Data-driven optimisation framework for assessing energy and emission saving potentials in foundation industries
Industry energy consumption represents almost 40% of current global total final consumption and is still dominated by fossil fuels, e.g., gas. As estimated by the International Energy Agency (IEA) in 2021, this high level of reliance on fossil fuels together with the CO2 emitted in raw material reduction processes (e.g., from limestone in cement
production) results in the industry sector emitting 8.7 Gt CO2. This makes industry the second‐largest emitting sector after power generation. Hence, sustainable production systems are vital for the reduction of CO2 emissions and the achievement of the Net-Zero goals. Methane emissions from fossil fuel operations would need to fall by
77% by 2030, and 90% by 2050. Industrial energy efficiency innovation will play a huge role in achieving this target.
The IEA predicts that efficiency increases will prevent 1Gt of carbon emissions by 2030 alone. Full efficiency potential requires system-wide optimisation and studies show that optimised and energy-efficient production processes can give energy savings from 10% to 50%. Furthermore, concerns over climate change are likely to make
inefficiency and high emissions increasingly serious business liabilities. This project aims at contributing to this timely and relevant challenge by devising and assessing an innovative data-driven optimisation framework to identify operational and energy management strategies resulting in significant energy and emission savings. This
advanced optimisation framework can be used as a decision-support system to inform industries about more efficient energy management strategies, which still achieve the intended production targets. The potential energy and emission savings will be assessed and quantified based on real data and processes from an actual industry in
the paper sector. It is worth noting that, although the devised optimisation framework is assessed on an industry in the paper sector, the devised methodology can be applied to any foundation industrial sectors.
Dr. Alessandra Parisio
University of Manchester
Published: September 23rd, 2022
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