COST OPTIMISATION
FEATURE SPONSOR
ACCURATELY FORECASTING O&M COSTS
O&M costs for windfarms are difficult to predict and can vary significantly between windfarms and turbine technologies. O&M cost is by far the least predictable factor in a windfarm’s operating expenditure (OPEX) and investors are demanding more accurate predictions.
WHAT DRIVES UNCERTAINTY IN O&M COST?
Windfarm O&M cost is primarily made up of scheduled (planned) and unscheduled (unplanned) maintenance. The main source of uncertainty is unscheduled maintenance and the biggest driver behind this is what we call ‘technology risk’. This can stem from a new turbine type that is relatively unproven, an existing turbine type running a new gearbox variant, blades from a new supplier or a new control algorithm that has been rolled out by the OEM. The accuracy of an O&M cost forecast is critical to meeting the long term financial goals for a project.
SOME SOLUTIONS FOR AVOIDING COMMON PITFALLS INCLUDE…
• Utilise historical failure data – by keeping turbine information and reliability data in a large database, failure statistics can be quickly constructed for any turbine type, right down to subcomponent level. Romax InSight uses a vast historical database compiled from many years of past projects.
• The forecast must be site- specific – no two windfarms are the same. Factors such as turbulence, terrain, proximity to ridges or forests, the risk of icing or lightning and the suitability of the turbine to the site all play a part in O&M cost predictions.
• Logistics matter – if a site is located a long way from other windfarms, the lead time for large cranes can be long and the costs for mobilising the crane can be very high.
• There is no substitute for experience – talk to the site managers; read operational reports; interview technicians. People on site almost always know which turbines are problematic, even if they might not have the relevant expertise to diagnose the problem.
• Evaluate your supply chain – some turbine OEMs have gone out of business, been bought up or reduced their support for older models.
• Predictive maintenance matters – analysis has shown that moving to predictive or planned maintenance rather than a reactive strategy can save up to 40% in O&M costs. In practice, this can be delivered through better use of condition monitoring, particularly for older/smaller machines with no CMS, predictive tools such as component life models, along with better management of data relating to reliability, inspection and servicing using software such as Romax InSight’s Fleet Monitor and Field Pro.
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www.windenergynetwork.co.uk
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