Generation Profiles Research Articles

Holistic Hosting Capacity Enhancement Through Sensitivity-Driven Flexibility Deployment and Uncertainty-Aware Optimization in Modern Distribution Networks

This study presents a novel sensitivity-driven distributionally robust optimization framework designed to enhance hosting capacity in renewable-powered distribution networks through targeted flexibility resource deployment. The proposed approach integrates temporal sensitivity mapping with robust optimization techniques to prioritize resource allocation across high-sensitivity nodes, addressing uncertainties in renewable energy generation and load demand. By leveraging a dynamic interaction between sensitivity scores and temporal system conditions, the framework achieves efficient and resilient operation under extreme variability scenarios. Key methodological innovations include the incorporation of a social force model-based sensitivity mapping technique, a layered optimization approach balancing system-wide and localized decisions, and a robust uncertainty set to safeguard performance against distributional shifts. The framework is validated using a synthesized test system, incorporating realistic renewable generation profiles, load patterns, and energy storage dynamics. Results demonstrate a significant improvement in hosting capacity, with system-wide enhancements of up to 35% and a 50% reduction in renewable curtailment. Moreover, sensitivity-driven resource deployment ensures efficient utilization of flexibility resources, achieving a peak allocation efficiency of 90% during critical periods. This research provides a comprehensive tool for addressing the challenges of renewable integration and grid stability in modern power systems, offering actionable insights for resource allocation strategies under uncertainty. The proposed methodology not only advances the state-of-the-art in sensitivity-based optimization but also paves the way for scalable, resilient energy management solutions in high-renewable penetration scenarios.

THE MATURE CRISIS IN CONTEMPORARY TIME: Critical psychosocial analysis in Winnicott

This study addresses the crisis of maturity in contemporary times, exploring its possible causes and illnesses, in addition to presenting interventions based on the Winnicottian approach. The methodology used consists of a bibliographical review focused on Winnicott's studies on the coming-of-age crisis, using periodicals, dissertations, theses and relevant books. The qualitative approach is adopted to provide a comprehensive understanding of reality, especially with regard to the profile of the contemporary generation. The Literature Review offers a wide range of materials for the critical analysis of theoretical data. The specific objectives include the analysis of differences between generations, the identification of possible causes and illnesses arising from the maturational crisis, and the description of possible interventions based on the Winnicottian approach. This study seeks to contribute to the understanding of the phenomenon of the coming-of-age crisis in contemporary times and provide relevant insights for effective therapeutic approaches. The research addressed the crisis of contemporary maturity, highlighting the importance of psychological and emotional maturity, creativity and cultural impact, especially related to the use of technology in young people's mental health. Limitations were identified, such as the lack of empirical data and the temporal delimitation of the studies reviewed. Future research with mixed methodologies is recommended, considering cultural and contextual aspects to support young people in the transition to adulthood.

Enhancing asset management for improved resilience through representative generation profiles

Enhancing asset management for improved resilience through representative generation profiles

A twenty-year dataset of hourly energy generation and consumption from district campus building energy systems

Distributed energy resources (DERs) would play a crucial role in the transition towards decentralized and decarbonized energy systems. However, due to the limited availability of long-term, high-resolution datasets, there has been little research on the descriptive analysis of distributed energy systems throughout the lifespan of distributed power generators and beyond. To address this challenge, this study has collected and described a twenty-year dataset (from 2002 to 2021) consisting of hourly energy generation and consumption profiles from a campus distributed energy system, covering the entire lifespan of on-site generators. The dataset includes supply-side data such as gas consumption from combined heating and power (CHP) units (fuel cell, gas engine), absorption chiller, gas boiler, solar photovoltaic generation, CHPs output, and grid electricity import. Additionally, real-life electricity, hot water, space heating, and cooling energy load profiles from individual buildings within the campus were also collected. This long-term dataset can be utilized in various scenarios, providing researchers and policymakers with comprehensive insights into the energy efficiency of distributed energy systems.

