Time series analysis-based dimensioning of decentralized hydrogen production systems for manufacturing applications

Abstract The decarbonization of energy-intensive manufacturing processes is crucial for reducing greenhouse gas emissions, particularly in high-temperature applications, such as forging and heat treatment. Decentralized hydrogen production through electrolyzers offers a potential solution. However, current system dimensioning approaches are typically tailored to specific use cases, such as refueling stations, or centralized setups, limiting their adaptability to decentralized manufacturing contexts. This paper presents a novel method for dimensioning hydrogen production systems, specifically designed to accommodate for the complex, time-variable energy demands and operational constraints of manufacturing environments. The method application begins with a time series analysis to isolate representative periodic elements within hydrogen demand profiles, capturing recurring demand patterns essential for strategic planning. The following step incorporates a cross-technology mathematical model that describes the relationship between an electrolyzer’s electrical power input and the achievable hydrogen output volume flow, integrating operational constraints, such as partial load performance and load change limits, to reflect real-world flexibility requirements. Subsequently, a nonlinear programming-based algorithm is employed, enabling the optimal dimensioning of the hydrogen production system – comprising both electrolyzer and hydrogen storage – while minimizing total system costs within defined technical constraints. An industrial case study and a sensitivity analysis validate the method’s robustness and practical applicability. This comprehensive approach offers manufacturing companies a practical, cost-effective framework for the strategic integration of decentralized hydrogen production systems, supporting broader decarbonization initiatives across energy-intensive sectors.