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Conference programme 

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Poster session

Lead Session Chair:
Stephan Barth, Managing Director, ForWind - Center for Wind Energy Research, Germany
Mauricio Almiray Jaramillo DONG Energy Wind Power, Denmark
Mauricio Almiray Jaramillo (1) F P
(1) DONG Energy Wind Power, Gentofte, Denmark (2) Technical University of Denmark, Lyngby, Denmark

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Presenter's biography

Biographies are supplied directly by presenters at OFFSHORE 2015 and are published here unedited

Mauricio Almiray is a Mexican Mechanical and Electrical Engineer, who started his professional journey in the oil industry in the Middle East and Latin America. After six years he decided to follow his passion for wind power and moved to Denmark, where he studied a Master of Science in wind energy at the Technical University of Denmark. He focused his thesis research on developing a statistical decision making tool for selecting the optimum power rating of substation transformers. He is now working as a Measurements Engineer for DONG Energy Wind Power.


Discrete event simulation model for selecting optimal substation transformers for offshore wind power plants


A key challenge for the offshore wind energy industry is to reduce the cost of electricity. Among the crucial components of an offshore wind power plant (OWPP) are the substation transformers due to their high cost, size and vital role in the transmission system. The transformer power rating defines a significant proportion of an OWPP CapEx. It does so directly, but also indirectly, through driving the specifications of other electrical equipment on the offshore substation and ultimately the structure itself. Furthermore, transformers greatly affect the operations and maintenance (O&M) costs because unplanned outages can cause large power curtailment.


A model utilising the Discrete Event Simulation (DES) method has been developed for the research work upon which this paper is based.
This is a time-domain method that models the operation of an OWPP in a natural manner throughout its lifetime. By performing multiple computer simulation runs, it is possible to construct a probability distribution of losses in electricity production and monetary units. In this way a decision of optimum transformer ratings can be made based on confidence intervals such as 90%, 95% and 99% instead of the traditional use of average values.

Main body of abstract

In recent years, there has been some research in the area of estimating the optimum number of transformers and percentage of redundancy. While these models provide useful estimates, all of them are based on mean values, which hide some of the information that is important for decision making. Average values conceal significant variations in the power production and losses of the system because in reality parameters like wind speed, equipment reliability and maintenance accessibility vary stochastically.
The objective of this study is to investigate the economic effects of the change of main parameters related to the substation transformers taking stochastic variations into account. The approach developed and the results obtained provide the foundation for a procedure to decide the optimum transformer power rating based on the most relevant parameters identified. Discrete Event Simulation (DES) is used to model the performance of a reference offshore wind power plant. This is because of its flexibility and ease to model different design options and to estimate the performance of the system functioning in stochastically changing environments and states of the system.


A reference OWPP is established based on realistic data. A simulation model is built to mimic the lifetime operation of the wind farm subjected to the variation of different parameters, such as wind speed and equipment reliability. The model is validated using a reference case and the output compared to expected values. A sensitivity analysis is run to examine the effects of specific parameters. With these results, a qualitative analysis is carried out to determine which factors have greater effects on the economics of the OWWP. Finally, an optimization loop is run to find the optimum transformer power rating.

Learning objectives
The presentation/ poster/ paper will allow the audience to:
• understand the principles and benefits of the analysis methodology
• appreciate the key drivers affecting the selection of the optimum transformer rating
• examine a method that assists in making decisions about the optimal transformer rating for an OWPP