Techno-economic analysis of decarbonized backup power systems using scenario-based stochastic optimization
Jonas Schweiger, Ruaridh Macdonald

TL;DR
This study evaluates various clean backup power systems using stochastic optimization to identify cost-effective and low-emission solutions for grid reliability and decarbonization, highlighting the importance of fuel replacement and hybrid technologies.
Contribution
It introduces a scenario-based stochastic optimization framework for comparing 27 backup power technologies, including hybrid systems, across multiple decarbonization scenarios.
Findings
Ammonia generators and hydrogen fuel cells with iron-air batteries are cost-effective decarbonization options.
Significant emissions reductions are achievable with moderate cost increases.
Fuel replacement plays a crucial role in emissions and cost outcomes.
Abstract
In the context of growing concerns about power disruptions, grid reliability and the need for decarbonization, this study evaluates a broad range of clean backup power systems (BPSs) to replace traditional emergency diesel generators. A scenario-based stochastic optimization framework using actual load profiles and outage probabilities is proposed to assess the most promising options from a pool of 27 technologies. This framework allows a comparison of cost-effectiveness and environmental impact of individual technologies and hybrid BPSs across various scenarios. The results highlight the trade-off between total annual system cost and emissions. Significant emission reductions can be achieved at moderate cost increases but deep decarbonization levels incur higher costs. Primary and secondary batteries are included in optimal clean fuel-based systems across all decarbonization levels,…
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Taxonomy
TopicsHybrid Renewable Energy Systems · Advanced Battery Technologies Research · Advanced battery technologies research
