Energy-intensive Research Articles

Energy optimization of hydrogen liquefaction process via process knowledge combined with multivariate Coggin's algorithm

Sustainable and cost-effective transportation of hydrogen is one of the major challenges to futuristic hydrogen value chain. Hydrogen, in its produced form, exhibits low energy density and large volume, rendering it highly unsuitable for transportation, particularly over extended distances. Liquefaction is one of the promising approaches to improve hydrogen's energy density and to make it more compact. However, liquefaction is an energy intensive process, raising the cost of transportation. In this study, the specific energy consumption of the hydrogen liquefaction process is aimed to reduce through knowledge-based optimization followed by optimization using the multivariate Coggin's algorithm to improve energy and economic profiles of the process. Design variables, composite curve, exergy, and economic analyses are performed to evaluate and compare the thermodynamic, economic, and environmental feasibility of the optimized process. The results depict a significant reduction (14.3%) in specific energy consumption to 9.40 kW/kgLH2 without increasing process complexity. Further key improvements include a massive drop in refrigerant flowrates (9.2%), annualized cost (m$ 0.15), and annual CO2 emissions (1008.45 tCO2/annum). The largest exergy destruction is observed in CHX-201, reflecting further room for improvement. These results underscore the potential for optimizing hydrogen liquefaction processes to enhance energy efficiency, process economics and environmental impact, providing valuable insights for researchers and industry professionals seeking to advance hydrogen liquefaction technologies. However, challenges remain in the comprehensive evaluation of chemical exergy for ortho- and para-hydrogen and in conducting advanced exergy analyses to further optimize hydrogen liquefaction processes without adding complexity.

Designed harmonic step filter automatic control system to improve power quality and electric efficiency

Designed harmonic step filter automatic control system to improve power quality and electric efficiency

Proposing an innovative polygeneration process based on biogas fuel: A comprehensive thermo-enviro-economic (4E) analysis

The utilization of biogas as a renewable fuel is feasible due to its high energy density, allowing for the development of polygonation structures in a cascade configuration. However, the high initial cost associated with biogas-based high-temperature applications is the central gap considered in this study. This paper introduces a novel heat integration model that employs a novel multi-stage cascade heat recovery and cost-effective operational approach. A biogas burner, an organic Rankine cycle, a Kalina cycle, an absorption chiller cycle, a heat supplier unit, and a proton exchange membrane electrolyzer-based hydrogen generating process are all part of the proposed system. Following the structure's modeling with the Aspen HYSYS program, thermodynamic, environmental, and economic evaluations are carried out along with a thorough parametric assessment. The simulation results indicate that the system has the capability to generate 2993 kW of electricity, 23350 kg/h of hot water at 80 °C, 68120 kg/h of chilled water at 10 °C, and generate 40.32 kg/h of hydrogen. This structure's energy, exergy, and electrical efficiencies are measured at 40 %, 23.71 %, and 16.68 %, respectively. Moreover, the exergy analysis indicated that the biogas burner and ORC evaporator account for 75.1 % of the total irreversibility (13800 kW).

Numerical examination of expanding the effectiveness of thermal photovoltaic framework by changing the level of heat transfer conveyance

In photovoltaic systems, only a tiny portion of solar radiation reaches the module's surface and is converted to electrical energy. The remaining solar radiation is wasted, which raises cell temperature and reduces electrical efficiency. This research focused on examining the effects of different factors on nanofluids. In the simulations performed in this thesis, the inlet temperature of the water fluid changes from 5°C to 30°C. The radiation intensity equals 600W per square meter, and the input speed is 0.07452m per second. The innovation of this article is the use of two nanofluids of aluminum oxide and copper together with a mixture of water to investigate the effect of effective parameters on the electrical, thermal, and overall efficiency of photovoltaic systems, such as the amount of incoming radiation to the surface of the panel, the temperature of the fluid inlet in mountainous areas, the temperature of the absorber. , so that the thermal efficiency of copper and aluminum oxide is investigated and compared. As a result, copper nanofluid can increase the ratio more than aluminum oxide and pure water. There is a direct relationship between the output fluid temperature and the input temperature. With an increase in the input fluid temperature, the output temperature also increases proportionally. Increasing the inlet temperature affects the temperature of the absorber surface, which, in turn, reduces the electrical efficiency of the photovoltaic system. These changes are reduced by adding nanofluids to the photovoltaic system.Although the increase of nanoparticles causes a decrease in the temperature of the absorber plate, and this temperature decrease for copper nanofluid is 10% higher than that of aluminum oxide and pure water until the volume fraction is reached.

