Abstract Offshore wind power is an emerging technology identified as a source of future growth by EDF Group, for which the number of wind farm projects will potentially increase in the future. Although there is greater potential for offshore wind generation, the investment to construct is more significant than onshore due with higher installation costs (essentially for foundations, electrical connections, towers and turbines). In addition to this, operation and maintenance needs more important access methods. In this context, a tool ECUME has been developed in recent years to support EDF Group in making its choices of investment, technologies and the development of operating and maintenance strategies for offshore wind turbines. The tool evaluates the total mean cost of operation of an offshore wind farm project, as early in the development process as its design phase, in order to help decision making on investment, technology selection, and life cycle logistics and maintenance strategies. This paper proposes some improvements to ECUME in order to supply more accurate output indicators as a simple mean cost which is not sufficient to make investment decisions about a farm, a design or a maintenance strategy. These decisions in the offshore wind context are exposed to greater uncertainty of failure occurrence and inaccessibility. Risk measurement indicators better fitted to the decision context can take into account the uncertainties in the evaluation of risks. This allows EDF to understand the confidence that can be accorded to the mean value assessed and the range of values between which the indicator is distributed; the risk that an investment is not profitable despite a positive mean Net Present Value, .. To provide these indicators, we introduce an event model (based on Monte-Carlo simulation) to model failure risk and HMM (Hidden Markov Model) to model the evolution of meteorological and marine parameters and evaluate inaccessibility risk.
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