Siemens is deploying industrial software to support operation of Galp Energia’s 100MW renewable hydrogen project at Sines in Portugal. Announced on 8 October 2026, the collaboration centres on a physics-based process digital twin and real-time optimisation tools. Galp expects the first phase of its GalpH2Park facility to begin operation around the end of the year, so its proposed hydrogen output should not be reported as current production.
Siemens says the plant is designed to produce up to 15,000 tonnes of renewable hydrogen annually. Galp also targets a reduction of approximately 110,000 tonnes of carbon dioxide equivalent per year in its Scope 1 emissions. Both figures depend on the project becoming operational and meeting its planned operating conditions; they are not verified outcomes from a full year of production.
The software deployment uses Siemens’ Hydrogen Performance Suite, an environment intended to bring together operational information, predictive modelling and production decisions. Its core Digital Process Twin is based on physical process models that represent the behaviour of plant equipment. The system can use measurements from operating equipment to update understanding of performance rather than relying on a static engineering simulation.
Siemens says it will supply digitalisation technology for Galp’s 100MW hydrogen project at Sines. The statement concerns planned systems and their intended operational benefits. An announced digitalisation scope does not establish measured hydrogen output, realised plant energy savings or production uptime. Those outcomes can only be assessed after equipment is installed, commissioned and operated with consistent performance reporting.
Siemens says the suite can incorporate live information from the plant and external sources, including electricity markets and grid operators. Bringing those streams together could help determine when production should rise or fall and how operating schedules affect electricity expenditure. The practical result will depend on the accuracy of incoming data, the model and the ability of plant controls to implement recommendations safely.
The company estimates that the suite can deliver energy savings of up to 15%. That is an estimated potential from the supplier, not a reported saving already achieved at Sines. Independent assessment would require an agreed baseline, comparable production conditions and measurements of actual electrical consumption once the plant is running.
Digital twins do not remove the need for process engineering. Industrial hydrogen systems have equipment constraints, water requirements, safety arrangements, power conversion equipment and operating limits. A software recommendation must be evaluated within those restrictions. Engineers also need effective control interfaces and procedures for dealing with inconsistent sensor readings or other abnormal conditions.
For a 100MW facility, efficiency and scheduling can have substantial financial consequences even where the percentage improvement appears small. Electricity is a major input to electrolytic hydrogen production, so the combination of procurement cost, operating hours and equipment efficiency contributes significantly to the delivered cost of hydrogen. This makes the link between digital engineering and commercial operation particularly relevant.
The Sines project also illustrates the challenge of scaling software from smaller production demonstrations to industrial facilities. Digital models must reflect how multiple equipment packages interact and how plant behaviour changes during ramp-up, steady operation and shutdown. The integration of data systems with the physical controls used by operators becomes a substantial part of the implementation work.
Siemens describes an integrated stack for process modelling, data analytics and real-time visualisation. Operators may use this to assess energy purchasing and production schedules while monitoring the plant’s actual condition. Whether the suite reduces downtime or operating expense in practice will depend on how it is configured, validated and maintained over time.
Galp’s wider ambition is to use renewable hydrogen to reduce emissions associated with its industrial activities. Achieving the reported Scope 1 reduction will depend on substituting hydrogen in the relevant processes and on the final configuration and output of the production facility. A digital control project can support that process, but it cannot on its own guarantee emissions outcomes.
The confirmed development is a supplier agreement for digital infrastructure at a specific industrial hydrogen project. The next evidence points will be commissioning, operational performance and measured electricity use. Those outcomes will determine how much of Siemens’ forecast benefit translates into verifiable savings during commercial production at Sines. For performance comparisons to be meaningful, analysts will also need to account for variations in electricity prices, plant utilisation and the profile of hydrogen demand. A fall in electricity expenditure could reflect changes in market prices rather than improvements in physical efficiency, while a different production schedule may change the cost per tonne. Separating those effects will be essential to assessing the value of the optimisation software.
