Rene van de Pieterman, Contributor
April 10, 2013 | 0 Comments
LONDON -- Several European countries have defined targets to install and operate offshore wind energy as part of their renewable energy goals. According to these targets, more than 40 GW offshore wind power is expected to be installed across the region by the year 2020.
With an average turbine size of about 5-10 MW, between 4000 and 8000 wind turbines need to be transported and installed, operated and maintained. When other international developments are also considered, these numbers are much higher. This means that worldwide the required effort for operation and maintenance (O&M) of offshore wind farms will be enormous. And as a result the control and optimisation of O&M during the lifetime of these offshore wind turbines is essential for an economic exploitation.
The Need for O&M Cost Modeling
At present O&M costs of offshore wind farms contribute substantially (by €2-4 cents/kWh) to the life cycle costs, so it may be profitable to check whether the O&M costs can be reduced so that the cost per kWh can be reduced over the operational life of a wind turbine. Accurate cost estimations for future O&M of offshore wind farms can be used as input by both operators and original equipment manufacturers (OEMs), for example for deciding on new O&M contracts, making reservations for future O&M budgets, optimizing O&M at the end of a warranty period and periodically for the optimization of accessibility.
The key to efficient operation and maintenance of wind farms is a full understanding of the processes and cost drivers related to O&M. Most operators collect data related to their wind farm in separate documents, files and databases. Yet they do not necessarily have the tools or the working processes available to make maximum use of this data. As a result, some operators lack a full understanding of their wind farm and thus are unable to develop O&M strategies that reduce operational costs and ultimately increase revenues.
Making estimates and optimization of O&M costs and downtime is not an easy task: the amount of preventive, corrective and condition-based maintenance needs to be determined. Many parameters play a role and need to be quantified.
The most important are the number of failures which lead to a shutdown, the number of failures that can be repaired during regular visits, the repair strategy (varying from simple resets to expensive replacements with crane vessels), weather constraints, and costs for labor, spares and equipment. These parameters can be quantified using the operational data and experiences generated by the wind farm from day one of operation.
Most operators are currently not able to collect these kinds of data (failure data, repair data, logistics data, costs, SCADA data, data from load measurement campaigns, and data from condition monitoring) in a structured manner which allows semi-automated data analysis for estimating the total O&M costs.
Operation & Maintenance Cost Estimator Approach
In order to improve the situation, the Operation & Maintenance Cost Estimator (OMCE) approach was developed with two main parts: the OMCE Building Blocks (BBs) to process operational data, and the OMCE-Calculator to assess future O&M costs through maintenance strategy analysis.
The OMCE requires feedback of operational data from a specific wind farm under consideration, such as O&M data, data from measurement campaigns, and data from condition monitoring programs. Data about failures, repair actions, vessel usage, spare parts and weather conditions are analyzed to estimate the effort for unplanned corrective maintenance. Data from condition monitoring systems and load measurements are analyzed to estimate the effort for condition-based maintenance.
For this purpose four BBs have been specified, each covering a specific data set. Their main objective is to process operational data in such a way that useful information is obtained, and can be used for performance monitoring and as input for the OMCE-Calculator. For the processing of wind farm data by two of these BBs, a format is required to link the different maintenance actions to a single event.
Meanwhile, the OMCE-Calculator is a tool for the assessment of the expected O&M effort and associated costs for the coming period, where among others the information provided by the OMCE BBs is taken into account. Three types of maintenance should be considered to assess the O&M effort: unplanned corrective maintenance, condition-based maintenance and calendar-based maintenance. The structure of the OMCE approach is depicted in Figure 1.
Since operators and OEMs are the owners of the operational data, ECN and partner RWE defined a research project in the context of the Dutch Far and Large Offshore Wind (FLOW) program. The project goal is to apply the OMCE baseline model to an actual offshore wind farm, and assess the contribution in terms of cost reductions. Within this research project operational data is supplied by RWE as input for further development of the OMCE approach.
Structuring and Analysis of Wind Farm Data
To derive useful information from operational data which can be used as input for O&M cost modeling, it is important that data from sources related to O&M are collected in a structured manner. In fact, structuring raw O&M data is a key challenge.
Wind farm operators collect O&M data in different sources which are frequently stored at independent locations. Additionally, the format between data sources is often different, which makes them unsuitable for automated data processing (for example, data is reported per turbine, chronologically, per month, tri-monthly, etc). For example, data is reported on a per-turbine, chronological, per month, and tri-monthly basis. In addition, it is not always clear how different alarms, maintenance actions, downtimes and such are linked with each other. Therefore, within the OMCE approach the Event List was introduced.
An Event List can be best visualized as a list showing events per turbine in chronological order. It should include all fields that are relevant for further processing in order to obtain information about the failure behavior of components and use of equipment and spare parts. Within the context of the OMCE, an “event” is considered as a (sequence of) maintenance action(s) to prevent or correct turbine malfunctions. The total duration of an event is often longer than the sum of the individual maintenance actions. Maintenance actions can be remote resets, visits with technicians only, or the replacement of large components.
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