Power Cost Research Articles

Stability Assessment and Reactive Power Compensation Strategies for Grid-Connected Wind Power Generations

With the acceleration of global economic integration and the rapid increase in population, the reserves of mineral resources on the earth are becoming increasingly scarce, and non-renewable resources are becoming increasingly scarce. Technological advances have significantly reduced the cost of photovoltaic and wind power, improved energy storage efficiency and smart grid technology, and solved the intermittent problem of new energy. How to boost the utilization rate of new energy and ensure its secure and reliable operation during grid connection is an important challenge that the current development of electric power technology must tackle. To serve as a guide for the creation of new wind power, this article analyses the two most widely used reactive power compensation devices, studies the method of restoring the stable state through reactive power compensation after the grid-connected wind power becomes unstable, and introduces several control methods for power compensation using reactive power compensation devices. The main objective of this article is to summarize the current mainstream stability assessment methods in the world and compare their benefits and drawbacks.

Ultrafast Coherence-Based Power Doppler Estimation Using Nonlinear Compounding With Complementary Subset Transmit.

Conventional coherent plane wave compounding (CPWC) and sum-of-square power Doppler (PD) estimation lead to low contrast and high noise level in ultrafast PD imaging when the number of plane-wave angle and the ensemble length is limited. The coherence-based PD estimation using temporal-multiply-and-sum (TMAS) of high-lag autocorrelation can effectively suppress the uncorrelated noises but at the cost of signal power due to the blood flow decorrelation. In this study, the TMAS PD estimation is incorporated with complementary subset transmit in nonlinear compounding (DMAS-CST) to leverage the signal coherence in both angular and temporal dimensions for improvement of PD image quality. The CST correlation can be performed not only within the same Doppler ensemble (i.e., intra-correlation) but also across the adjacent Doppler ensembles (i.e., inter-correlation) to increase the number of correlation pairs in TMAS PD estimation. In both simulations and experiments, DMAS-CST is capable of improving the contrast of TMAS PD image by over 10 dB compared to the nonlinear compounding alone by enhanced noise suppression and lower flow decorrelation. When the CST correlations are performed both intra and inter Doppler ensembles, the noise level further reduces in DMAS-CST. Since the TMAS PD estimation is often limited by the loss of signal power due to temporal decorrelation, the design of complementary subsets in DMAS-CST should be carefully examined to preserve the blood flow signal. Future work of this study will focus on how to combine the conventional PD and the TMAS PD for better signal preservation and effective noise suppression.

تحسين الطاقة لشبكات الاتصال اللاسلكي ذات الطبقتين: نهج قائم على خوارزمية تحسين سرب الجسيمات (PSO)

One of the most challenges for future wireless communication networks is energy consumption. Heterogeneous networks, which are built to handle the increasing need for high data traffic, are one of the most promising strategies to address these challenge in future cellular networks. Network coverage may be increased by adding more base stations, but this comes with a high power cost. In the two-tier network concept, small cells (SCs) work along with main cell stations (MCs) to provide wider coverage. Some SCs experience low traffic rates due to user equipment's (UEs) mobility, yet they still consume a considerable amount of energy. To save energy and increase energy efficiency (EE), some SCs must be turned off. This study extends the operation modes for BSs and introduces a bio-inspired mechanism to select the optimal operation mode for each SC. A bias factor is used to regulate power consumption, with SCs operating in one of four modes: On, Standby, Sleep, or Off. The EE maximization problem is defined under a set of limitations and a Variant Power Mode Selection (PSO-VPMS) based on Particle Swarm Optimization Algorithm is proposed in this study. The simulation findings show that the suggested algorithm scheme offers a high EE. Keywords: two-tier network; energy efficiency (EE); bias factor; Particle Swarm Optimization (PSO).