Energetic, Exergetic, and Techno-Economic Analysis of A Bioenergy with Carbon Capture and Utilization Process via Integrated Torrefaction–CLC–Methanation

Bioenergy with carbon capture and storage (BECCS) or utilization (BECCU) allows net zero or negative carbon emissions and can be a breakthrough technology for climate change mitigation. This work consists of an energetic, exergetic, and economic analysis of an integrated process based on chemical looping combustion of solar-torrefied agro-industrial residues, followed by methanation of the concentrated CO2 stream with green H2. Four agro-industrial residues and four Italian site locations are considered. Depending on the considered biomass, the integrated plant processes about 18–93 kg h−1 of raw biomass and produces 55–70 t y−1 of synthetic methane. Global exergetic efficiencies ranged within 45–60% and 67–77% when neglecting and considering, respectively, the valorization of torgas. Sugar beet pulp and grape marc required a non-negligible input exergy flow for the torrefaction, due to the high moisture content of the raw biomasses. However, for these biomasses, the water released during drying/torrefaction and CO2 methanation could be recycled to the electrolyzer to eliminate external water consumption, thus allowing for a more sustainable use of water resources. For olive stones and hemp hurd, this water recycling brings, instead, a reduction of approximately 65% in water needs. A round-trip electric efficiency of 28% was estimated assuming an electric conversion efficiency of 40%. According to the economic analysis, the total plant costs ranged within 3–5 M€ depending on the biomass and site location considered. The levelized cost of methane (LCOM) ranged within 4.3–8.9 € kgCH4−1 but, if implementing strategies to avoid the use of a large temporary H2 storage vessel, can be decreased to 2.6–5.3 € kgCH4−1. Lower values are obtained when considering hemp hurd and grape marc as raw biomasses, and when locating the PV field in the south of Italy. Even in the best scenario, values of LCOM are out of the market if compared to current natural gas prices, but they might become competitive with the introduction of a carbon tax or through government incentives for the purchase of the PV field and/or electrolyzer.

Global Trends in Electric Vehicle Battery Efficiency and Impact on Sustainable Grid

Over the past decade, transportation electrification has emerged as a pivotal focus of the article. Electric vehicles (EVs) have progressively gained traction in the market, displacing conventional internal combustion engine vehicles. This surge in EV popularity has led to a corresponding increase in the number of charging stations, thereby significantly influencing the power grid (PG). Various charging strategies and grid integration approaches are being devised to mitigate the potential negative impacts of EV charging while optimizing the advantages of integrating EVs with the grid. This paper provides a comprehensive overview of the current state of the EV market, standards, charging infrastructure, and the PG’s response to the impact of EV charging. The article provides a comprehensive assessment of how forthcoming advancements in EV technology, including connected vehicles, autonomous driving, and shared mobility, will intricately influence the integration of EVs with the PG. Ultimately, the article concludes by meticulously analyzing and summarizing both the challenges and recommendations pertinent to the prospective expansion of EV charging infrastructure and grid integration. The proliferation of venture capital investments in nascent start-up ventures specializing in EV and battery technologies has experienced a pronounced surge, reaching an impressive sum of nearly USD 2.1 billion in 2022. This notable increase represents a substantial uptick of 30% compared to the figures recorded in 2021. Furthermore, these investments have been directed towards two key areas: advancements in battery technology and the acquisition of critical minerals. This discernible shift in investment trends underscores the growing recognition of the strategic importance and potential profitability associated with innovations in EV and battery technologies. In 2022, global expenditures on EVs surpassed USD 425 billion, marking a substantial 50% increase compared to the previous year, 2021. Remarkably, a mere 10% of these expenditures can be attributed to governmental support, with the bulk stemming from consumer investments.

