Potential Cost Reduction Research Articles

Brazilian beef production and GHG emission - social cost of carbon and perspectives for climate change mitigation.

The livestock sector holds a prominent position among Brazilian economic sectors; however, beef production is linked to noteworthy environmental impacts, including deforestation and greenhouse gas (GHGs) emissions. In alignment with the Paris Agreement, Brazil aims to reduce GHG emissions by 43% by 2030 as part of its NDC commitment. This study aims to elucidate the nexus between beef production and emissions from beef cattle, providing an assessment of predictive GHG emission scenarios for 2030, and an economic valuation of these emissions utilizing the social cost of carbon (SCC). Under a business-as-usual (BAU) scenario, GHG emissions from beef production are estimated to range between 0.42-0.63 GtCO2e in 2030. Conversely, meeting the Brazilian Nationally Determined Contributions (NDC) target requires limiting emissions to 0.26 GtCO2e. The SCC analysis unveils a potential cost reductions ranging from US $18.8 to $42.6 billion in 2030, contingent upon achieving the NDC. Furthermore, a strategic assessment considering climate targets and prioritizing beef exports envisions a domestic market availability of 2-10kg of beef per capita in 2030. This study highlight the critical need for transformative adjustments in livestock production methods to reduce GHG emissions per unit of beef yield, with a focus on the economic advantages of emission mitigation.

Pohled ergoterapeutů, fyzioterapeutů a pacientů na aplikaci tradičních a inovativních postupů Constraint-induced movement therapy v České republice

Background: The comprehensive therapeutic program, Constraint-induced movement therapy (CIMT), focuses on functional training of the paretic upper limb and the transfer of acquired skills in daily life. Aim: The purpose of the survey was to map the current experience of therapists and patients with the therapeutic toolkit and home activity monitoring. Methods: The components of CIMT currently used, monitoring forms, barriers to provision, and motivations and subjectively perceived limitations for the use of technology in rehabilitation for activity monitoring were explored with the use of on-line surveys. Results: A total of 95 occupational therapists and physiotherapists and 91 patients participated in the survey. Czech therapists reported the most common perceived barriers that limit CIMT provision were as follows: low number of suitable patients, lack of knowledge of the method, increased administrative and time demands, or concerns about the high demands of the method for patients. The patients themselves are then limited in participating in the program due to its low accessibility or fear of the high difficulty of the exercise. As part of monitoring, patients complete a paper exercise diary (36%) or less frequently one on a computer (6.7%), but most often they do not track the results (40.4%). A total of 55% of patient respondents are motivated to share their results electronically with their therapist. Conclusions: According to the survey results, patients with spastic paresis of the upper limb after brain injury are motivated to participate in remote therapy and share results of home exercise remotely. The application of innovative approaches in CIMT and activity monitoring increases the availability of therapeutic interventions with potential cost reduction in clinical practice.

The Impact of Smart Contracts and Decentralized Finance Platforms on Transaction Costs in Indonesia's Traditional Economy

This study examines the impact of smart contracts and decentralized finance (DeFi) platforms on transaction costs within Indonesia's traditional economy. Using a quantitative approach, the research involved 60 respondents engaged in traditional economic sectors, utilizing a Likert scale (1-5) to gather perceptions on the efficiency, transparency, and cost-reduction potential of these technologies. Data were analyzed using SPSS version 25, with results indicating that both smart contracts and DeFi platforms significantly reduce transaction costs. Smart contracts were found to automate agreements and enhance trust, while DeFi platforms increased accessibility and reduced financial barriers. Regression analysis revealed that these technologies collectively explain 62% of the variance in transaction costs. The findings underscore the transformative potential of blockchain technologies in Indonesia's traditional economy, offering practical implications for stakeholders and policymakers to address technological and regulatory challenges. This research provides valuable insights for the integration of blockchain solutions in fostering economic efficiency and sustainability.