Uma geração verdadeiramente única: esperta, ágil e independente ou solitária, frágil e ansiosa?

The objective of this text is to reflect on what the intense use of screens and social media causes for children, adolescents, and young people today. Is digital culture making them smarter, more agile, and independent, or anxious, lonely, and fragile? With this question as a starting point, we propose a discussion based on the writings of various authors who address the constitution of those born in Brazil from the year 2000 onward. The text was developed from a literature review perspective based on two doctoral research projects focusing on related themes: the formation of contemporary youth in the face of techno-scientific transformations, and the professional development of teachers within a collaborative and investigative community, considering the new generational profile that is entering schools, marked by global hyper-connection. The results indicate that we have a generation facing dramatic changes in how they constitute themselves, exist, and live as contemporary subjects. This is a generation that dedicates excessive time to screens and social media, facing the highest rates of depression, loneliness, self-harm, suicide attempts, and completed suicides. Such a scenario compels us to question how digital communication and information technologies are interfering with the physical, psychological, cognitive, and emotional development of this generation. Keywords: Contemporaneity. Current generation. Technological artifacts. Human development.

Adapting the National Financial Capability Test to Address Generational Differences in Cognitive Biases

This study examined the influence of cognitive biases on financial literacy test outcomes across four generational groups: Gen Z, Millennials, Gen X, and Baby Boomers. Using the National Financial Capability Test and an online in silico experiment, we analyzed how cognitive biases influence the likely responses of each generation. The results indicate that the current test format aligns more closely with Baby Boomers, who are less affected by certain biases but tend to exhibit resistance to new financial strategies. A key contribution of this research is the identification of generational bias profiles and actionable recommendations for tailoring financial literacy assessments to reflect these differences. Our approach not only advances behavioral finance literature but also introduces innovative methodology through AI-driven simulations, providing a replicable framework for exploring cognitive influences in decision-making. The findings underscore the need for tailored financial education programs that consider these cognitive biases, aiming to foster unbiased financial decision-making across age groups.

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.

Low-emission hydrogen supply chain for oil refining: Assessment of large-scale production via electrolysis and gasification

The refining industry is a major hydrogen consumer, mainly relying on fossil fuel-derived hydrogen. While recent literature has focused on the production of hydrogen from water electrolysis, (waste) biomass gasification is another effective method for low-emission hydrogen production, and the refining industry is well positioned for its rapid adoption. This study conducts a techno-economic assessment of the whole supply chain of hydrogen for oil refining and analyses the LCA-climate change for residual biomass gasification and water electrolysis pathways. The potential economic and environmental benefits of combining both production methods are also analyzed. A real case study featuring four different scenarios, using data from a refinery, coupled with local data and future projections for potential curtailment and electricity prices, is included. The hourly hydrogen generation and demand profiles of the refinery were analyzed to accurately assess storage requirements. Results indicate that combining both technologies does not result in clear environmental or cost benefits, with residual biomass gasification emerging as the most advantageous configuration for the base case. Sensitivity analysis reveals that hydrogen produced via electrolysis may become more cost-effective if residual biomass prices are high enough. The importance of underground storage (salt cavern) is highlighted due to its low investment, while other storage methods can significantly increase the Levelized Cost of Hydrogen (LCOH). This study demonstrates that hydrogen production through gasification can be less carbon-intensive and more cost-competitive than electrolysis. Achieving low LCOH values and greenhouse gas emissions is feasible in all scenarios, indicating that both water electrolysis and residual biomass gasification are economically viable options for contributing to a low-emission global energy system.

