Comparison of Installation Scenarios for Offshore Wind Farms Using Operations Simulator with Markov Wind & Wave Weather Model

Abstract

Abstract This paper describes how operational scenarios for installing offshore wind farms were developed considering:onshore marshaling/assembly of wind generator components with discrete transport to, and installation on, site using self-elevating vessels (jack boats) andat site marshaling of wind generator components using a large storage/assembly/installation vessel permanently on location with routine resupply of equipment by barges. The scenarios were prepared as sequential weather (wind and wave) dependent steps based on prior wind generator installation experience and programmed into an operations simulator. The paper further describes development of a Markov weather model of transitional sea and wind states based on persistence data tables. Introduction Operational simulators are useful when modeling projects with sequential and repetitive operations, especially when the operations are dependent on external factors such as variations in weather. Installation of an offshore wind farm is an ideal example. In an offshore wind farm, typically a large number of wind turbines must be placed within an offshore grid, hooked up to a power junction facility and tied back to shore. The turbine system could be a structure fixed to the seafloor (fixed system) or a floating hull moored to the seafloor (floating system). Installation of the turbine system may be done all at once at each location or in two or more phases such as installation of foundations for fixed structures or moorings for floating systems, followed by installation of the turbine platform. Whether all at once or in phases, or fixed or floating, the simulator models the onshore logistics and assembly, load-out, sea transport, set-up and installation operations as sequential steps, or tasks, with individual durations and precedent events. Each step has upper weather operating limits, both wind and wave. Each step also has required predecessor steps. Exceeding weather limits and/or missing a predecessor step will cause a stand-by action until the condition favorably changes. Simulators that choose the "next step" sea or wind states based on transitional probabilities conditioned by the sea or wind state of the "current step", use a Markov process model. More simply stated, a Markov process model has memory of where it currently is, and models the sequencing of sea states more realistically than a simulator with no weather state memory such as one using a Monte Carlo process where the transitional probabilities are the same for each time step regardless of the current sea or wind state. The goal of a simulator is to compare alternatives for achieving the same objective - installing all the offshore wind turbine facilities in the least amount of time and/or lowest cost. With a simulator, it is possible to define a more optimal mix of marine equipment, development strategies, and working weather periods for given site locations, weather statistics and transit distances, among other factors. The simulator provides a good productivity comparison of alternative execution models and reasonable estimates of expected job duration, and standard deviation, for a specific execution model upon which cost and schedule forecasts can be based. The current study compares two development strategies for installing fixed turbine wind farms. The first strategy uses 1 or 2 self-elevating vessels that transit back and forth between shore support facilities and the wind farm site, each vessel carrying multiple cargoes of foundations and/or turbine assemblies. The second strategy uses a single construction vessel that is kept at the wind farm site with foundation and turbine assemblies transported to the construction vessel on feeder barges. The comparison is similar to an offshore pipeline installation done either by a reel vessel that goes to shore for resupply of pipe on its reel(s) or by a lay barge where joints of pipe are brought to and installed by the barge.