Integration of Blockchain-Based Decentralized Finance into Financial Planning and Analysis: A Framework for Corporate Finance Innovation

The integration of Decentralized Finance (DeFi) into Financial Planning and Analysis (FPA) systems marks a pivotal transformation in corporate financial management, presenting organizations with unprecedented opportunities for operational efficiency, risk management, and strategic advancement. This article provides a comprehensive examination of the implementation framework, challenges, and strategic implications of incorporating DeFi technologies into traditional FPA systems. The article analyzes the technical architecture required for successful integration, including smart contract implementation, decentralized liquidity mechanisms, and blockchain-based audit systems, while addressing critical considerations in regulatory compliance and organizational change management. The article reveals significant potential for cost reduction, improved process efficiency, and enhanced risk management capabilities through DeFi integration while highlighting the importance of robust security protocols and governance frameworks. The article also identifies emerging opportunities in artificial intelligence integration, cross-chain interoperability, and industry-specific applications, offering valuable insights for organizations navigating this technological transformation. Furthermore, the article examines implementation challenges and provides strategic solutions for organizations undertaking DeFi integration initiatives. The article demonstrates that while the integration process presents complex technical and organizational challenges, the potential benefits in terms of operational efficiency, cost reduction, and competitive advantage make it a compelling strategic initiative for forward-thinking organizations. This article contributes to the growing body of knowledge on DeFi implementation in corporate settings and provides practical guidelines for organizations seeking to leverage blockchain technology in their financial operations.

Thermodynamic integration in combined fuel and power plants producing low carbon hydrogen and power with CCUS

Demand for low-carbon sources of hydrogen and power is expected to rise dramatically in the coming years. Individually, steam methane reformers (SMRs) and combined cycle gas power plants (CCGTs), when combined with carbon capture utilisation and storage (CCUS), can produce large quantities of on-demand decarbonised hydrogen and power respectively. The ongoing trend towards the development of CCUS clusters means that both processes may operate in close proximity, taking advantage of a common infrastructure for natural gas supply, electricity grid connection and the CO2 transport and storage network. This work improves on a previously described novel integration process, which utilizes flue gas sequential combustion to incorporate the SMR process into the CCGT cycle in a single “combined fuel and power” (CFP) plant, by increasing the level of thermodynamic integration through the merger of the steam cycles and a redesign of the heat recovery system. This increases the 2nd law thermal efficiency by 2.6% points over un-integrated processes and 1.9% points the previous integration design. Using a conventional 35% wt. monoethanolamine (MEA) CO2 capture process designed to achieve two distinct and previously unexplored CO2 capture fractions; 95% gross and, 100% fossil (CO2 generated is equal to the quantity of CO2 captured). The CFP configuration reduces the overall quantity of flue gas to be processed by 36%–37% and increases the average CO2 concentration of the flue gas to be treated from 9.9% to 14.4% (wet). This decreases the absorber packing volume requirements by 41%–56% and decreases the specific reboiler duty by 5.5% from 3.46–3.67 GJ/tCO2 to 3.27–3.46 GJ/tCO2, further increasing the 2nd law thermal efficiency gains to 3.8%–4.4% points over the un-integrated case. A first of a kind techno economic analysis concludes that the improvements present in a CO2 abated CFP plant results in a 15.1%–17.3% and 7.6%–8.0% decrease in capital and operational expenditure respectively for the CO2 capture cases. This translates to an increase in the internal rate of return over the base hurdle rate of 7.5%–7.8%, highlighting the potential for substantial cost reductions presented by the CFP configuration.

Application of Mixed-Integer Linear Programming Models for the Sustainable Management of Vine Pruning Residual Biomass: An Integrated Theoretical Approach

This study explores the application of Mixed-Integer Linear Programming (MILP) models to optimize the collection and transportation of vineyard pruning biomass, a critical resource for sustainable energy and material production. Two optimization approaches are evaluated, as follows: a base MILP model designed for scenarios with single processing points and an advanced model incorporating intermediate processing steps to enhance logistical efficiency. Using synthetic datasets that simulate vineyard regions, the models demonstrate potential cost reductions of up to 30%, showcasing significant improvements in operational efficiency and resource utilization. This study underscores the scalability and real-world feasibility of the proposed models, highlighting their alignment with circular bioeconomy principles. Additionally, it addresses key limitations such as computational complexity and adaptability to dynamic environments. Future research directions are outlined, focusing on real-time data integration, dynamic updates, and multi-objective optimization to further enhance model robustness and applicability in diverse supply chain scenarios.