Assessing the usage of end-of-life tire pyrolysis oil as an alternative fuel in a diesel engine in the point of energy, exergy, exergoeconomic, exergoenviroeconomic, and sustainability parameters

ABSTRACT The present study examines the utilization of fuel blends comprising waste tire pyrolysis oil (WTPO) at varying ratios (10%, 20%, 30%, and 40%) in a compression-ignition (CI) engine at different loads (25%, 50%, 75%, and 100%). This is with a view to elucidating the performance and emission characteristics of the blends in detail. The performance and emission data were subjected to detailed analysis. Energy, exergy, exergoeconomic, exorgoenviroeconomic, and sustainability analyses were conducted with the objective of comparing the fuel blends. Based on these analyses, the energy dissipation of the engine, exergy losses, cost of power from the engine shaft, and sustainability index (SI) were calculated for each fuel at all operating conditions. As the fraction of WTPO in the fuel blends increased, fuel consumption increased and energetic efficiency declined owing to the lower energy content of the alternative fuel additive. As the percentage of WTPO in the fuel blends increased gradually, the exergy losses increased, resulting in a decline in exergy efficiency. At the highest load, the exergetic efficiency of TP20 was found to be 5.65% higher than that of TP40. Given that the cost of traditional diesel fuel (D100) was 73.3% higher than WTPO, the cost of power from the engine shaft decreased as the WTPO ratio ascended in the blends. Consequently, the aforementioned parameter for TP10 was calculated to be 144.55 $/GW at a load of 75% while 120.90 $/GW was found for TP40. The greatest quantity of CO2 released into the environment was 11,512.4 kg CO2/month in TP40 at the highest load. Under the same conditions, it was calculated as 5,958.2 kg CO2/month for D100. In the context of an SI based on load, a reduction of 5.89% was observed in the case of conventional D100 in comparison with TP40 in the CI engine operating at full load. The findings of the present examination indicate that WTPO may be a viable alternative fuel for CI engines running on D100.

Research on Energy Savings through Floating DO Measuring Device in SBR Wastewater Treatment Method

Objectives : The objective of this study is to propose an optimal operational control method to ensure stable effluent water quality and reduce treatment costs in the SBR(Sequencing Batch Reactor) wastewater treatment process. In particular, the study aims to maintain the dissolved oxygen(DO) concentration required for microorganisms while reducing power costs associated with excessive aeration.Methods : To address issues with conventional fixed DO sensors, such as scum formation, inaccuracies caused by bubbles and strong flow velocities during aeration, and reduced reliability due to fluctuating water levels, a floating DO sensor was introduced to measure DO concentrations in real-time. Based on these real-time measurements, the optimal DO concentration required for microbial activity was calculated, and a system was designed to automatically control the airflow rate set value(SV) of the turbo blower.Results and Discussion : The application of a single-variable DO control method effectively reduced the power consumption required for aeration in the SBR aeration tank. This approach prevented energy waste caused by excessive aeration while maintaining the appropriate DO concentration needed for microbial activity. These results demonstrate that the proposed method improves the reliability and efficiency of the system.Conclusion : The real-time DO control method using a floating DO sensor enables energy savings and ensures stable effluent water quality in the SBR process. The proposed method overcomes the limitations of conventional fixed DO sensors, contributing to reduced power costs and improved process efficiency.

A framework for optimal agent deployment and opportunistic routing in flying Ad-Hoc networks for precision weather forecasting

Drone based precision weather prediction and forecasting is a prevailing area of research in recent times. Modern flying ad-hoc network (FANET) leverages advanced low latency communication protocol between small flying drones and base stations. In this work, a FANET framework for efficient and precision weather prediction and forecasting that leverages ultra low latency opportunistic message transfer protocol (MTP) is proposed. An, edge empowered intelligent computing quasi-stationary sink nodes are employed to develop the FANET ecosystem further. Flying sensor nodes and edge computing quasi-stationary sink nodes are deployed in the target area in order to achieve optimal sensor coverage minimizing the cost of data transmission power thus ensuring long endurance operation of drones. An ensemble model is deployed in edge level for localized weather prediction. Opportunistic routing strategies are utilized for converge casting. The experimental results show the maximum of 0.98 message delivery ratio and a minimum of 820 ms latency is achieved through opportunistic MTP. An accuracy of 96.5% is achieved in predicting the temperature and humidity data metric.

