Energy assessment strategies in carbon-constrained industrial clusters

Abstract

With the increasing climate change concerns, governments around the world are working on setting targets to mitigate its upsurge. Greenhouse gases (GHG), more specifically carbon dioxide (CO2), are the highest contributors to global warming. As a result, strict regulations for GHG emissions are being enforced, worldwide. Industrial sectors rely extensively on fossil fuels, the highest carbon emitters, and in turn face many challenges towards the compliance of the set emission standards. Therefore, finding solutions that would both meet the environmental requirements while satisfying the industries’ energy and fuel demands has been the focus of several studies over the years. This paper proposes a carbon reduction optimisation-based technique that assesses more than one source of energy with carbon utilisation technologies and assesses both its economic and environmental feasibilities. A systematic optimization-based model is introduced to develop sustainable utilization strategies to meet a cluster's product requirements, while meeting the set CO2 emission limits and maximizing associated financial returns. A Mixed Integer Nonlinear Program (MINLP) was developed to select the optimal allocation of the different fuels, the optimal source to sink mapping and carbon utilization configuration to meet the mentioned targets. Even though the integration of biomass, or a renewable source of energy as an alternative to fossil fuels, has been previously investigated by many, there exist no studies that targeted more than one type of fossil fuel in carbon constrained industrial cluster. Four different case studies consisting of a natural gas cluster, a coal cluster, a biomass cluster, and a blended fuel cluster, were analysed to illustrate the proposed model.