DEVELOPMENT OF LOCOMOTIVE CC 203 MAINTENANCE STRATEGY USING RISK-BASED RELIABILITY CENTERED MAINTENANCE (RCM 3) METHOD

Trains play a vital role in Indonesia's transportation system as they help reduce exhaust emissions and are one of the most environmentally friendly modes of transportation. PT Kereta Api Indonesia (PT KAI) as the largest train operator in Indonesia has an important role in providing reliable and efficient train services. This research analyzes the maintenance strategy applied to locomotive CC 203 and provides recommendations to improve reliability and maintenance cost efficiency using the Risk-Based Reliability Centered Maintenance (RCM 3) method. The RCM analysis results show that by changing the maintenance interval from P24 to P12, P24, and P48 the reliability of the diesel engine system can be improved from 66,3% to 80,2%. In addition, the risk of failure mode occurrence decreases. Although the cost of the proposed maintenance increases, the benefits obtained are much greater including increased system reliability, decreased risk, and potential reduction in corrective maintenance costs. Therefore, this new maintenance recommendation is expected to assist PT KAI in maintaining reliable and efficient operations, as well as anticipating the risks associated with corrective maintenance costs.

Topological optimization with support structure filter for additive manufacturing

Topological optimization proves to be an important tool for analysis and design of projects, seeking the best structural performance within criteria such as stiffness, strength, economy, and stability. However, manufacturing optimized structures by traditional methods is not always feasible, due to the complex and unconventional configuration of the geometry. Additive Manufacturing (AM) emerges as a solution, allowing the production of objects layer by layer, without the need for molds. However, angles greater than 45° formed in the geometry may require support material to avoid failures and deformations during printing, increasing material costs and manufacturing time. This study combines topological optimization with AMfilter, a support structure filter for AM developed by Langelaar (2016). Using the open-source MATLAB® code of 88 lines developed by Andreassen et al. (2010), in which AMfilter is integrated during the numerical analysis of the topological optimization problem. The objective is to evaluate the effectiveness of topological optimization with the implementation of AMfilter, through simulations of printing the optimized models, highlighting the potential cost reduction benefits. The results demonstrate a decrease in the use of supports, and in some cases, their complete elimination, making this methodology efficient in the cases examined in this study.

Digital Flexible Ureteroscope: Evaluating Factors Responsible for Damage and Implementing a Mandatory Certification Program for Usage.

Objective: Digital flexible ureteroscopes (DFUs) play a crucial role in endourological procedures, and scope breakages are often avoidable with proper measures in place. We aimed to evaluate the effect of mandatory training on DFU durability and to assess the influence of various factors on instrument damage. Materials and Methods: Mandatory training involving instructional videos on DFU care was introduced for all processing and operating room staff handling DFUs. Only certified personnel were allowed to handle DFUs, with meticulous usage documentation. The average annual usage of each DFU was compared pre and post program implementation. We examined factors such as patient demographics, procedure details, and operator experience impacting scope life using negative binomial regression. Results: The average usage of DFU increased by 21%, from 6.38 to 7.74 cases. We found that post-graduate year stood out as a significant predictive factor (estimate = 3.28, p = 0.04). Moreover, the streamlined model revealed that previous ureteral-stent use (estimate = 0.94, p < 0.001), struvite stones (estimate = 3.08, p = 0.01), and a higher number of stones (estimate = 0.11, p = 0.04) were associated with an increased number of procedures before DFU breakage, whreas in situ lithotripsy in the lower calyx was associated with a reduced number of procedures before DFU breakage (estimate = -1.11, p = 0.003). Conclusion: Implementing a mandatory training program showed an increase in DFU durability by 21%, suggesting a potential reduction in annual repair and replacement costs by the same percentage. Furthermore, outcomes were more favorable when experienced practitioners conducted treatments, especially in cases involving struvite stones.

Programming Model for Enterprise Multi-Process Decision Optimization

This paper addresses critical decision-making challenges faced by enterprises during the production process, particularly focusing on efficient quality inspection, inspection and disassembly decisions, defective rate control, and cost minimization. In the current dynamic market environment, existing algorithms demonstrate insufficient adaptability, hindering their effectiveness in addressing complex production scenarios. To overcome these limitations, we propose a novel genetic algorithm that incorporates dynamic change adjustment through a 0-1 programming model. This approach enhances the algorithm's flexibility, enabling enterprises to develop scientifically sound and rational production decision schemes tailored to varying market conditions. Our empirical analysis reveals that the average production cost for enterprises utilizing this method is 32.7, indicating significant potential for cost reduction while maintaining product quality. The findings contribute to the existing literature by providing a robust theoretical framework that underscores the importance of adaptive algorithms in improving production efficiency and decision-making processes in an ever-evolving market landscape.

Improving transparency in malaria programme funds: A business case for connected diagnostics in Kenya.