The Effect of Wind Turbines’ Load Factor on the Overall Cost of Electricity

Abstract The load factor of wind turbines has a strong effect on the wider electricity system. As the rated wind speed of turbines reduces, the load factor increases. This allows wind farms to generate constant power for longer periods of time, which in turn improves the match between the profiles of electricity demand and renewable generation and reduces the need for energy storage. The behaviour of the total cost of electricity is driven largely by the levelized cost of wind power, which has a minimum at a rated speed of 12 m/s. Faster rated speeds (>12 m/s) lead to higher electricity costs due to the lower load factors of the turbines. At slower rated speeds (<12 m/s) the higher capital cost of the turbines overshadows the improved load factors, leading to increased electricity costs.

Advances in Deep Reinforcement Learning for Computer Vision Applications

Deep Reinforcement Learning (DRL) has become very popular for computer vision (CV), solving mostly visually complex environments with decision making and dynamic adaption to different situations. This article provides an introduction to the basic concepts of deep reinforcement learning with a special focus on their applications in computer vision tasks, including challenging problems and emerging solutions. It reviews various DRL algorithms such as Q-learning, policy gradient methods, and Actor-Critic models, explaining much of the modifications that are done to make it work on high-dimensional visual problems. Different applications of DRL in major CV applications like object detection, image segmentation, target tracking and image generation are reviewed to demonstrate the power as well as limitations of DRL in practice. More importantly, the novel paradigms such as hierarchical policy learning, adaptive reward design multi-task reinforcement learning and domain adaptation can be viewed as promising premises to improve model efficiency and generalizability in multiple scenarios. Finally, this paper mentions a few of the existing challenges like computational power cost and sample efficiency; as well as future paths for enhancing that can widen devout reinforcement learning in computer vision. Through this comprehensive overview, we aim to shed light on the promising synergies between DRL and CV, while identifying key areas for future research and application.

Modelling of Harris Hawks optimization with deep learning-assisted microgrid energy management approach

Microgrid (MG) is a potential decentralized energy distribution and generation technology that is resilient, reliable, and efficient. This small-scale power system is reliable and resilient since it connects to the grid or runs independently. Renewable energy is difficult to integrate into MG due to variable load and unreliable electricity. MG operation relies on an energy management system (EMS) to balance electricity demand and supply, reduce operational costs, and maximize renewable energy use. Intelligent control systems, optimization methods, and machine learning algorithms were used for MG EMS. The Harris Hawks optimization with deep learning-assisted microgrid energy management (HHODL-MGEM) technique is developed in this work. HHODL-MGEM comprises two main stages. In the first step, the HHODL-MGEM approach uses the Harris Hawks optimization or HHO algorithm to meet load power demands at a low cost while maintaining DC bus voltage and protecting the battery from overcharging and depletion. In the second step, long short-term memory (LSTM) networks can predict power costs. The HHODL-MGEM approach is evaluated using multiple methods. The experimental results showed that HHODL-MGEM outperforms other methods.

Energy Aware Optimal Virtual Machine Scheduling in Cloud Environment Using Hybridized Egret Swarm with Sea Lion Optimization Algorithm

With emergence of advanced technologies, the internet plays as the essential role to share the information across the world. With emergence of large number of users, the data quality gets affected thus; it leads to cause burden in scheduling where it provides fewer services to the users. Due to this existence, the cloud computing technology emerges to offer better services. Certainly, the optimal scheduling process of a Virtual Machine (VM) becomes challenging in the larger size of data in cloud environments. Modern systems and data centers place a high priority on energy consumption. Thus, it provides poor performance regarding energy usage and throughput analysis marked in the traditional techniques. In order to consider aforementioned issues, a novel VM scheduling mechanism is introduced for allocating and managing resources in cloud. The major scope of this developed VM scheduling process tends to minimize energy consumption. The developed Hybrid Egret Swarm-based Sea Lion Optimization (HES-SLO) algorithm is implemented to allocate resources based on several objective functions like execution time, energy or power consumption, cost, and resource utilization. Thus, the overall performance analysis takes place, where the developed VM scheduling model is compared with the traditional VM allocation mechanisms to verify the efficacy. In this validation, the HES-SLO attains 21.16%, 4.903%, 0.17%, and 7.86% for energy consumption, resource utilization, execution time, and throughput analysis. Based on the entire validation, it shows greater performance by compared with existing approaches.