A Computationally Efficient Rule-Based Scheduling Algorithm for Battery Energy Storage Systems

This paper presents a rule-based control strategy for the Battery Management System (BMS) of a prosumer connected to a low-voltage distribution network. The main objective of this work is to propose a computationally efficient algorithm capable of managing energy flows between the distribution network and a prosumer equipped with a photovoltaic (PV) energy production system. The goal of the BMS is to maximize the prosumer’s economic revenue by optimizing the use, storage, sale, and purchase of PV energy based on electricity market information and daily production/consumption curves. To achieve this goal, the method proposed in this paper consists of developing a rule-based algorithm that manages the prosumer’s Battery Energy Storage System (BESS). The rule-based approach in this type of problem allows for the reduction of computational costs, which is of fundamental importance in contexts where many users will be coordinated simultaneously. This means that the BMS presented in this work could play a vital role in emerging Renewable Energy Communities (RECs). From a general point of view, the method requires an algorithm to process the load and generation profiles of the prosumer for the following three days, together with the hourly price curve. The output is a battery scheduling plan for the timeframe, which is updated every hour. In this paper, the algorithm is validated in terms of economic performance achieved and computational times on two experimental datasets with different scenarios characterized by real productions and loads of prosumers for over a year. The annual economic results are presented in this work, and the proposed rule-based approach is compared with a linear programming optimization algorithm. The comparison highlights similar performance in terms of economic revenue, but the rule-based approach guarantees 30 times lower processing time.

Life Cycle Assessment of Liquid Alkaline Electrolyzers Comparing Environmental Performance across Various Design, Operation, and End-of-Life Scenarios

Alkaline water electrolysis (ALK) is a demonstrated technology, used for over 100 years primarily for ammonia production, and later advanced for oxygen production for nuclear submarine applications. With a new focus on the expansion of renewably-powered hydrogen production, ALK systems hold great promise for commercialization. Recent research may further drive-down costs by addressing challenges related to electrodes, electrolytes, bubble formation, and impact of operation patterns. However, literature studies on ALK often lack a comprehensive model that can capture the impact of such deployment nuances on overall greenhouse gas emissions and environmental impacts. For example, an analysis of the effect of hourly or sub-hourly operation of ALK based on electricity generation profiles on required heat management, shutdowns, hydrogen leakage, safety, and cell degradation are lacking. Additionally, details on the manufacturing of critical components of the ALK cell stack are missing, although material contributions by weight are available. Materials at their end-of-life may have unique requirements for recycling or disposal, and these factors are also not well understood.Herein, we present an overview of life cycle assessments (LCA) of ALK, as well as novel modeling of environmental impacts associated with ALK supply chains in the United States. Details and impacts of component manufacturing is included, along with the uncertainties of the raw materials production. We will then present our dynamic ALK model that includes cell voltage degradation, effects of the input power load on the electrolyzer temperature, purity, and associated hydrogen leakage at the electrolyzer facility itself. Finally, we present findings on plausible recycling and landfilling of the raw materials. We use the NREL United States Life Cycle Inventory database supplemented by Ecoinvent in the OpenLCA platform to evaluate embodied emissions. We compare the environmental performance for different scenarios of stack design (baseline versus advanced based on reduced diaphragm thickness and improved catalyst material), operation (low versus high pressure and scales such as 50 versus 500 ton/day), end-of-life cases (landfilling versus combination of landfilling and recycling). Finally, we make a comparison of these different scenarios to identify environmental impact hotspots along the life cycle of a liquid alkaline electrolyzer and guide future research on cell stack development.

Biomass valorization: Comparative analysis of tea waste pellets and wood pellets for steam generation and emission profiles

This study investigates the viability of tea waste as a biomass feedstock for pellet production and its combustion characteristics. Tea waste, an abundant agricultural byproduct, presents a promising avenue for renewable energy generation if effectively utilized. The pellets derived from tea waste were subjected to detailed analysis focusing on their calorific values and carbon composition. The calorific value of tea waste pellets was determined to be approximately 18.5 MJ/kg, comparable to conventional wood pellets. Notably, these pellets exhibit a high carbon content of 45 %, indicating a significant fixed carbon fraction that necessitates tailored combustion strategies for optimal efficiency. This research underscores the potential of tea waste pellets as a sustainable biofuel, contingent upon the development and application of precise combustion methodologies. It underscores the critical importance of understanding the chemical properties of solid biofuels in optimizing their utilization for energy production.

