International audienceIn this paper, an advanced model, based on recurrent high order neural networks, is developed for the prediction of the power output profile of a wind park. This model outperforms simple methods like persistence, as well as classical methods in the literature. The architecture of a forecasting model is optimised automatically by a new algorithm, that substitutes the usually applied trial-and-error method. Finally, the online implementation of the developed model into an advanced control system for the optimal operation and management of a real autonomous wind-diesel power system, is presented

In this paper, an advanced control system for the opt1 mal operation and nianagenient of isolated power svstenis with increased renewable power integration is presented The control system minimises the production costs through on-line optimal scheduling of the power units, taking into account short-term forecasts of the load and the renwable resources. The power system security is supervised via on-line security assessment modules, which emulate the power system frequency changes caused by preselected disturbances. For each of the above functions, a nuinber of techniques has been applied both conventional and AI based. The system has been installed in the Dispatch Center of Crete since June 1999, and is currently under e\Valuation.

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