Iron complex with multiple negative charges ligand for ultrahigh stability and high energy density alkaline all-iron flow battery

Alkaline all-iron flow batteries (AIFBs) are highly attractive for large-scale and long-term energy storage due to the abundant availability of raw materials, low cost, inherent safety, and decoupling of capacity and power. However, a stable iron anolyte is still being explored to address complex decomposition, ligand crossover, and energy density to improve battery performance. Herein, a promising metal-organic complex, Fe(NTHPS), consisting of FeCl3 and 3,3',3''-nitrilotris(2-hydroxypropane-1-sulfonate) (NTHPS), is specifically designed for alkaline all-iron flow battery. The NTHPS exhibits strong binding strength with iron ions, resulting in ultrahigh stability during the charge-discharge process. AIFB based on the [Fe(CN)6]4- catholyte and Fe(NTHPS) showcases an exceptionally high capacity retention of 97.8% after 2000 cycles (0.0011% per cycle), maintaining high coulombic efficiency near 100%. Furthermore, with a solubility as high as 1.82 mol L-1, the Fe(NTHPS) anolyte demonstrates an ultra-high theoretical capacity of 47.23 Ah L-1. This multiple negative charges ligand not only resolves existing barrier associated with AIFBs, but also provides valuable insight for their commercial application.

Flashlight-Induced Ultrafast, Scalable Surface Activation of Highly-Loaded Graphite Composite Anode

Numerous substantial challenges persist in achieving widespread and pragmatic applications of LIBs, including further improvements in energy and power density, safety, and cost reduction. One of the many efforts to address them is to increase the loading level of electrodes. This can not only improve energy density per unit area, but also dramatically lower the cost of the battery pack by reducing the stacking number of cells and the use of inactive components such as current collectors and separators. However, contrary to the expectation of such a positive effect, it had been shown that increasing the loading level, i.e., the thickness of the electrodes often resulted in a degradation of the electrochemical properties of the cell. For a thick electrode, a large amount of solvent is volatilized when drying, causing more binder to migrate to the electrode surface, and the paths that the lithium ions and electrons travel become longer and more tortuous. These lead to inhibition of lithium ion diffusion and the accumulation of a solid electrolyte interface (SEI) layer and dead lithium at the interface between the electrode/electrolyte, and consequent degradation of cell performance such as rate capability.Several emerging materials with enhanced electronic and ionic conductivity are being developed to overcome the performance degradation arising from thickened electrode, but their practical use is hampered by the long time required to verify mass production and performance reliability. Another approach is to build thick electrodes into a three-dimensional (3D) porous structure that is effective for ion and electron transfer. Specially, anisotropic structure with vertical microchannels serving as the high transport pathway had known to enhance the electrolyte permeability into the electrode and alleviate the resistance to ion migration at the electrolyte-electrode interface. This promoted lithium ion diffusion within thick electrode, allowing enhanced rate capability and high volumetric capacity. resulting in improvement of rate capability, and magnetic templating or laser ablation are commonly used to create them. However, for these technologies to be implemented in the battery manufacturing industry, there are still issues that need to be solved, such as a complex and time-consuming manufacturing process, incompatibility with roll-to-roll process and significant loss of active material due to structuring. Therefore, it is important to develop more effective strategy to overcome the limitations in thick electrodes.From this perspective, in this study, we explored a new and efficient way to address the challenges posed by highly-loaded graphite composite anode using a flash annealing process that is roll-to-roll compatible and capable of large-area processing. When a flashlight is irradiated on the surface of a high-energy-density electrode for less than a second, the light energy absorbed by the graphite active material and conductive carbon additives can be converted to thermal energy. At this time, the surrounding binder can undergo an instantaneous carbonization reaction by the heat, which eventually can form into a porous carbon nanostructure. In addition, some of the weakly bound active material can be cleaned away from the surface, creating pores and bumps on the electrode surface. These changes of electrode surface derived from the interaction with the flashlight can contribute to easier penetration of the electrolyte, increased reaction surface area and improved conductivity, which can lower the transfer resistance of electrons and lithium ions in a thick anode. To confirm these effects, the structural and chemical changes on the electrode surface after irradiation with flashes of different energies were closely analyzed, and the improvement in electrochemical properties such as performance stability and rate capability was confirmed by implementing flash-treated highly loaded graphite anode over 3.6 mAh/cm² into half-cell. Functionalization of the electrode surface using flashlight is not only effective in improving the electrochemical performance degradation caused by the adoption of thick electrodes, but also has the advantage of being compatible with the roll-to-roll process which is mainly adopted by the battery manufacturing industry, as it can be performed in milliseconds on a large area. Therefore, it is expected to become a new growth engine for the battery manufacturing industry in the near future.