An adaptive methodology based on predictive deep learning and context aware clustering for electricity power usage mining and optimization at different granularity levels

Smart metering in electricity power grid is an optimistic trend at global level. All smart devices and appliances based on Internet of Things (IoT) are now playing very significant role in household. These days’ electric power usage mining and optimization is possible down to meter level only. However, it is very challenging and significant to go down to different granularity levels such as appliances, various sensors and activities etc. The shifting of the electric power usage to low price electricity is also significant and possible by mining and optimizing electric power usage behaviour at low level. All smart appliances and activities are needs to be customized to when you use them. This paper proposes an adaptive methodology based on predictive deep learning and context aware clustering to discover new ways for mining and optimization of electric power usage at different granularity levels and make optimal decisions for shifting electric power usage to low cost. Here we have considered households and business meters approximately 2000 with unique id of each meter. The data of three months is used for user preference of starting appliance. The predictive accuracy of proposed methodology for usage mining and optimization is improved by average 4 %. Different input data features are used to form clusters of meters with similar power consumption behaviour for household occupancy. The clustering accuracy for household occupancy is improved from 0.68 to 0.91. The impact of accurate household occupancy detection and appliance usage mining and optimization is in reduction of electric power cost. The consumer can see how electric power efficiency and time-of-use shift makes a difference using experimental setup.

Imidazolium bromide based dual-functional redox mediator for the construction of dendrite-free Li-CO2 batteries

Rechargeable lithium-carbon dioxide (Li-CO2) batteries have emerged as a highly promising approach to simultaneously address energy shortages and the greenhouse effect. However, certain limitations exist in Li-CO2 batteries like high charge overpotential and unstable Li metal interface, which adversely affect the energy efficiency and cycling life. The incorporation of soluble redox mediators (RMs) has proven effective in enhancing the charge transfer between lithium carbonate (Li2CO3) and cathode, thereby substantially reducing the charge overpotential. Nevertheless, the severe shuttle effect of RMs results in the reactions with Li anode, not only exacerbating the corrosion of Li anode but also leading to the depletion of RMs and electrical energy efficiency. In this work, an organic compound containing large cation group, 1-ethyl-3-methylimidazole bromide (EMIBr) is proposed as the defense donor RM for Li anode in Li-CO2 batteries to address the above problems simultaneously. During charging, Li2CO3 oxidation kinetics can be accelerated by bromide anion pair (Br3−/Br−). Meanwhile, the cations (EMI+) are preferentially adsorbed around the protruding tips of Li anode through electrostatic interaction driven by surface free energy, forming protective layers that effectively inhibit further Li deposition at these tips, which is verified by DFT calculations. Additionally, Li dendrites growth is inhibited by the electrostatic repulsion of polar groups in EMIBr, resulting in uniform Li deposition. Consequently, a lower overpotential (∼1.17 V) and a longer cycle life (∼200 cycles) have been obtained for Li-CO2 battery incorporating EMIBr.

