ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning

Alexander J. M. Kell, Matthew Forshaw and A. Stephen McGough

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Abstract: Due to the threat of climate change, a transition from a fossil-fuel based system to one based on zero-carbon is required. However, this is not as simple as instantaneously closing down all fossil fuel energy generation and replacing them with renewable sources -- careful decisions need to be taken to ensure rapid but stable progress. To aid decision makers, we present a new tool, ElecSim, which is an open-sourced agent-based modelling framework used to examine the effect of policy on long-term investment decisions in electricity generation. ElecSim allows non-experts to rapidly prototype new ideas. Different techniques to model long-term electricity decisions are reviewed and used to motivate why agent-based models will become an important strategic tool for policy. We motivate why an open-source toolkit is required for long-term electricity planning. Actual electricity prices are compared with our model and we demonstrate that the use of a Monte-Carlo simulation in the system improves performance by $52.5\%$. Further, using ElecSim we demonstrate the effect of a carbon tax to encourage a low-carbon electricity supply. We show how a {\pounds}40 ($\$50$) per tonne of CO2 emitted would lead to 70% renewable electricity by 2050.

Date: 2019-10
New Economics Papers: this item is included in nep-cmp, nep-ene and nep-env
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1911.01203

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