Maros and Taro software
The hydrogen industry is becoming a key player in the global energy transition. It promises to be a clean and versatile energy source for sectors ranging from transportation to heavy industry. The biggest challenges to realizing this potential include the lack of mature infrastructure for producing, transporting and storing hydrogen. Current infrastructure is limited, with few large-scale projects in operation. This gap not only raises costs but also creates significant logistical barriers, particularly for storage and distribution. Moreover, hydrogen’s economic feasibility remains uncertain due to high production and distribution costs compared to more established energy sources.
DNV is ready to help unlock growth for your hydrogen project
For over 40 years, DNV’s Maros and Taro software solutions and advisory services have been trusted in the oil and gas sectors. Now, as hydrogen becomes central to the energy transition, these tools are proving to be equally essential for simulating hydrogen asset performance. By identifying opportunities for optimizing CAPEX and OPEX, Maros and Taro empower engineers to enhance production availability and evaluate more business cases across the asset lifecycle—from design to decommissioning. Even small improvements in availability (1–2%) can lead to significant ROI over a 30-year asset lifespan.
How is RAM analysis used in hydrogen?
Reliability, Availability and Maintainability (RAM) analysis emerges as a crucial tool for hydrogen companies striving to overcome these challenges and unlock long-term growth. Yet, while RAM is widely recognized in industries such as oil and gas, its specific application to hydrogen's evolving infrastructure is less understood. RAM analysis allows companies to systematically identify potential bottlenecks, optimize designs and improve operational efficiency across the hydrogen supply chain—a vital need given the nascent stage commercialization of hydrogen technologies.
Reliability targets focus on ensuring continuous and fault-free operations in hydrogen facilities, particularly for high-demand applications such as production and storage. Availability assesses the system's operational readiness, aiming to maximize uptime and ensure the supply chain remains robust. Meanwhile, maintainability addresses how easily maintenance can be performed effectively to avoid extended unscheduled downtime.
By integrating these three dimensions, a comprehensive RAM analysis with DNV’s Maros and Taro facilitates informed decision-making that enhances system performance while minimizing life-cycle costs. For hydrogen technologies, RAM analysis plays an even more pivotal role as it addresses the risks inherent in scaling up an industry that is still in its infancy. These insights not only help to mitigate inefficiencies but also increases investor confidence and stakeholder trust by demonstrating a commitment to reliability and performance.
Making the case for investment in renewable energy source
Renewable energy sources such as solar, wind and biomass pave the way for producing green hydrogen—a key component in meeting decarbonization efforts. However, integrating renewables with hydrogen production presents technical and economic challenges. Notably, there remains a shortage of comprehensive models that evaluate the feasibility and efficiency of hydrogen production from renewable energy sources. Although significant advancements have been made in solar and wind technologies, their intermittent nature presents a significant obstacle to the continuous and reliable generation of green hydrogen.
Addressing these issues is critical to overcoming the bottlenecks associated with large-scale green hydrogen production. RAM analysis can address these complexities by evaluating how different renewable energy systems meet hydrogen production demands. It factors in variables such as equipment downtime, maintenance, weather conditions and operational risks. This structured approach helps improve system performance, improve reliability and optimize capital (CAPEX) and operational expenditures (OPEX).
Optimizing hydrogen production performance
Water electrolysis is a promising technology for decarbonization, but its costs remain high due to inefficiencies and the capital intensive nature of renewable energy systems. While there are models for individual components such as electrolysis cells, evaluating the availability of the entire production system remains a challenge. This is crucial since a well-functioning hydrogen production system relies on the coordinated operation of various interconnected components. System availability analysis for hydrogen production considers four critical aspects:
- reliability of individual components
- system configuration
- the impact of component failure on overall performance
- repairable downtime
Unplanned failures not only lead to costly maintenance but also result in lost production due to unscheduled downtime. To mitigate these losses, developing system-wide RAM models is essential. These models help identify components that require further optimization and inform maintenance strategies, such as scheduled replacements and downtime minimization.
Simulating various storage solutions
Hydrogen storage plays a pivotal role, especially as the industry scales up for large-scale utilization in transportation, manufacturing and power generation. To meet current and future market demands, storage solutions must be reliable and robust, tailored to each application. However, optimizing storage requirements—considering storage capacity, operating conditions and potential system failures—can be a complex, time-consuming task without the right tools.
RAM modelling helps to simulate various operational scenarios to determine the optimal storage capacities and conditions needed to meet demand while accounting for potential system failures. For instance, DNV’s Maros and Taro can help predict how different sales scenarios affect tank utilization rates, or how upstream production failures might impact storage requirements. The capability to estimate storage capacity provides a necessary buffer to ensure that disruptions do not jeopardize the hydrogen supply chain.
Understanding the bottlenecks in hydrogen transportation
As demand for green hydrogen grows, efficient transportation is becoming an increasingly critical challenge, particularly for long-distance delivery via sea. Current transportation methods, however, often fail to account for potential disruptions. Weather variations, vessel breakdowns and port delays can significantly affect delivery schedules. The lack of integrated analysis leads to inefficiencies, potentially higher operational costs and unreliable hydrogen supply chains.
RAM modelling offers a solution by evaluating the resilience of hydrogen transportation networks. By factoring in variables such as vessel types, sailing times, tank sizes and weather conditions, RAM models help predict potential bottlenecks and provide strategies for optimizing fleet management to meet deliverability targets. This enables companies to assess whether their hydrogen supply chain can consistently meet contractual obligations.
Integrated hydrogen supply chain modelling
A comprehensive view of the hydrogen economy requires modelling the entire energy supply chain—from production through to storage, transportation and consumption. Modelling these interactions reveals operational constraints and inefficiencies across the supply chain that may not be evident when analyzing segments in isolation. For example, a production issue could cascade through storage and transportation, causing systemic inefficiencies.
By integrating these elements into a unified RAM model, operators can identify and mitigate potential bottlenecks across the entire system. Additionally, the model allows for optimizations that consider how changes in one part of the chain impact others. For example, increasing production may not lead to higher output if storage or transportation systems cannot handle the additional volume.
Learn more about how our hydrogen capabilities can help you unlock growth in this dynamic sector.
