In the global energy transition where the shift from fossil fuels to renewable energy is needed, wind energy is a growing industry. In the offshore wind industry, Service Operation Vessels (SOVs) are needed to operate and maintain wind farms. To reduce the environmental footprint of SOVs at offshore wind farms, the possibility of battery-electric sailing with plug-in charging at offshore wind farms is investigated. Battery-electric sailing has been applied to many vessels, however, it is mostly applied to ferries which operate with a fixed daily schedule. An SOV has a variable operational schedule and therefore the energy use calculation is more complex than for a fixed operational schedule.

At the root of calculating the daily energy use are the daily schedules of the SOV. The daily schedules are determined by the maintenance strategy applied by the contractor, and the optimisation of the vehicle routing problems. However, in the concept design phase, this method is too detailed to get a useful and trustworthy result. A discrete event simulation is suggested to create daily operation schedules of the SOV where the power and duration are still calculated for, but the too-detailed routing information is left behind. The daily schedules are structured as a vehicle routing problem with delivery and pick-up with full-day and half-day tasks. They are influenced by wind farm characteristics, vessel characteristics, and operational characteristics.

With the information that is known about the daily schedules and the input parameters, a Monte Carlo simulation is deemed the most appropriate. This method takes into account the likelihood of input variables, can deal with these uncertainties, and still give a useful, trustworthy, result. The model creates many daily schedules of which the resulting maximum energy use, by the law of large numbers, converges to the expected value. For the idle time, a charging module is implemented to make the choice between standby and charging.

A case study is done to look at the influence on the results of design choices and boundary settings. The inputs that are varied during the case study are: with or without charging, the number of charging points, the layout of the offshore wind farm, the workday length, the task distribution and the charging power. The daily energy use results for a 12-hour workday vary from a bit over 4000 kWh with not that many tasks and six charging points, to over 10000 kWh for many tasks and only one charging point. Individual inputs can make a difference from 500 to 3000 kWh. The case study gives a good insight into how much influence different parameters have on daily energy use and shows that offshore charging during the day can drastically reduce the maximum battery energy needed during the day.