4.8 Article

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

Journal

APPLIED ENERGY
Volume 302, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.117579

Keywords

Integrated energy system; Supply and demand-side co-optimization; Carbon tax; Stochastic programming; Uncertainty analysis

Funding

  1. National Key R&D Program of China [2018YFC0704602, 2016YFC0700305]
  2. GEF [1-A-CS-014]

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This study proposes a co-optimization model that simultaneously optimizes the supply and demand sides of an Integrated Energy System (IES), achieving higher energy efficiency and promoting a climate-neutral economy. By introducing a carbon tax, the study enhances the understanding of interactions between energy supply and demand, leading to a sustainable system with minimal carbon cost.
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.

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