Operation & Maintenance Cost Estimator (OMCE)

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Main results and recommendations

The following main results and recommendations are obtained through this research project:

ECN’s Operation & Maintenance Cost Estimator (OMCE) approach is further developed to provide the offshore wind industry with an integral O&M solution to reduce the costs of energy for offshore wind. ECN can assist wind farm operators to implements (parts of) the OMCE approach upon request.
ECN is actively approaching and searching for project partners which are interested in implementing the OMCE for a longer period of time. The main goal of such a project is to assess the added value of the OMCE in more detail.
Based on a case study, the potential of the OMCE is further quantified. The FLOW cost model is applied to calculate the cost reduction effects over the entire lifecycle of a wind farm which results in an average cost reduction of approximately 1% compared to a representative cost baseline for Dutch wind farms in 2010.

Project description

For the initial Operation & Maintenance (O&M) planning of offshore wind farms in the development phase, cost modelling tools such as the ‘ECN O&M Tool’ give a good estimation of averaged long term maintenance costs and downtime. However, during the operational phase of the farm it is essential to make use of the historical operational data of the farm and update the O&M cost estimations on a regular basis to e.g. make reservations for future O&M budgets, negotiate O&M contracts, make investment decisions for new vessels etc. Therefore, ECN developed the Operation & Maintenance Cost Estimator (OMCE) which aims to provide the offshore wind industry with accurate tools and procedures to implement such an approach. Figure 1 shows the detailed structure of the OMCE approach.

As part of the Far and Large Offshore Wind (FLOW) innovation program, ECN together with industry partner RWE Offshore Wind Nederland (ROWN) started the FLOW project titled “Development and demonstration of the Operation & Maintenance Cost Estimator (OMCE)” with the objective to further develop and implement ECN’s OMCE approach. The main project objectives are:

A. Further development of tools and working procedures using data and feedback from an existing RWE wind farm to develop an OMCE baseline model.
B. Make developed OMCE baseline model available to other offshore operators.
C. Apply the model for an analysis of expected O&M costs for an operational offshore wind farm.
D. Validate the model by implementation of the OMCE approach in an operational offshore wind farm.

The FLOW OMCE project is executed through five Work Packages (WP’s):

WP’s 1-3 focus on further development of the Event List procedures for structured data collection (WP1), the Building Blocks tools for the analysis of operational data (WP2) and the OMCE-Calculator tool for the calculation of the expected O&M effort (WP3). These WP’s represent the development of the baseline OMCE model in project objectives A and B.
WP’s 4 and 5 focus on applying the OMCE baseline in an operational wind farm to validate the model and assess the added value as part of project objectives C and D.

Project results
The Event List is used to collect and structure wind farm operational data from various data sources with the objective to chronologically list all maintenance events for each wind turbine in a wind farm. The location of the Event List within the OMCE approach is in between the raw wind farm data and the OMCE Building Blocks, see Figure 1. ECN and RWE performed an inventory of available data sources for RWE’s Rhyl Flats wind farm in the Irish Sea. The inventory revealed that O&M data are stored in many different sources at independent locations. The operational data were analysed initially to determine whether the fields of the existing Event List format could be filled or should be updated. Based on the analyses results, some of the fields of the Event List format are updated to match the available on-site data. Examples of such fields are the travel time of access equipment and the number of hours of weather downtime. The manual structuring of operational data has proven to be labour intensive and one of the main recommendations from the analysis is that automated procedures should be developed to connect the Event List format to a computerised maintenance management system.

Once the operational data is structured in the Event List format it can be processed by the OMCE Building Blocks (BB’s) data analysis tools to obtain information on amongst others: weather conditions, equipment usage, crews, logistics of spare parts and failures rates of wind farm components. The processed data can later on be used as input for the OMCE-Calculator. In total five BB’s are specified as part of the OMCE, see Figure 1. The demonstration versions of BB’s ‘Operation and Maintenance’ and ‘Logistics’ are improved by ECN based on feedback from RWE as follows:

The tools are now able to read the updated Event List format.
The information obtained from the output is now more consistent to the required input of the OMCE-Calculator.
The tools are integrated in a single software tool for data analysis.
A reporting module is added which can produce automatic reports in PDF and Word formats.

Additionally, ECN and RWE have developed detailed specifications for the analysis of meteorological and wave buoy measurements. Amongst others it is determined that this Building Block should supply the wind shear model parameters, time series of wind speed and significant wave height measurements, and the operational limits for each equipment applied for maintenance.

The OMCE-Calculator is the tool to estimate the O&M effort for the coming years by using the output of the OMCE Building Blocks, see Figure 1. The OMCE-Calculator is a time domain simulation tool developed in MATLAB. In the project, the demonstration version is developed into a fully functional software tool where the following key improvements are made:

The functioning of the OMCE-Calculator demo was reviewed and the software is validated by a comparison study to the ECN O&M Tool.
Additional functionality is implemented based on feedback from demonstration users and RWE such as additional output graphs, modelling alternative access vessels, modelling variable feed-in tariffs, and many more.

The User Manual is updated to match the latest version of the toolThe developments on the OMCE Event List, Building Blocks and Calculator as described above have completed the baseline model of the OMCE. The next step in the project is to implement the baseline model of the OMCE for a longer period of time to validate the model and assess the added value in more detail. Unfortunately, this step could not be made in the FLOW project as a wind farm for implementation was not available. Therefore, ECN is actively approaching and searching for interested project partners which would like to conduct a project to implement the OMCE.

Contribution to cost and risk reduction of far-offshore wind energy
Based on the field data collected for RWE’s Rhyl Flats wind farm a limited case study was performed which demonstrated the potential of the OMCE approach to reduce the O&M costs by approximately 10% and decrease production losses by approximately 4%. The results from this study are attached as Appendix F to this report and are also publicly available through ECN’s website:

Asgarpour, M.; Pieterman, R.P. van de; “O&M Cost Reduction of Offshore Wind Farms – A Novel Case Study”, ECN-E--14-028, July 2014.

The FLOW cost model is applied to calculate the effects over the entire lifecycle using the aforementioned cost reductions. This has resulted in a total cost reduction of approximately 1% compared to a representative cost baseline for Dutch wind farms in 2010. Given that the OMCE couldn’t be implemented for a longer period of time, ECN considered an uncertainty of 50% in the proposed cost reductions. The proposed uncertainties result in a lower limit of 0.7% and an upper limit of 2% for the total cost reduction as calculated with the FLOW cost model.

Presentations

Windkracht 14: Development and demonstration of the OMCE to estimate the future O&M costs