Enhancing Urban Energy Resilience: Vehicle-to-Grid (V2G) Strategies within Electric Scooter Battery Swapping Ecosystems

With the global rise in electric scooter adoption and the expansion of battery swapping stations (BSSs), particularly in Taiwan—home to the world's densest network of these facilities—these stations are increasingly recognized as crucial energy storage hubs that enhance grid stability. This study introduces a smart energy management system designed for optimal charge and discharge management of BSSs, using Taiwan as a practical example. Central to our approach is a vehicle-to-grid (V2G) strategy, which, through hourly resolution analyses, assesses the impacts on grid peak demand, operational costs, and emissions. Our results indicate that V2G significantly reduces peak power demand by 110.1% compared to traditional charging methods and lowers operating costs by 18.9% through energy arbitrage. Although current emission reductions are modest due to Taiwan's limited renewable installed capacity, projections demonstrate that emissions could rise by 2% without strategic emission management. Our proposed V2G strategy targets both peak shaving and low-emission charging periods, potentially reducing emissions by 12.8% and supporting national sustainability targets. Furthermore, a comparative analysis shows that V2G is effective in both urban and rural settings, with rural areas achieving greater reductions in peak power usage and costs due to their higher idle battery capacity. This emphasizes the importance of tailored energy management strategies and underscores the critical role of well-designed BSS charging strategies in moving towards a sustainable, net-zero future.

Levelized cost analysis of onshore wind-powered hydrogen production system in China considering landform heterogeneity

Harnessing wind power for hydrogen production is a promising solution to tackle the challenges of climate change. However, the high cost associated with wind-powered hydrogen production systems emerges as a significant barrier. Hence, this study aims to present an economic analysis of wind-powered hydrogen production systems, taking into account the heterogeneity of landforms. The analysis utilizes hourly wind speed data from 290 anemometer towers throughout China, providing a comprehensive and accurate assessment of wind power generation. The findings reveal that landform heterogeneity has a significant impact on the levelized cost of hydrogen (LCOH), but such impact is expected to diminish over time. Moreover, the LCOE in various provinces ranges from ¥0.31–0.52/kWh, and the LCOH ranges from ¥25.75–36.31/kg, with an average of ¥30/kg. Electricity costs and CAPEX account for over 75 % of the total hydrogen production costs. Inner Mongolia, Xinjiang, and Jiangsu exhibit the lowest LCOH due to their lower wind power costs. Furthermore, the predicted results indicate a swift descent in the LCOH from 2020 to 2030. By the years 2030 and 2060, the nationwide average LCOH is projected to reach ¥25/kg and ¥22/kg, respectively, signifying an 18 % and 28 % reduction compared to the year 2020.