Barriers to Reverse Logistics of Construction and Demolition Waste

Objective: This study aims to identify the main barriers to implementing reverse logistics for construction and demolition waste (RCD), focusing on challenges faced by both small and large waste generators. Theoretical Framework: The research is grounded in reverse logistics theories, addressing sustainability and waste management frameworks. These concepts provide a basis for understanding the diverse challenges different generator profiles encounter. Method: A systematic literature review was conducted over nine months (October 2023 to July 2024) following the PRISMA method. Seven databases were consulted—Web of Science, Scopus, MDPI, Emerald, ScienceDirect, Taylor and Francis, and Wiley—resulting in 119 relevant articles. The study identifies and categorizes barriers for small and large generators. Results and Discussion: The results revealed 20 barriers for large generators and 7 for small generators, with 4 common barriers between both groups. These barriers highlight the complexity of RCD management and suggest specific policy and strategy needs. In the discussion, these barriers are analyzed in the context of the theoretical framework, revealing practical implications for improving reverse logistics systems. Research Implications: The findings provide valuable insights for both academic research and practical applications in waste management, contributing to the development of more effective strategies for RCD handling and disposal. This research has the potential to influence public policy and industry practices in waste logistics. Originality/Value: This study fills a gap in the literature by providing a comprehensive overview of barriers specific to different waste generator profiles. It advances theoretical knowledge and offers practical recommendations for improving RCD reverse logistics.

Increasing revenues of offshore wind farms with co-located energy storage systems

Abstract Co-located onshore and offshore energy storage systems exhibit the potential of diversifying and increasing revenue streams of offshore wind farms. However, these systems should be designed and sized considering the power generation profile, the route to market of these assets, i.e. power trading strategy, and dynamics of the various segments of the power market. In this study, the feasibility of deploying subsea hydro-pneumatic storage systems was investigated. It was seen that if a 50MW capacity system with a storage duration of 4 hours is deployed in an offshore wind farm of 1000MW capacity, the wind farm can potentially participate in the day-ahead and ancillary services markets more confidently from a risk perspective. The relatively higher volatility in these markets presents an opportunity to improve economics of these offshore wind projects as long as costs can be kept under control.

A power-law distribution of infectious quanta for the top 30% of SARS-CoV-2-infected individuals

Minimising airborne infection with respiratory viruses, such as SARS-CoV-2, requires knowledge of the infectious quanta generation rate for determining the minimum dilution requirement. The two existing methods for estimating quanta generation rates are the viral load method and outbreak method. The former method is challenged by significant uncertainty in input data, including dose-response parameters and infectious viral loads. The latter method, based on the Wells–Riley equation, is challenged by significant individual heterogeneity in quanta generation rates and lack of outbreak data. In this study, the two methods are integrated for studying the quanta generation profile of all individuals infected with an ancestral SARS-CoV-2 strain, based on four reported outbreaks of infection. The airborne transmission droplet size ranges in the four outbreaks, which were determined in previous studies, are used to estimate the hourly volume of expired droplets for the viral load method. Various viral load datasets and conversion factors from RNA copies to infectious quanta are tested. Two criteria are used to identify the probable quanta generation profile, i.e. 70% of infected individuals do not infect others, and the estimated quanta generation rates estimated using the outbreak method should be within the top 80%–99% of infected individuals. The predicted quanta generation profile of all individuals infected with SARS-CoV-2 follows a log-normal distribution, whereas that of the top 30% of infected individuals approximately follows a power-law distribution.Practical significance: A major obstacle in defining dilution requirements for minimising airborne infection is the lack of infectious quanta generation rates for the general population. Our approach integrates two existing quanta estimation methods and paves the way to obtaining reliable quanta generation rate profiles at the population level.