Enhancing energy efficiency in tyre pressure and temperature monitoring systems

This study addresses the pivotal challenge of enhancing power efficiency in tyre pressure and temperature monitoring systems (TPMS) for heavy vehicles and trailers. Employing field-programmable gate arrays (FPGA) and adaptive channel frequency hopping in bluetooth low energy (BLE) communication, the research focuses on mitigating power consumption issues specific to heavy vehicles with multiple tyres. The proposed solution incorporates strategic BLE channel blocking and adaptive frequency hopping on the FPGA platform to alleviate channel congestion and interference, ultimately reducing TPMS power consumption. The FPGA's adaptability tailors frequency hopping strategies to automotive TPMS nuances, optimizing channel selection and minimizing energy-intensive processes. Empirical results showcase a significant reduction in power consumption, with the TPMS operating at 100 MHz during active mode consuming 66 mW, dropping to 11 mW in sleep mode, and reaching 0 mW in hibernate mode for the majority of operational time. This research establishes a practical FPGA-based approach for power optimization in commercial TPMS, promising heightened reliability, safety improvements, and environmental impact reduction in the automotive sector.

Review of Control Strategies for Improving the Photovoltaic Electrical Efficiency by Hybrid Active Cooling

Photovoltaic (PV) cooling systems are used widely in order to increase the PV efficiency. Most review paper was published for the role, design and cooling techniques of PV applications, there is a lack of collected and organised information regarding the latest and the newest updates on control strategies for PV cooling control systems. Hence, this paper presents a comprehensive review of PV cooling control strategies discussing the latest research works during the years from 2010 to 2022. PV/T hybrid cooling types are highlighted, followed by the main focus of this paper an extensive review of the control schemes for diverse types of PV cooling systems that have been carried out. This paper summarises most of the related work and also pays a special focus on research trends regarding the control of PV cooling systems that have been previously published in the literature. This review paper will be helpful to new researchers when identifying research directions for this particular area of interest.

Performance augmentation of photovoltaic solar chimneys using asphalt material

AbstractIn this study, an experimental model of a photovoltaic (PV) solar chimney (SC) was built and study the extent to which the asphalt material, being a phase‐change material, affects its performance electrical and thermal. Results were taken for the two systems: The photovoltaic solar chimney which contains phase change material (SCPV‐PCM), and the photovoltaic solar chimney which does not contain phase change material (SCPV). The finding demonstrated that the PCM affects the SCPV electrical and thermal performance; the results were as follows: The electrical power for the SCPV‐PCM system increased during the day and its highest value at noon was 384.34 W, and then it began to decrease. The SCPV system had a higher power at the end of the test, 73.24 W, due to the lower temperature of the PV panel. The highest electrical efficiency was for the SCPV‐PCM system at the beginning of the test, reaching the highest value of 13.12%, then it decreased at the end of the test to be less than the SCPV system at 5:00 pm. The thermal efficiency of the SCPV‐PCM arrangement is lesser than the arrangement that does not contain PCM, reaching its highest value at noon, which was 57.1% for the SCPV system. The total efficiency of the SCPV‐PCM system is lesser than the SCPV system from the beginning of the test until 3:30 pm approximately, reaching its highest value of 68.05% at noon.

The future of exergy-based methods

Exergy-based methods consist of at least an exergetic analysis, which can be combined with an economic analysis and a life cycle assessment in order to evaluate and improve energy-intensive processes. The author coined the term exergoeconomics in 1984 to replace the term thermoeconomics when exergy costing is used in the combination of an exergetic analysis with a cost analysis and to emphasize the role of exergy in the efforts to reduce the product cost. He also developed a general exergoeconomic methodology based on exergy-based variables and on appropriate definitions of the “product” and “fuel” for each component of an energy conversion system. These definitions and the application of exergoeconomics were generalized by A. Lazzaretto and the author in 2006 in an approach based on specific costs (SPECO approach).L. Meyer and the author coined the term exergoenvironmental analysis in 2009 for the combination of an exergy analysis with a life-cycle analysis when exergy is used to assign environmental impacts to streams. An exergoenvironmental analysis uses the methodological background of exergoeconomic methods.Starting in 2002, to reduce the limitations of the conventional exergy-based methods, and to facilitate system optimization, the author, and later in cooperation with T. Morosuk and co-workers at TU Berlin, developed the advanced exergy-based methods, which are based on the notion that the inefficiencies (exergy destruction and exergy loss), the costs, and the environmental impacts can be split into avoidable/unavoidable and endogenous/exogenous parts, to improve understanding of the formation process of inefficiencies, costs and environmental impacts within an energy conversion system.As often happens, after their introduction, all the above terms and methods have been misused and misinterpreted by some other authors.This paper briefly reviews past contributions by the author and some other exergy practitioners and discusses future developments. It concludes, that the advanced exergy-based methods need further development to be generalized, and integrated and to reduce their subjectivity in addition to the efforts and time required for their application. Development of appropriate software and shortcut methods will facilitate their use by researchers and engineers in industry and the application of exergy-based methods in energy-intensive industrial processes for multiobjective optimization purposes.

