Planning and scheduling of electrified steelmaking in renewable-rich power systems

Su, Pengfei 2025. Planning and scheduling of electrified steelmaking in renewable-rich power systems. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

The iron and steel industry (ISI), as one of the most energy- and carbon-intensive sectors, plays a pivotal role in achieving climate change mitigation targets. Electrifying steel production not only enables substantial reductions in energy-related CO2 emissions, but also enhances demand-side flexibility to support the integration of renewable energy into electricity systems. This thesis first proposes a bottom-up optimisation model to support the planning of electrification transition pathways for the ISI. To prevent CO2 emissions from a non-decarbonised power system, the model highlights the need to synchronize steel plant decarbonisation with timely renewable generation and grid infrastructure reinforcement. The framework jointly optimises long-term investment and short-term operations, thereby enhancing adaptability to the variability inherent in renewable energy supply. Building on the identified transition pathways, the thesis further investigates the operational scheduling of two key processes: the scrap-based electric arc furnace (EAF) and the hydrogen-based direct reduced iron combined with electric arc furnace (H2-DRI-EAF). This analysis aims to enable their participation in demandresponse programmes and to support grid stability. For the scrap-based EAF route, a multi-objective scheduling model is developed for steel plants equipped with renewable energy and energy storage systems. The model accounts for variability in processing time requirements across steel production orders, aiming to minimise electricity costs and indirect emissions while ensuring operational safety and continuity. For the H2-DRI-EAF route, a cost-effective scheduling model is proposed for plants powered by grid-assisted renewables. A resource-task network (RTN) model is constructed for each sub-process and integrated through boundary dependency constraints, allowing explicitly capturing the coupling constraints and interdependencies among sub-processes. The integrated RTN structure is then embedded within an optimisation framework to support economically efficient scheduling decisions. In summary, this thesis presents integrated modelling frameworks that bridge electrification pathway planning with operational scheduling in decarbonised steel production. The contributions are twofold: aligning the rising electrified steelmaking demand with the developments of renewable energy and the regional energy system, and leveraging the inherent flexibility of steelmaking for the response on the demand side. These insights are particularly relevant to stakeholders in the UK steel industry and electricity sector, providing actionable guidance for infrastructure-coordinated industrial decarbonisation. Ultimately, the findings support the UK’s net zero ambitions and offer a transferable modelling approach for other hard-to-abate sectors.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Schools > Engineering
Uncontrolled Keywords:	1. Iron and Steel Industry 2. Renewable-Rich Power System 3. Pathway Planning 4. Scheduling 5. Generalised Disjunctive Programming 6. Resource-Task Network
Date of First Compliant Deposit:	1 July 2025
Last Modified:	01 Jul 2025 15:19
URI:	https://orca.cardiff.ac.uk/id/eprint/179439

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