On the regulatory and economic incentives for renewable hybrid power plants in Brazil

The complementarity between renewable generation profiles has been widely explored in the literature. Notwithstanding, complex interactions between regulatory and economic frameworks add interesting challenges and opportunities for hybrid power plant investors, regulators, and planners. Focusing on the Brazilian power market, we study the alignment of incentives between the economically-optimized strategy of hybrid power plant investors and the efficient utilization of the transmission resources. To do that, we propose a decision model that co-optimizes the risk-adjusted strategy of a hybrid power plant owner comprising (i) the forward-market involvement, (ii) the contracted amount of network access, and (iii) the share of renewable sources composing the hybrid power plant. We also propose adjusting the current regulatory framework to consider a unified calculation for the Firm Energy Certificates of non-controllable renewable power plants, including hybrid units. Based on that, we ensure a non-discriminatory regulatory framework for renewables acknowledging the diversity of generation profiles that hybrid units may have due to their optimal hybridization shares and network-access contracting strategies. A case study using realistic data from the northeastern region of the Brazilian power system showcases strong economic incentives for hybridization with reduced transmission resource utilization.

A novel design approach based on sequential-conjugate method for high-mesh-ratio harmonic drives with dual-conjugate profiles and polynomial wave generators

The tooth profiles and meshing ratio of the flexsplines and circular-splines in harmonic drives have attracted significant research attention, especially for applications requiring high-torque. The present study proposes a new five-phase method for the design of the wave generator profile and all the tooth profiles in the harmonic drive. Once the upper profile of rack-cutter has been given, the proposed method enables all of the other undefined tooth profiles in harmonic drive (including the upper/lower-profiles of the flexspline/circular-spline and the lower-profile of the rack-cutter) to be constructed using a sequential-conjugate approach. The designed tooth profiles achieve a high meshing ratio, and thus reduce the transmission load. Notably, part of the period during the meshing process is dual-conjugate (i.e. the flexspline and circular-spline have two meshing points simultaneously). Furthermore, the profile of wave generator is defined as a polynomial curve, which thus provides greater design freedom for any follow-up optimization task. An illustrative example is presented to demonstrate the effectiveness of the proposed method for a harmonic drive with a three-tooth difference and a wave generator based on a quintic polynomial. The results show that the theoretical meshing ratio is as high as 81%, and the dual-conjugate region accounts for 23% of total conjugate region.

Energy dataset of Frontier supercomputer for waste heat recovery

The Hewlett Packard Enterprise–Cray EX Frontier is the world’s first and fastest exascale supercomputer, hosted at the Oak Ridge Leadership Computing Facility in Tennessee, United States. Frontier is a significant electricity consumer, drawing 8–30 MW; this massive energy demand produces significant waste heat, requiring extensive cooling measures. Although harnessing this waste heat for campus heating is a sustainability goal at Oak Ridge National Laboratory (ORNL), the 30 °C–38 °C waste heat temperature poses compatibility issues with standard HVAC systems. Heat pump systems, prevalent in residential settings and some industries, can efficiently upgrade low-quality heat to usable energy for buildings. Thus, heat pump technology powered by renewable electricity offers an efficient, cost-effective solution for substantial waste heat recovery. However, a major challenge is the absence of benchmark data on high-performance computing (HPC) heat generation and waste heat profiles. This paper reports power demand and waste heat measurements from an ORNL HPC data centre, aiming to guide future research on optimizing waste heat recovery in large-scale data centres, especially those of HPC calibre.

Enhanced thrombin and plasmin generation profiles in alpha-2-antiplasmin–deficient patients: Data from the Rare Bleeding disorders in the Netherlands study