Performance characterization of nano-enhanced PV/T systems in various cross-sections, extended flow turbulators, fins, and corrugated patterns

Photovoltaic thermal (PV/T) systems may generate both heat and electricity from the sun. Modifying the collector's thermal performance by passive methods is a reliable approach to making them more effective. This study compares the impact of different cross-sections, extended surface turbulators, fins, and corrugated patterns based on the ISO criterion when the working fluid is enriched by MWCNT-water nanofluid at φ=0.3%. The multi-angle yet passive techniques used here, including the nanofluid in Longitudinal Fin (LF), Flat Plate Turbulator (FPT), Wedge Plate Turbulator (WPT), Triangular Corrugated Channel (TCC), and Wavy Corrugated Channel (WCC), and smooth channels, improve the optical efficiency (η0) and reduce the heat-loss coefficient (a1) by 6.8 % and 19.6 %, 12.5 % and 29.3 %, 12.5 % and 27.7 %, 11.7 % and 23.6 %, 10.81 % and 22.9 %, and 3.2 % and 10.71 % compared to the base case (i.e., the smooth channel with pure water) respectively. Pump power in WCC, TCC, and LF is negligible, leading to enhancement in electrical efficiency (ηelec) up to 4.7 % for the former two and 2.9 % for the latter cases. However, plate turbulators show a decline in ηelec at higher inlet velocities due to increased pressure drop. A parametric study of FPT reveals that reducing height and periodic ratios effectively decreases pump power while slightly affecting the performance parameters (η0anda1). The system's performance is also evaluated using the overall exergy efficiency (ηex,ov) concept. The study finds the FPT configuration with the highest ηex,ov of 16 %.

Sustainability and environmental impact in the LNG value chain: Current trends and future opportunities

The liquefied natural gas (LNG) industry plays a crucial role in the global energy landscape, offering a cleaner alternative to traditional fossil fuels. However, the LNG value chain presents environmental challenges that must be addressed to ensure long-term sustainability. This paper examines current trends and future opportunities for enhancing sustainability and reducing environmental impact across the LNG value chain. The LNG value chain comprises several stages, including natural gas extraction, liquefaction, transportation, regasification, and distribution. Each stage presents unique sustainability challenges, such as methane emissions during extraction and transportation, energy-intensive liquefaction processes, and the carbon footprint of regasification and distribution. Current trends in the LNG industry focus on mitigating these challenges through various strategies. These include the adoption of advanced technologies for methane detection and reduction, the use of renewable energy sources for liquefaction, and the implementation of efficient regasification and distribution practices. Additionally, there is a growing emphasis on stakeholder engagement, transparency, and reporting to enhance sustainability performance across the value chain. Future opportunities for improving sustainability in the LNG value chain lie in the continued development and deployment of innovative technologies. These include carbon capture and storage (CCS) technologies to reduce emissions, the use of renewable natural gas (RNG) as a feedstock, and the integration of LNG with renewable energy sources to create hybrid energy systems. Addressing sustainability and environmental impact in the LNG value chain requires collaboration among industry stakeholders, governments, and regulatory bodies. By implementing best practices, embracing innovation, and prioritizing sustainability, the LNG industry can continue to play a vital role in the transition to a cleaner and more sustainable energy future.

