Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization

Wang, Meng, Yu, Hang, Yang, Yikun, Lin, Xiaoyu, Guo, Haijin, Li, Chaoen, Zhou, Yue ORCID: https://orcid.org/0000-0002-6698-4714 and Jing, Rui 2021. Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization. Applied Energy 302 , 117579. 10.1016/j.apenergy.2021.117579

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Abstract

Integrated energy systems (IES) can help achieve greater energy efficiency, and then ultimately promote a climate-neutral economy by utilizing local renewable resources. Demand-side energy-saving measures can reduce operational costs associated with energy usage. Most existing IES models, however, focus on supply-side optimization, while the demand-side energy-saving potential and its impacts on whole-system performance are still not clear. The increasing carbon tax makes it even more important to understand the interactions between supply and demand sides to achieve a sustainable system with a minimal carbon charge. Hence, this study proposes a co-optimization model to simultaneously optimize the supply and demand sides of an IES considering the impact of the carbon tax. A selection tree is developed to describe various demand-side envelope upgrading technologies, and a binary tree is established by generating a set of supply-side scenarios with corresponding probabilities. Based on these results, an improved two-stage stochastic programming model is proposed. The robustness of the modeling results was further validated by a simulation–optimization-based uncertainty analysis addressing price uncertainties. A case study in Shanghai indicates that the proposed co-optimization model achieves more cost-efficient solutions than supply-side-only optimization considering carbon tax. Introducing carbon tax can reduce the installed capacity of fuel-based energy technologies by up to 24% and greatly accelerate the penetration of renewables. The increasing carbon tax also promotes the adoption of more advanced energy-saving technologies. Uncertainty analysis reveals acceptable robustness of the optimal demand-side scheme and supply-side configuration with a deviation of less than 5% and a coefficient of variation of 7%. Overall, the observations of the proposed model and case study provide valuable insights for IES design considering an emerging charge of carbon tax.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Elsevier
ISSN:	0306-2619
Date of First Compliant Deposit:	9 September 2021
Date of Acceptance:	8 August 2021
Last Modified:	30 Nov 2024 07:30
URI:	https://orca.cardiff.ac.uk/id/eprint/143992

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