Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design
نویسندگان
چکیده
Process industry remains one of the difficult-to-decarbonise sectors globally. To mitigate industrial greenhouse gas (GHGs) emissions, an eco-industrial energy systems (e-IES) optimisation framework is proposed by coupling mathematical with clustering algorithms and first principle modelling. Within framework, a rooftop farming database was developed using biogeochemical simulations, which models seven crop growth in response to 10 cultivation conditions. Clustering algorithm applied analyse system data, along database, inform model. A Mixed Integer Linear Programming model optimize design considering trade-off between economic environmental objectives. The implications on e-IES their interactive effects decarbonisation were addressed. case study at park Suzhou China reveals that could generate mutual benefits from both cost GHG reduction perspectives. Planting lettuce indicates cost-efficient solution, planting tomato contribute most emission reduction. Compared PV spare rooftop, 2.4% 5.6% savings, as well 10.2% 16.3% be achieved respectively implementing farming. Overall, this demonstrates emerging perspective decarbonising sector simulation adopting cross-disciplinary approaches.
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ژورنال
عنوان ژورنال: Applied Energy
سال: 2021
ISSN: ['0306-2619', '1872-9118']
DOI: https://doi.org/10.1016/j.apenergy.2021.116773