Browsing by Author "Strathern, M."

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    Exploring smart grid possibilities: a complex systems modelling approach
    (De Gruyter Open, 2015-08-26) Rylatt, R. Mark; Snape, J. Richard; Allen, Peter M.; Ardestani, Babak M.; Boait, Ekkehard; Fan, Denis; Fletcher, Graham; Gammon, Rupert; Lemon, Mark; Pakka, Vijay; Rynikiewicz, Christophe; Savill, Mark A.; Smith, Stefan; Strathern, M.; Varga, Liz
    Smart grid research has tended to be compartmentalised, with notable contributions from economics, electrical engineering and science and technology studies. However, there is an acknowledged and growing need for an integrated systems approach to the evaluation of smart grid initiatives. The capacity to simulate and explore smart grid possibilities on various scales is key to such an integrated approach but existing models – even if multidisciplinary – tend to have a limited focus. This paper describes an innovative and flexible framework that has been developed to facilitate the simulation of various smart grid scenarios and the interconnected social, technical and economic networks from a complex systems perspective. The architecture is described and related to realised examples of its use, both to model the electricity system as it is today and to model futures that have been envisioned in the literature. Potential future applications of the framework are explored, along with its utility as an analytic and decision support tool for smart grid stakeholders.
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    Modelling Organisational Evolution and Change - a Complex Systems Modelling Perspective
    (Cranfield University, 2008-05) Strathern, M.; Allen, Peter M.
    The cumulative output of these papers emphasise that modelling organisational evolution and change from a complex systems perspective makes a significant contribution to organisational studies and brings new insight and understandings both to theory and practice. It is also true that the studies and modelling presented in these papers has pushed forward the boundaries of complex systems science, again both in theory and practice. The papers have made new findings and understandings of the processes, drivers and outcomes of the evolution of social systems and organisations through the development of new evolutionary models and frameworks that contribute both to organisational and complexity sciences. They have through a number of innovations based in complexity science addressed questions in organisational science concerning the importance of knowledge and learning, together with questions about the evolution and survival of organisations and industries. These innovations have played back into and developed complexity science.