Power system expansion planning under global and local emission mitigation policies

Daniela Quiroga, Enzo Sauma, David Pozo

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)

Abstract

This work analyzes the impacts on the power system expansion planning of implementing CO2 and local pollutant emission taxes under five different policy-relevant scenarios. To do this, we have formulated and implemented an optimization model based on a mixed-integer linear program, which determines the optimal expansion plan considering the installation of both large-scale power plants and renewable-based distributed generation. An important characteristic of the proposed model is that it includes a detailed formulation of the power system. Moreover, differently than existing literature, special attention is given to the analysis of the spatial-temporal distributive effects of pollutant taxes, considering both global and local pollutant emissions. The method is applied to the main Chilean power system. Our results indicate that global and local pollutant taxes significantly impact both planning and operational decisions in the power system. In particular, pollutant taxes may have significant spatial distributive effects, as shown in the analysis of 13 regions of Chile, leading to damages in some specific regions while relatively benefiting others. Our results also show that the availability of renewable energy capacity may improve the effectiveness of pollutant taxes. Particularly, adding 1.5 GW of hydro capacity to the Chilean system allows avoiding around 32 GWh of fossil fuel generation per year, saving more than 1.5 billion US$ in the 10-year horizon considered. The proposed method and qualitative results are sufficiently generic to apply to any other jurisdiction.

Original languageEnglish
Pages (from-to)1250-1264
Number of pages15
JournalApplied Energy
Volume239
DOIs
Publication statusPublished - 1 Apr 2019

Keywords

  • Carbon tax
  • Energy policy
  • Local pollutants
  • Pollutant emissions
  • Power system planning

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