The safety and environmental impacts of battery storage systems in renewable energy

The integration of battery storage systems in renewable energy infrastructure has garnered significant attention due to its potential to enhance energy reliability, efficiency, and sustainability. However, alongside these benefits, concerns persist regarding the safety and environmental impacts associated with the deployment and operation of such systems. This review explores the multifaceted aspects of safety and environmental considerations in battery storage systems within the context of renewable energy. Firstly, safety concerns encompass a range of factors, including thermal runaway, fire hazards, and chemical leakage, which pose risks to both human life and property. Mitigation strategies such as advanced battery management systems and fire suppression technologies are critical for addressing these risks effectively. Secondly, environmental impacts arise throughout the lifecycle of battery storage systems, from raw material extraction to end-of-life disposal. Key issues include resource depletion, greenhouse gas emissions, and pollution from mining activities. Sustainable practices such as responsible sourcing of materials, recycling initiatives, and the development of second-life applications are essential for minimizing environmental footprints. Furthermore, the interaction between battery storage systems and renewable energy sources introduces complexities in assessing environmental impacts. While battery storage facilitates the integration of intermittent renewables like solar and wind by providing grid stabilization and energy storage capabilities, its environmental benefits may be compromised by factors such as energy-intensive manufacturing processes and reliance on non-renewable resources. The safety and environmental impacts of battery storage systems in renewable energy demand comprehensive evaluation and management strategies to maximize benefits while minimizing risks. Collaboration among stakeholders, technological innovation, and regulatory frameworks are crucial for promoting the sustainable deployment and operation of these systems in the transition towards a cleaner and more resilient energy future.

Can machine learning predict environmental attitudes and beliefs?

ABSTRACT Beliefs and attitudes regarding climate change significantly influence public support for environmental policy regulations and willingness to engage in voluntary actions. This paper endeavours to forecast public perceptions concerning global warming, anthropogenic climate change, support for environmental tax policies, and the inclination to purchase energy-efficient home appliances. Leveraging data from the European Social Survey, we employ four machine learning techniques to anticipate individuals’ environmental beliefs and attitudes. Across various settings, our analysis achieves an accuracy of over 70% in identifying environmentally conscious respondents.

Hydrogen as Fuel of Tomorrow

As well know that carbon-based fossil fuels are a non- renewable resource and these are depleting at an alarming rate. The unmonitored explicit usage of fossil fuels certainly demands for an alternate type of fuel which could replace it in the future because not today but in the near future there will come a time when we will be short on carbon based fuels and need for an alternative type of fuel will the demand of the day. The increasing global demand for sustainable and clean energy sources has finally demanded the exploration of alternative fuels. Hydrogen, with its high energy density and zero carbon and greenhouse gas emissions during combustion, has emerged as a promising fuel of the future. Hydrogen is a potential fuel which can change our fossil fuel based dependency for energy generation to hydrogen economy. The various properties of hydrogen make it excellent alternative and soon to be primary source of fuel in the future. The various techniques of hydrogen production such as electrolysis and coal-based extraction will be discussed as well as the storage methods. Hydrogen is a better fuel in every term. There will be comparative study as well which compares the versatility, the combustion properties, electrical generation efficiency, thermal usage efficiency and also that it’s extraction methods are certainly more eco friendly as compared to other fossils fuels. Researchers are still going to make hydrogen as feasible as fossil fuels are today and soon in the upcoming years, we will see hydrogen economy booming. Keywords—Hydrogen, electrolysis, fuel, efficiency, fuel cell

Mixed Fe-Mo carbide prepared by a sonochemical synthesis as highly efficient nitrate reduction electrocatalyst

