ACEGES

The ACEGES model (Computational Economics of the Global Energy System) is a decision-making tool for energy policy by means of controlled computational experiments. [1] The ACEGES tool is designed to be the foundation for large custom-purpose simulations of the global energy system. The ACEGES methodological framework, developed by Voudouris (2011) [2] by extending Voudouris (2010), [3] is based on the agent-based computational economics (ACE) paradigm. ACE is the computational study of economies modeled as evolving systems of autonomous interacting agents. [4] [5]

The ACEGES tool is written in Java and runs on Windows , Mac OS and Linux platforms. The ACEGES tool is based on:

  • The MASON library – a discrete-event
  • The R Project for Statistical Computing
  • The GAMLSS framework

It is important to clarify that while the ACEGES model builds on the available scholarly and policy literature, it does not strictly follow any existing approach.

History

The ACEGES project was conceived by Vlasios Voudouris (with contributions by Michael Jefferson). Voudouris is now an Affiliate Professor at the ESCP Europe . The first version of the ACEGES decision-support tool was written in 2010. The ACEGES models energy demand and supply of 218 countries. The ACEGES tool was the main output of the ACEGES Project . The overall aim of the ACEGES project was to develop, test and disseminate an agent-based computational laboratory for the systematic experimental study of the global energy system through Energy Scenarios. In particular, the ACEGES framework and prototype can be used to help leaders in government,

Demonstrations

The ACEGES tool has been used, for example, to test the peak oil theory and to develop the plausible scenarios of conventional oil production by means of demonstration at:

  • 4th International Conference on Computational and Financial Econometrics, University of London & London School of Economics , 2010
  • 16th International Conference on Computing in Economics and Finance, Society for Computational Economics , 2010
  • Università Bocconi , 2010
  • UCL Energy Institute , 2011
  • Moscow State University , 2011
  • UK Energy Day: Sustainable Supply – An energy dans le day EU Sustainable Energy Europe Week supported by the Intelligent Energy Europe , 2011
  • Energy and Climate Change Select Committee (Westminster System) , UK Parliament – The UK’s Energy Supply: security or independence? Link , 2011

Details about the ACEGES decision-support tool (including supporting documentation) are available from ABM Analytics .

References

  1. Jump up^ Voudouris, V., Stasinopoulos, D., Rigby, R. and Di Maio, C., (2011), “The ACEGES Laboratory for Energy Policy: Exploring the Production of Crude Oil”, Energy Policy. Available from:Link
  2. Jump up^ Voudouris, V. (2011), “Towards a conceptual synthesis of dynamic and geospatial models: the fusing agent-based and Object – Field models”, Environment and Planning B: Planning and Design 38 (1) 95-114Link
  3. Jump up^ Voudouris, V. (2010), “Towards a unifying formalization of geographic representation: The Object-Field model with uncertainty and semantics”, International Journal of Geographical Information Science, Vol. 24, No. 12, p. 1811-1828Link
  4. Jump up^ Tesfatsion, L., 2006. Handbook of Computational Economics Volume 2: Agent-Based Computational Economics. Elsevier, Amsterdam, Ch. Agent-based Computational Economics: A constructive approach to economic theory.
  5. Jump up^ Tesfatsion, L and Judd, K. (2006), Handbook of Computational Economics, Volume 2: Agent-Based Computational Economics, North Holland

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