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The ongoing liberalisation of the power sector adds a new dimension to the main issues in modelling of power systems. The very complex interactions and interdependencies among power market participants are much like those studied in game theory. However, the strategies used by market participants are often too complex to be conveniently modelled by standard game theoretic techniques. In addition, there has been much less research in the field of dynamic strategic behaviour and their impact on the electricity price in European markets. In this paper, we show new, prosperous combination of computational science and new ideas in evolutionary economics and cognitive science offering appealing extensions to traditional game theoretical modelling. We demonstrate the feasibility of implementing our approach in Matlab using learning algorithm and illustrate its advantages in more detailed and realistic representation of the strategic behaviour of biggest power producers in European power market.

The liberalisation of the elec tricity mark et in Co nt inenta l Euro pe started in th e late 1990 ' s and is still ongoing. In th is paper, past developments in this mar ket are ana lysed and co nditions necessary to enha nce co mpetition in thi s market in the long run are deri ved.Our major co nc lusion is that at a minimum, the fo llowi ng conditions wou ld be necessary to bring about effective co mpe tition in th e long run : (i) co mplete owners hip se pa rati on of the tran smi ssion gr id fro m ge neration an d supply in all coun tr ies and sub-ma rkets ; (ii) ade quate ca pac ity margin in ge ne ration; and (iii ) a suffic iently large number of ge nerato rs sharing th is cap acity. As it is not likely that these co nditions will be fulfil led , the pro sp ects for a vibrant competition in Co ntinenta l Euro pe are doubt ful.