Backgroundα2-Antiplasmin (A2AP) deficiency is a rare and often unidentified disorder characterized by increased fibrinolysis and subsequent bleeding. Global hemostasis assays may increase insight into the altered coagulation and fibrinolysis in these patients. ObjectivesTo explore thrombin and plasmin generation profiles in A2AP-deficient patients, corresponding A2AP activity levels and associated bleeding phenotypes. MethodsThe Nijmegen hemostasis assay was used to assess thrombin and plasmin generation in 23 A2AP-deficient patients (median age, 50 years; 70% women) from the cross-sectional Rare Bleeding disorders in the Netherlands study. Analyzed parameters included thrombin peak height, thrombin potential, fibrin lysis time, plasmin peak height, plasmin velocity index, and plasmin potential. These parameters were expressed as percentages of a reference obtained from 37 healthy controls (median age, 46 years; 57% women). The Nijmegen hemostasis assay data were correlated with A2AP activity levels and International Society on Thrombosis and Hemostasis Bleeding Assessment Tool scores using Pearson correlation coefficients. ResultsPatients’ A2AP activity levels ranged from 23% to 83% (reference range, 89%-122%). Plasmin generation increased, as evidenced by significantly shorter fibrin lysis times (73%; P < .001) and higher plasmin peak heights (203%; P < .001), plasmin velocity indices (302%; P < .001) and plasmin potentials (154%; P < .001) in A2AP-deficient patients than those in healthy controls. Moreover, significantly higher thrombin potentials (146%; P < .001) and thrombin peak heights (132%; P < .001) were observed. Enhanced plasmin generation parameters showed statistically significant correlations with lower A2AP activity levels and higher International Society on Thrombosis and Hemostasis Bleeding Assessment Tool scores. ConclusionA2AP-deficient patients exhibited augmented plasmin generation profiles that correlated with A2AP activity level and bleeding phenotype. Interestingly, increased thrombin generation profiles were also found in these patients.

Generation, expansion, gene delivery, and single-cell profiling in rhesus macaque plasma B cells.

A key step in developing engineered B cells for therapeutic purposes is evaluation in immunocompetent, large-animal models. Therefore, we developed methods to purify, expand, and differentiate non-human primate (NHP; rhesus macaque) B cells. After 7days in culture, B cells expanded 10-fold, differentiated into a plasma cell phenotype (CD38, CD138), and secreted immunoglobulin G. Using single-cell sequencing and flow cytometry, we verified the presence of plasma cell genes in differentiated NHP B cells and unearthed less-recognized markers, such as CD59 and CD79A. In contrast with human cells, we found that the immune checkpoint molecule CD274 (PD-L1) and major histocompatibility complex (MHC) class I molecules were upregulated in NHP plasma cells in the transcriptional data. Lastly, we established the conditions for efficient transduction of NHP B cells with adeno-associated virus (AAV) vectors, achieving a delivery rate of approximately 60%. We envision that this work will accelerate proof-of-concept studies using engineered B cells in NHPs.

Exploring convective entropy optimization and activation energy impact on magneto-nanofluid flow over a vertical stretched plate with Hall current and nonlinear thermal radiation using SQLM

This paper investigates the profound impact of entropy generation and activation energy on the dynamics of hydromagnetic nanofluids, focusing on nonlinear thermal radiation, viscous and Ohmic dissipation, and Hall current effects over a linear stretching sheet. Various nanoparticles are incorporated into the nanofluid formulation using the thermophoresis and Brownian motion model. Through similarity transformation, the system of nonlinear equations is solved with high precision using the Spectral Quasilinearization Method (SQLM). Comprehensive analyses of velocity, cross-flow velocity, temperature, concentration, and entropy generation profiles are conducted for numerous physical parameters. Results indicate that velocity and cross-flow velocity increase with the Hall parameter while temperature and concentration profiles decrease. Both the velocity and cross-flow velocity profiles enhance for mixed convection parameters closer to the sheet, whereas the temperature and concentration profiles exhibit the contrary tendency. Prandtl number diminishes the profiles of horizontal velocity, cross-flow velocity and concentration distributions. Temperature distribution profile hikes for both the Brownian motion parameter and thermophoresis parameter. The activation energy parameter enhances the cross-flow velocity, with a corresponding decline in temperature distribution and a similar trend is observed in the concentration profile. Further, entropy generation profiles increase with higher Brinkman and Reynolds numbers while exhibiting mixed tendencies with the Schmidt number. These findings reveal that Hall current introduces complex interactions within the nanofluid flow, significantly influencing thermal, concentration, and entropy generation characteristics, particularly in magnetic fields and activation energy.