Cost-Effective Approaches to Recycle Current and Future Waste Solar Modules

Recycling solar panels has been a revolutionary procedure that has affected sustainability practices in the renewable energy industry in the past, present, and future. With silicon photovoltaics contending for market share to reduce solar power costs, perovskite photovoltaics is becoming more popular. However, there is currently no practical means to manage dangerous lead Pb waste, which could spell the end of this technology. We offer a material management method for perovskite solar modules that addresses the end of their useful life. The goal is to recycle valuable transparent conductors and toxic lead to save the environment and promote the economy using recycled materials. An action plan for removing poisonous lead and precious glass substrates from perovskites-based solar panels. Organic solvents, such as dimethylformamide (DMF), dissolve lead in the perovskite layer during delamination of encapsulated perovskite solar panels. To entirely remove lead from organic solvents, an adsorbent adsorbs ions, eluted into a clean solvent for broth enrichment, and the precipitated PbI2 is collected for recycling. In this case, we used carboxylic acid cation exchange resin as an absorber to recycle lead from used perovskite modules. To reuse the used perovskite solar cells, a procedure must first be developed to unbind the encased modules and expose them to the perovskite layer. This section examined the composition of a perovskite module formed of indium tin oxide (ITO) glass and encapsulated by an additional piece of glass. Although silicon solar panels contain a large number of valuable materials, such as silicon, glass, silver, aluminum, etc., they still lack the cost-effective recycling technology that would allow them to be recovered. Silicon is incredibly diverse, but its high-value applications, such as semiconductors, require the same stringent purity requirements. However, employing it as an anode material in lithium batteries with less severe purity standards appears viable.Furthermore, abandoned solar cells have been shown to include silicon anode impurities such as boron, phosphorus, and silver, which improve their stability. There are now two phases in PV recycling: dismantling and filtration. Although silicon PV panels vary greatly, they all share the same basic construction. The sandwich construction solar cells, comprised of aluminium, silicon, and silver, are joined to modules by copper wires soldered with lead and tin (Pb and Sn). The modules are then sandwiched between two EVA layers, creating a waterproof seal.Alternative processes, like pyrolysis and chemical treatments, are used to gently peel off glass and solar cells to recycle Si and Ag by removing or extracting EVA. EVA is commonly used to coat and preserve solar cells and PV panels. This encapsulation makes it more difficult to separate the glass cover and back sheet and recycle the solar cells.Morphology conversion must be considered throughout the upcycling process, which employs nano-metal catalysed hydrofluoric acid (HF) acid etching to recover porous Si/carbon anode materials after a brief purification step. Because of the properties of silicon, HF is always used to form silicon pores, which are not meant to last. As a result, HF can be replaced in purification and morphological modification, resulting in a more environmentally friendly and long-lasting recycling process. The silicon wafer can also be recycled in all-solid-state batteries (ASSBs). This method states that after removing the perovskite and carbon, the metal oxide layers (TiO2, ZrO2) produced on the FTO can be reused to remanufacture enclosed carbon-based perovskite cells. In a solar simulator based on xenon lamps, the power conversion efficiency of perovskite solar cells and solar modules was measured using current-voltage (JV) measurement. Based on the study and comparison of solar PV production and the avoided burden approach due to recycling, it is possible to infer that recycling in the total life cycle evaluation of solar PV can result in a significantly higher impact reduction throughout the solar PV recycling process. Keywords Solar module recycling, Chemical recycling, End-of-life management, Upcycling, Circular economy, Refurbishment.

Development of Costing Model for Butt Joint Process using Mild Steel with Robotic GMAW: A Malaysian Context

This paper is about the development of a costing model aimed at determining the pricing strategy for a component manufactured through the welding process. Cost estimation in welding processes is crucial for industries due to various influencing factors like welding time, length, and joint type. Calculating welding costs involves considering various methods and factors. One method compares theoretical filling metal amounts with on-site welding material consumption, factoring in the welding difficulty coefficient. Additionally, Time Driven Activity Based Costing (TDABC) is one of the costing methods used to analyze input data and estimate welding costs accurately and efficiently, specifically in the GMAW process. Moreover, a comprehensive costing model developed by ESAB incorporates variables such as labor costs, electrode expenses, shielding gas usage, and overall power costs. In this paper, the selected welding design configuration is a double Vgroove butt joint using mild steel, ER70S-3 as filler wire, and S235 mild steel as substrate. Based on the chosen design, the welding cost model will be developed to analyze the cost of the butt joint welding process based on timedriven activity-based costing (TDABC) method. The outcome of this study is the total cost to manufacture the Double V-Groove butt joint project in terms of materials, labor, and equipment. Furthermore, subsequent efforts will be directed toward systematically enhancing the welding cost model to include a broader spectrum of materials, various part dimensions, and differing deposition rates.

