10.1016/j.jclepro.2018.02.309

Analysis of greenhouse gas emissions in electricity systems using time-varying carbon intensity

Abstract

Greenhouse gas (GHG) emissions from electricity generation are generally assessed using a yearly average carbon intensity (in carbon dioxide equivalent emissions per unit of energy). This masks the variability of emissions associated with different forms of generation over different timescales. Variability is a characteristic of electricity systems with high levels of renewable generation, where fossil fuels are typically used to meet any shortfall in supply. In this paper we argue that quantification of the time variability of carbon intensity is necessary to understand the detailed patterns of carbon emissions in electricity systems, particularly as future systems are likely to increasingly rely on a mix of time-variable generation types such as wind, hydro and solar. We analysed the time-varying carbon intensity of New Zealand's electricity sector, which has approximately 80% renewable generation. In contrast to many other nations, we found that carbon intensity did not consistently follow daily peak demand, and was only weakly correlated with demand. This result, and the finding that carbon intensity has significant seasonal variation, stems from the dominance of hydro (albeit with limited storage capacity) in New Zealand's generation mix. Further investigation of the operating regimes of the fossil fuel generators, using time-varying analysis, indicates that New Zealand's electricity system is sub-optimal from a GHG emission perspective, with more coal generation than would seem to be required. Two policy measures, which also generalize to other countries, are proposed to address this issue: (i) the creation of an electricity capacity market – providing revenue for standby fossil fuel generation capacity without the need for continual generation; (ii) use of time-varying carbon intensity to inform demand-side measures and decisions about new renewable generation.Peer Reviewe

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10523/8032oai:ourarchive.otago.ac.nz:10523/8032
Last time updated on July 9, 2019

This paper was published in Otago University Research Archive.

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