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

Lookup NU author(s): Alex Kell, Dr Matthew ForshawORCiD, Dr Stephen McGough



This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by ACM, 2019.

For re-use rights please refer to the publisher's terms and conditions.


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 £40 ($50) per tonne of CO2 emitted would lead to 70% renewable electricity by 2050.

Publication metadata

Author(s): Kell AJM, Forshaw M, McGough AS

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Tenth ACM International Conference on Future Energy Systems (ACM e-Energy)

Year of Conference: 2019

Pages: 556-565

Print publication date: 15/06/2019

Online publication date: 03/07/2019

Acceptance date: 02/05/2019

Date deposited: 03/07/2019

ISSN: 978-1-4503-6671-7

Publisher: ACM


DOI: 10.1145/3307772.3335321

Library holdings: Search Newcastle University Library for this item

Sponsor(s): State Grid Geiri North America, IBM

ISBN: 9781450366717