International vertical health financing programmes risk functioning in parallel with existing domestic funding in low- and middle-income countries (LMICs), leading to inefficient service delivery and concomitant poor health outcomes. We assessed the opportunities offered by digitalised diagnostics (ConnDx) to target and monitor health funds to those in need objectively and transparently. ConnDx was rolled out in five private health facilities in Kisumu, Kenya. The ConnDx process was codeveloped with the local Department of Health of Kisumu. We used the quantitative data generated by ConnDx. We also calculated the costs for ConnDx and standard care to assess potential cost reductions. In total, 2199 malaria cases were detected among 11 689 patients with fever. ConnDx allowed for the identification of malaria hotspots, semi-real-time assessment of patient health seeking behaviour across facilities and insights in doctor's prescription behaviours. Based on these insights, we estimated a 25% reduction in costs can be realised, while simultaneously better quality indicators can be monitored. The concept of ConnDx can be used for any medical condition that can be diagnosed in a digital manner and linked to mobile payment systems. The generated data can contribute to better quality services for individual patients while at the same time support local health policy makers and managers for more targeted interventions. The ConnDx approach can help decision makers in LMICs to channel disease-specific funds to the right patients for the right disease at the right time, which can potentially accelerate the way to universal health coverage.

Inequalities in oral health: estimating the longitudinal economic burden of dental caries by deprivation status in six countries

BackgroundThe recent World Health Organization (WHO) resolution on oral health urges pivoting to a preventive approach and integration of oral health into the non-communicable diseases agenda. This study aimed to: 1) explore the healthcare costs of managing dental caries between the ages of 12 and 65 years across socioeconomic groups in six countries (Brazil, France, Germany, Indonesia, Italy, UK), and 2) estimate the potential reduction in direct costs from non-targeted and targeted oral health-promoting interventions.MethodsA cohort simulation model was developed to estimate the direct costs of dental caries over time for different socioeconomic groups. National-level DMFT (dentine threshold) data, the relative likelihood of receiving an intervention (such as a restorative procedure, tooth extraction and replacement), and clinically-guided assumptions were used to populate the model. A hypothetical group of upstream and downstream preventive interventions were applied either uniformly across all deprivation groups to reduce caries progression rates by 30% or in a levelled-up fashion with the greatest gains seen in the most deprived group.ResultsThe population level direct costs of caries from 12 to 65 years of age varied between US10.2 billion in Italy to US$36.2 billion in Brazil. The highest per-person costs were in the UK at US$22,910 and the lowest in Indonesia at US$7,414. The per-person direct costs were highest in the most deprived group across Brazil, France, Italy and the UK. With the uniform application of preventive measures across all deprivation groups, the greatest reduction in per-person costs for caries management was seen in the most deprived group across all countries except Indonesia. With a levelling-up approach, cost reductions in the most deprived group ranged from US$3,948 in Indonesia to US$17,728 in the UK.ConclusionOur exploratory analysis shows the disproportionate economic burden of caries in the most deprived groups and highlights the significant opportunity to reduce direct costs via levelling-up preventive measures. The healthcare burden stems from a higher baseline caries experience and greater annual progression rates in the most deprived. Therefore, preventive measures should be start early, with a focus on lowering early childhood caries and continue through the life course.

Traditional and modern methods of construction: Comparative study of the sustainability of single‐family homes

AbstractModern construction methods, such as additive manufacturing, are aimed to enhance the efficiency and quality of construction processes while potentially reducing waste generation and material use, thus contributing to sustainability performance (SP). However, comprehensively understanding the sustainability trade‐offs associated with these methods is crucial for guiding both research and practical applications toward sustainable development. This study aims at quantifying the SP of various construction methods for housing, including traditional, prefabricated, and additive manufacturing approaches. A sustainability index, integrating economic, environmental, social, and technological criteria, is utilized to assess different alternatives. Findings reveal promising aspects of 3D printing technologies, such as potential cost reductions through scale increase and process optimization, minimized material waste generation, creation of skilled employment opportunities, and enhanced construction flexibility and ease. Nevertheless, challenges persist, notably significant greenhouse gas emissions and limited supplier availability. Addressing these challenges is imperative for advancing the sustainable implementation of additive manufacturing in construction.

