume to heat quantity, intuitively showing that the cold source had a higher energy storage density than the heat source. Finally, a typical hybrid PHS–CAES system was proposed, and a mathematical model was established and verified in specific cases based on height exergy and temperature exergy. It was demonstrated that when the polytropic exponent n = 1.2, the theoretical loss accounted for the largest proportion, which was 2.06%. Full article

This study examines the causes and implications of the unprecedented electricity consumption observed in Croatia during an intense heatwave in July 2024. On the evening of 17 July 2024, power demand reached an all-time high of 3381 MW, significantly surpassing the average demand of around 2000 MW. More concerningly, during these peak hours, 35% of the electricity had to be imported due to insufficient domestic generation capacity. As a result, average monthly electricity prices for July and August 2024 exceeded 250 EUR/MWh in the evening hours. Looking ahead, Croatia and Southern Europe are expected to face increasingly hotter summers, pushing power systems to accommodate even higher peak loads. As the energy transition progresses toward a greater reliance on intermittent renewable energy, enhancing power grid flexibility will become essential. Flexible power generation will play a critical role in bridging gaps in renewable energy output. Solutions such as pumped hydro storage and battery systems can store excess renewable energy and release it during peak demand periods. Additionally, demand response strategies—encouraging the shift of electricity usage to times of higher wind and solar availability—offer another effective way to adapt to the intermittent nature of renewable energy sources. Full article

In the current configuration of Brazil’s hydro-thermal-wind power system, hydroelectric reservoirs have progressively lost their long-term regulatory role due to inadequate planning, inefficient energy use, and reduced inflows. In the context of the energy transition and the incorporation of low-emission technologies into the generation mix, this study proposes expanding nuclear baseload capacity as a “regulatory thermal buffer” to mitigate hydrological uncertainty and strengthen grid stability. Using the São Francisco River basin as a case study, an equivalence factor is developed to relate nuclear energy output to stored hydropower reservoir volume. Results show that nuclear generation can help restore the multi-annual regulatory capacity of Brazil’s hydropower system and enhance the resilience of the National Interconnected System by contributing substantial inertia to an increasingly variable, renewable-based grid. Full article

There is a consensus that climate change has affected society. The increase in temperature and reduction in precipitation for some regions of the world have had implications for the intensity and frequency of extreme events. This scenario is worrying for various sectors of water use, such as hydroelectric power generation and agriculture. Reduced flows in river basins, coupled with increased water consumption, can significantly affect energy generation and food production. Within this context, this paper presents an analysis of climate change impacts in a large basin of Brazil between the Amazon and Cerrado biomes, considering the effects of water demands. Inflow projections were generated for seven power plant reservoirs in the Tocantins–Araguaia river basin, using projections from five climate models. The results indicate significant reductions in flows, with decreases of more than 50% in the average flow. For minimum flows, there are indications of reductions of close to 85%. The demand for water, although growing, represents a smaller part of the effects, but should not be disregarded, since it impacts the dry periods of the rivers and can generate conflicts with energy production. Full article

The São Francisco River provides water for agriculture, urban areas, and hydroelectric power generation, benefiting millions of people in Brazil. Its Basin supports various species, some of which are endemic and rely on its unique habitats for survival. Currently, monitoring maximum air temperature in the São Francisco River Basin is limited due to sparse weather stations. This study proposes three linear regression models to estimate maximum air temperature using satellite-derived land surface temperature from the Aqua’s moderate resolution imaging spectroradiometer across the Basin’s three main biomes: Caatinga, Cerrado, and Mata Atlântica. With over 94,000 paired observations of ground and satellite data, the models showed good performance, accounting for 46% to 54% of temperature variation. Cross-validation confirmed reliable estimates with errors below 2.7 °C. The findings demonstrate that satellite data can improve air temperature monitoring in areas with limited ground observations and suggest that the proposed biome-specific models could assist in environmental management and water resource planning in the São Francisco River Basin. This includes providing more informed policies for climate adaptation and sustainable development or analyzing variations in maximum air temperature in arid and semi-arid regions to contribute to desertification mitigation strategies in the São Francisco River Basin. Full article

This study focuses on the challenge of short-term economic dispatch in hybrid generation systems, specifically under scenarios where energy constraints arise due to reduced water availability. The primary aim is to compare various generation scenarios to evaluate the influence of renewable energy-based power plants on the overall operating cost of an Electric Power System. The hybrid generation system under analysis comprises hydroelectric, thermoelectric, photovoltaic solar, and wind power plants. The latter two, in particular, play a crucial role, yet their performance is highly dependent on the variability of their primary resources—solar radiation, wind speed, and ambient temperature—which are inherently stochastic. To estimate their behavior, the Monte Carlo method is applied, utilizing probability distribution functions to predict resource availability throughout the planning horizon. Once the scenarios are established, the problem is formulated as a hydrothermal dispatch optimization, which is then tackled using heuristic and metaheuristic approaches, with a strong focus on the Differential Evolution algorithm. Full article

Dams are critical infrastructures that provide essential services such as water supply, hydroelectric power generation, and flood control. As many dams age, the risk of structural failure increases, making safety assurance more urgent than ever. Traditional monitoring systems typically employ predictive models—based on techniques such as the finite element method (FEM) or machine learning (ML)—to compare real-time data against expected performance. However, these models often rely on static warning thresholds, which fail to reflect the dynamic conditions affecting dam behavior, including fluctuating water levels, temperature variations, and extreme weather events. This study introduces an adaptive warning threshold methodology for dam safety based on kernel density estimation (KDE). The approach incorporates a boosted regression tree (BRT) model for predictive analysis, identifying influential variables such as reservoir levels and ambient temperatures. KDE is then used to estimate the density of historical data, allowing for dynamic calibration of warning thresholds. In regions of low data density—where prediction uncertainty is higher—the thresholds are widened to reduce false alarms, while in high-density regions, stricter thresholds are maintained to preserve sensitivity. The methodology was validated using data from an arch dam, demonstrating improved anomaly detection capabilities. It successfully reduced false positives in data-sparse conditions while maintaining high sensitivity to true anomalies in denser data regions. These results confirm that the proposed methodology successfully meets the goals of enhancing reliability and adaptability in dam safety monitoring. This adaptive framework offers a robust enhancement to dam safety monitoring systems, enabling more reliable detection of structural issues under variable operating conditions. Full article

To explore the feasibility of renewable hybrid energy systems for expressway infrastructure, this study proposes a scenario-based design methodology integrating solar, wind, and hydropower resources within the expressway corridor. A case study was conducted on a highway service area located in southern China, where a solar/wind/hydro hybrid energy system was developed based on the proposed approach. Using the HOMER Pro 3.14 software platform, the system was simulated and optimized under off-grid conditions, and a sensitivity analysis was conducted to evaluate performance variability. The results demonstrate that the strategic integration of corridor-based natural resources—solar irradiance, wind energy, and hydrodynamic potential—enables the construction of a technically and economically viable hybrid energy system. The system includes 382 kW of PV, 210 kW of wind, 80 kW of hydrokinetic power, a 500 kW diesel generator, and 180 kWh of battery storage, forming a hybrid configuration for a stable and reliable energy supply. The optimized configuration can supply up to 1,095,920 kWh of electricity annually at a minimum levelized cost of energy of USD 0.22/kWh. This system reduces CO₂ emissions by 23.2 tons/year and NO_x emissions by 23 kg/year. demonstrating strong environmental performance and long-term sustainability potential. Full article