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

TL;DR

ElecSim is an open-source agent-based model that uses Monte-Carlo simulations to evaluate long-term electricity policies, demonstrating how carbon taxes can significantly increase renewable energy adoption by 2050.

Contribution

This paper introduces ElecSim, a novel open-source agent-based modelling framework that incorporates Monte-Carlo simulations for improved long-term electricity policy analysis.

Findings

Monte-Carlo simulation improves model performance by 52.5%

A carbon tax of £40/tonne CO2 leads to 70% renewable energy by 2050

ElecSim enables rapid prototyping of electricity policy scenarios

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.