BIOSIMILAR MEDICINAL PRODUCTS – LEGISLATIVE DECISIONS AND MARKET ENTRY

Biosimilar drugs, structurally identical and manufactured similarly to original biologic drugs, offer potential cost reductions in therapeutic practice, albeit with variations in adoption across European countries. This review synthesizes findings from literature examining legislative decisions and their effects on biosimilar market entry in Europe. Drawing from scientific articles and official documents, the review reveals that biologics constitute 36% of European drug expenditure, with the market valued at €78.6 billion in 2021 and growing annually at 10.5% over the past five years. Approximately 15% of new active substances centrally approved by the EMA in 2020 were biologics. The European biosimilars market is projected to reach €8.8 billion in 2021. Various measures are being implemented to boost biosimilar uptake, including pricing strategies, reimbursement policies, and substitution practices. Access, measured in terms of availability and time to entry, is still difficult in a number of countries, but legislative measures are helping biosimilars enter European markets more quickly.

Design of a Reverse Osmosis Desalination Plant Powered by Renewables for a Small Mediterranean Island

Abstract Water shortage is one of the main problems for small, isolated islands, especially in the Mediterranean Sea. Water supply in those areas relies on maritime transport through tanker ships, especially during periods of high demand. However, this solution is unsuitable for isolated islands due to the high costs and environmental impact. This study aims to assess the feasibility of powering a desalination facility in a remote location with renewable energy sources to assess the potential cost savings and reduction of greenhouse gas emissions compared to the current supply mechanisms. To this end, the Greek island of Tilos is selected as a case study due to its high unexploited renewable energy production during winter months. The study hypothesizes using a seawater reverse osmosis (SWRO) unit to increase the sustainability of the water supply and promote the island’s self-sufficiency. Two control strategies have been adopted, simulating a demand-driven and a renewable production-driven scenarios. Results show a levelized cost of water that ranges between 1 and 2 €/m3, which is consistent with the average cost for the existing desalination plants in Grece. The adoption of a SWRO facility coupled with water storage systems results always in a more cost-effective solution than maritime transport, leading also to a relevant reduction of the environmental impact.

The Value of Machine Learning Models in Predicting Factors Associated with the Need for Permanent Shunting in Patients with Intracerebral Hemorrhage Requiring Emergency Cerebrospinal Fluid Diversion

ObjectiveTo assess the efficacy of machine learning models (MLMs) in identifying factors associated with the need for permanent ventricular shunt placement in patients experiencing intracerebral hemorrhage (ICH) who require emergency cerebrospinal fluid (CSF) diversion. MethodsA retrospective review was performed on patients with ICH requiring urgent CSF diversion who were admitted to our facility between July 2009 and May 2023. A binary logistic regression analysis was carried out to determine independent predictors linked to the development of shunt-dependent hydrocephalus following ICH. Five different machine learning models—random forest (RF), support vector machine (SVM), k-nearest neighbor (k-NN), logistic regression (LR), and Adaptive Boosting (AdaBoost)—were utilized to predict the need for permanent shunting in those with spontaneous ICH necessitating emergency CSF diversion. Additionally, RF techniques were applied to identify the factors affecting the need for permanent ventricular shunt placement in these patients. ResultsA total of 578 patients were included in the analysis. Shunt-dependent hydrocephalus occurred in 121 individuals (20.9%). In the multivariate analysis, the Graeb Score, the length of time the external ventricular drain (EVD) was in place, and an elevated intracranial pressure (ICP) greater than 30 mm Hg were significant predictors for the need for permanent CSF diversion (p<0.05). All predictive models showed commendable performance, with RF achieving the highest accuracy (0.921), followed by SVM (0.906), k-NN (0.889), LR (0.881), and AdaBoost (0.823). RF also excelled over the other models in terms of sensitivity and specificity, with a sensitivity of 0.912 and specificity of 0.892. The area under the curve (AUC) values for RF, SVM, k-NN, LR, and AdaBoost were recorded at 0.903, 0.820, 0.804, 0.801, and 0.798, respectively. ConclusionThis research demonstrates that machine learning models can effectively predict the need for permanent CSF diversion in patients with ICH who underwent EVD placement for urgent CSF diversion, offering important prognostic insights that could facilitate early intervention and lead to potential cost reductions.