Single laser based novel wavelength shift keying scheme for ground to satellite bidirectional links

Abstract Laser communication in space is gaining more recognition due to its ability to provide a much broader and unregulated data transmission capacity compared to traditional radio frequency systems, while also significantly decreasing the size, power requirements, and weight of the communication system. In this work, a novel technique for the generation of a wavelength shift keying (WSK) signal for the bidirectional transmission of 10 Gbps data between the ground station and low Earth orbit (LEO) satellite is presented. Our proposed scheme requires a single laser source to transmit WSK signal, that generally requires two wavelength sources to transmit the binary data bits. Furthermore, the scheme allows us to remodulate the optical signal received at the LEO satellite for downlink signal transmission. Therefore, the requirement of a laser source at the LEO satellite is eliminated, achieving the much desirable goals of low power consumption, weight and cost. The free space optical (FSO) channel is modelled using the gamma-gamma channel model. The performance of the proposed link is also compared with a conventional On-Off keying (OOK) based modulation scheme by using bit-error-rate (BER) as the performance metric.

Sharp PDE estimates for random two-dimensional bipartite matching with power cost function

Sharp PDE estimates for random two-dimensional bipartite matching with power cost function

Energetic and Neuromuscular Demands of Unresisted, Parachute- and Sled-Resisted Sprints in Youth Soccer Players: Differences Between Two Novel Determination Methods.

The aim of this study was to analyze the differences in terms of (1) muscle activation patterns; (2) metabolic power (MP) and energy cost (EC) estimated via two determination methods (i.e., the Global Positioning System [GPS] and electromyography-based [EMG]); and (3) the apparent efficiency (AE) of 30-m linear sprints in seventeen elite U17 male soccer players performed under different conditions (i.e., unloaded sprint [US], parachute sprint [PS], and four incremental sled loads [SS15, SS30, SS45, SS60, corresponding to 15, 30, 45 and 60 kg of additional mass]). In a single testing session, each participant executed six trials (one attempt per sprint type). The results indicated that increasing the sled loads led to a linear increase in the relative contribution of the quadriceps (R2 = 0.98) and gluteus (R2 = 0.94) and a linear decrease in hamstring recruitment (R2 = 0.99). The MP during the US was significantly different from SS15, SS30, SS45, and SS60, as determined by the GPS and EMG approaches (p-values ranging from 0.01 to 0.001). Regarding EC, significant differences were found among the US and all sled conditions (i.e., SS15, SS30, SS45, and SS60) using the GPS and EMG methods (all p ≤ 0.001). Moreover, MP and EC determined via GPS were significantly lower in all sled conditions when compared to EMG (all p ≤ 0.001). The AE was significantly higher for the US when compared to the loaded sprinting conditions (all p ≤ 0.001). In conclusion, muscle activation patterns, MP and EC, and AE changed as a function of load in sled-resisted sprinting. Furthermore, GPS-derived MP and EC seemed to underestimate the actual neuromuscular and metabolic demands imposed on youth soccer players compared to EMG.

A thermo-economic comparison on new and conventional alternatives of pressurization of CO2 in CCS systems

The final stage of carbon capture and storage processes involves the pressurization of CO2 by a suitable method which is conventionally carried out through a series of compressors with intercoolers in between them. In the present study, the idea of liquefying the captured CO2 is considered. Four different systems for the liquefaction process are evaluated and compared Thermo-economically with the benchmark system of direct carbon dioxide compression. The results indicate that the EPLS system outperforms the others, with a product cost 5.89% lower than the benchmark system. Evaluations show that most of the costs are imposed by the initial compression stage in each system. A detailed investigation of the sensitivity analysis shows that the benchmark and claude systems have the largest dependency on pressure ratio and intercooling temperature, respectively. Additionally, evaluation of the economic parameters indicates that the changes in unit cost of power have the most effect on the benchmark system while the interest rate affects the results of claude and DEBARS more than other options. Detailed evaluations reveal that the EPLS layout has the advantage of less dependency on the changes of operating parameters and on the other hand, the cost of input heat, the maintenance factor, and the generator and evaporator temperatures make a high difference in the final product cost of the DEBARS. Finally, the effect of pressure drops in heat exchangers is investigated and results reveal that the consideration of pressure drops leads to power penalties ranging from 0.97 to 8.52 $/hr in different systems.