Modeling Time-dependent CO$_2$ Intensities in Multi-modal Energy Systems with Storage
Abstract
CO emission reduction and increasing volatile renewable energy generation mandate stronger energy sector coupling and the use of energy storage. In such multi-modal energy systems, it is challenging to determine the effect of an individual player's consumption pattern onto overall CO emissions. This, however, is often important to evaluate the suitability of local CO reduction measures. Due to renewables' volatility, the traditional approach of using annual average CO intensities per energy form is no longer accurate, but the time of consumption should be considered. Moreover, CO intensities are highly coupled over time and different energy forms due to sector coupling and energy storage. We introduce and compare two novel methods for computing time-dependent CO intensities, that address different objectives: the first method determines CO intensities of the energy system as is. The second method analyzes how overall CO emissions would change in response to infinitesimal demand changes. Given a digital twin of the energy system in form of a linear program, we show how to compute these sensitivities very efficiently. We present the results of both methods for two simulated test energy systems and discuss their different implications.
Cite
@article{arxiv.1806.04003,
title = {Modeling Time-dependent CO$_2$ Intensities in Multi-modal Energy Systems with Storage},
author = {Christopher Ripp and Florian Steinke},
journal= {arXiv preprint arXiv:1806.04003},
year = {2024}
}
Comments
This work has been submitted to the Elsevier Applied Energy for possible publication