On Assessing a Potential Reuse of the Indonesian Post-Operation Offshore Oil/Gas Pipelines as A Cold-Water Pipe for an Ocean Thermal Energy Conversion (OTEC) System: A Thermal and Fluid Dynamic Perspective

One of the main issues arising in offshore oil and gas decommissioning is associated with significant required costs. Research assessing the potential reuse of the post-operation offshore oil and gas pipeline (POGP) in Indonesia for the Ocean Thermal Energy Conversion (OTEC) system offer double the potential cost reductions in POGP decommissioning and OTEC development. In the context of OTEC development, research on increasing system efficiency makes a significant effort by modifying working fluids and usually by employing the assumption that the temperature of the cold seawater at the surface outlet of the Cold-Water Pipe (CWP) is practically the same as that at the inlet of the CWP at a depth of about 900 m. Unfortunately, this was not the case when the POGP was to be reused for the OTEC system because there was difficulty in applying additional insulation to the existing subsea pipelines. The temperature change in the cold seawater is even more critical considering that oil and gas operations at a depth of 900 m could be associated with more than 60 km of pipeline length to reach an onshore system for a typical seabed bathymetry. This paper assesses the potential reuse of the POGP as a CWP for the Ocean OTEC system. The temperature distribution within CWP is analyzed using a thermal and fluid dynamics approach. The results show that the reuse of POGP for the OTEC system could offer an excellent opportunity for capital cost reductions because the POGP has a remaining service life of over 20 years. However, the results of the analysis of heat and mass transfers show that the temperature change in cold seawater at CWP is about 3 to 6 oC, depending on the technical scenarios of the pipelines. The POGP used in the OTEC system could be suitable for a 20 kW OTEC system with practically no cost of pipelines, which usually accounts for a significant investment cost.

Design of a broadband Si3N4 waveguide amplifier based on a gain medium of ion-sliced titanium-doped sapphire.

In recent years, significant progress has been made in the on-chip integration of Ti:sapphire amplifiers and lasers, showing great potential in device miniaturization, cost reduction, and mass production. However, the further integration of such devices on standard CMOS platforms has been challenging due to its limits on the wafer bonding method between gain materials and substrates. Here, we present a novel, to the best of our knowledge, Si3N4 on-chip broadband optical waveguide amplifier scheme with an ultra-wide bandwidth of 650-900 nm and a peak gain of 28 dB based on an ion-sliced Ti:sapphire platform. The difficulty of heterogeneous integration is significantly reduced by growing Si3N4 thin films on Ti:sapphire. Moreover, by using homogeneous bonding combined with ion slicing technology, the target thickness of Ti:sapphire is expected to be easily controlled to less than 1 µm, greatly reducing the device volume and improving its practicality. Through subsequent experimental optimization, this work is expected to provide a new approach for the optimized design and experimental realization of on-chip Ti:sapphire waveguide amplifiers and lasers.

Water–Energy Nexus-Based Optimization of the Water Supply Infrastructure in a Dryland Urban Setting

Managing water supply systems is essential for developing countries to face climate variability in dryland settings. This is exacerbated by high energy costs for pumping, water losses due to aging infrastructures, and increasing demand driven by population growth. Therefore, optimizing the available resources using a water–energy nexus approach can increase the reliability of the water distribution network by saving energy for distributing the same water. This study proposes a methodology that optimizes the Water Distribution Network (WDN) and its management that can be replicated elsewhere, as it is developed in a data-scarce area. Indeed, this approach shows the gathering of WDN information and a model to save energy by optimizing pump schedules, which guarantee water distribution at minimal operational costs. The approach integrates a genetic algorithm to create pumping patterns and the EPANET hydraulic simulator to test their reliability. The methodology is applied for a water utility in the dryland urban setting of Lodwar, Turkana County, Kenya. The results indicate a potential reduction in energy costs by 50% to 57% without compromising the supply reliability. The findings highlight the potential of WEN-based solutions in enhancing the efficiency and sustainability of data-scarce water utilities in dryland ecosystems.

Optimization of operational strategies for industrial applications of solar-based green hydrogen

Renewable-based green hydrogen is emerging as a viable solution for decarbonizing energy-intensive industries. However, the fluctuating and intermittent nature of renewable energy sources requires careful consideration of operational strategies to ensure the safe and economical use of green hydrogen in industrial applications. This study examines the influence of operational strategies for electrolyzers and downstream processes on the cost of solar-based green hydrogen. The results demonstrate that optimal operational strategies for electrolyzers significantly impact the sizes of batteries and electrolyzers, reducing the Levelized Cost of Hydrogen (LCOH) by an average of 5.3%. Case studies further demonstrate that decentralized end-user supply strategies and cooperation with downstream processes can reduce LCOH by up to 39.8% for fully distributed end-users and by 24.2% with the introduction of supply tolerance. Additionally, the study evaluates the impact of grid backup, revealing that grid utilization can reduce LCOH by 12.9% in Houston, underscoring the potential for further cost reductions through grid decarbonization. These findings highlight the importance of optimizing operational strategies to improve the economic performance and market viability of green hydrogen systems.