This paper describes a set of anomaly-detection techniques and their applicability to wind turbine fault identification. It explains how the anomaly-detection techniques have been adopted to analyse supervisory control and data acquisition data acquired from a wind farm, automating and simplifying the operators' analysis task by interpreting the volume of data available. The techniques are brought together into one system to collate their output and provide a single decision support environment for an operator. The framework used is a novel multi-agent system architecture that offers the opportunity to corroborate the output of the various interpretation techniques in order to improve the accuracy of fault detection. The results presented demonstrate that the interpretation techniques can provide performance assessment and early fault identification, thereby giving the operators sufficient time to make more informed decisions regarding the maintenance of their machines

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The article define set of rules for future Electricity market structure, taking into account network codes, legislation and directives to ensure RES integration targets and Energy Union Dimensions in term of a fully integrated internal energy market and transition to a long lasting low-carbon society. Presented research studies are based on new way of power system operation development, namely Web-of-cell concept, of FP7 IRP ELECTRA. It's aiming to ensure conceptual E-market design and future power system 2030+ control solutions.