Ammonia, a versatile compound that can be used as a fertilizer, chemical or fuel, has since long been produced through the energy-intensive Haber-Bosch process. Recently, the electrochemical nitrate reduction reaction (NO3RR) using electricity generated from renewable sources has attracted widespread attention. However, the complex reaction pathway of NO3RR leads to the formation of many undesirable by-products. Herein we successfully prepared a mixed (FeMo)2C catalyst with good electrocatalytic NO3RR, having a NH3 yield of 14.66 mg h-1 cm-2 and an FE of 94.35% at low potential -0.3 V vs RHE. DFT calculations show that the presence of Fe in Mo2C lattice changes the reaction mechanism, decreasing the potential barrier to be overcome from 1.36 to 0.89 eV. In addition, mixed Fe-Mo carbide facilitates the adsorption of intermediates and promotes NH3 desorption, facilitating NO3− reduction to NH3. In addition, (FeMo)2C was used as cathode for Zn-NO3 battery to generate electricity, producing ammonia at the same time, with a power density of 3.8 mWcm-2 and an NH3 FE of 88%. This work describes a new synthesis method for mixed metal carbides and provides a promising strategy for NH3 production.

Investigation on different cooling strategies for photovoltaic thermal Systems: An experimental study

Since the convection in air photovoltaic/thermal systems (PV/Ts) is weak, this study analyzes different cooling strategies experimentally to improve the thermal/electrical efficiency of PV/Ts. Hence, a PV/T was fabricated and tested outdoors, considering three cooling strategies: unbaffled, solid baffled, and perforated baffled PV/Ts at two flow rates of 0.092 kg/s and 0.17 kg/s. Perforated baffles are a robust, novel method that improves convection, reduces PV temperature, and enhances efficiency. Furthermore, the lower the PV temperature, the higher the electrical efficiency. The experimental data reveal that the peak PV temperature in the perforated baffled scenario falls by nearly 15.6 % and 17.5 % compared to that in the unbaffled scenario at the flow rates of 0.092 kg/s and 0.17 kg/s, respectively. However, the outlet temperature increases in the baffled scenarios compared to the unbaffled one due to improvement in the convection mechanism. Using the solid and perforated baffles increases the peak outlet temperature by nearly 7.22 % and 12.38 % at the flow rate of 0.17 kg/s. Furthermore, the overall efficiency in the solid and perforated baffled PV/Ts improves by 17.29 % and 39.78 % compared to the unbaffled one at the flow rate of 0.17 kg/s. Hence, using perforated baffles is a strong method to boost the efficiency of PV/Ts.

Contact force and pressure analysis of the three-row roller pitch bearing in a large-scale wind turbine

Pitch bearings are the key components of wind turbines (WTs). The reliability of pitch bearings affects the electric energy output efficiency of WTs. Due to its large loading ability, constant contact angle and high stiffness, the three-row roller slewing bearing (TRSB) is becoming a more attractive choice as a pitch bearing, especially in large-scale WTs. The contact force and pressure distributions significantly affect the fatigue life of a three-row roller pitch bearing (TRPB). Therefore, it is essential to propose a precise calculation method for the contact force and pressure. The present work establishes a quasi-static five degree-of-freedom (DOF) mathematical model for TRPBs, in which the bearing under general loading conditions is considered. The influences of combined external forces, overturning moments and inner ring misalignment angle on the contact force and pressure distributions of TRPBs are comprehensively investigated. According to the analysis results, the overturning moment and axial force can significantly affect the number of load-carrying rollers in each row. Furthermore, a slight variation of the inner ring angular misalignment has a significant effect on the contact force and pressure of TRPBs. Finally, it is more prone to pressure concentration in the non-crowned roller than that in the crowned roller, especially in the case of the inner ring with a misalignment angle. Since the high calculation efficiency and accuracy, the proposed method has remarkable potential applications in the fatigue life prediction and design of TRPBs.