Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

Open source, agent-based energy market simulation with python

Lincoln, Richard and Galloway, Stuart and Burt, Graeme (2009) Open source, agent-based energy market simulation with python. In: 6th International Conference on the European Energy Market, 2009. EEM 2009. IEEE. ISBN 9781424444557

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

Increasingly, the electric energy transmitted and distributed by national power systems is traded competitively in free markets. Long-term decisions must be made by authorities as to the structure of energy markets and the regulations that govern interactions between participants. It is not practical to experiment with real energy markets and in order to establish the potential effects of making these decisions there are few options but to simulate the markets computationally. This paper proposes that the complexity of power systems and the associated energy markets necessitates an open approach in their modelling and simulation. It presents an open source software package for simulating electric energy markets using the Python programming language. Power systems and their associated constraints are modelled using traditional steady-state analysis techniques. While market participants are represented by reactive agents that learn through reinforcement. The software and all of its dependencies are open and freely available to the scientific community.