Dong Energy Wind Power reinforces profit with a simulation model

To operate a wind farm is a complex and expensive task that requires a lot of logistical planning. The weather plays a central role; e.g. wind and wave conditions need to be right so ships can move steadily between the turbines in the farm. You must also consider executing maintenance campaigns in the clement part of the year, how to staff your technicians accordingly, and not least scrambling to repair eventual breakdowns and keep turbines running to protect the yield off your investment.

Offshore windmill under construction

Related to these aspects, the logistic planning is comprehensive, and therefore it is important to have the right data and analysis tools for a global leader within offshore wind like Dong Energy Wind Power, that can provide valuable data and analysis. 

Previously, Dong Energy Wind Power had a tool that solely worked on expected outcomes based on average data values without variation. However, they wanted to have more detailed analysis embracing the inherent uncertainty of planning into the future and be able to investigate more options and outcomes. That was the reason for them to collaborate with SAS Institute.

Based on the challenges Dong Energy Wind Power were facing, and the results they would like to accomplish, SAS Institute came up with a solution built on advanced analytics in the form of a discrete-event simulation (DES) model that can evaluate the quality of a specific operation and maintenance logistics support setup.

“The DES model is a much more compelling but also demanding tool for us to work with, than the one we used before. We had to rethink our work process, deliveries etc., but it provides us with specific results and answers, that are very valuable to our business unit,” Hans Jacob Jørgensen, Senior Analyst in Dong Energy, explains.

A foundation for making better decisions

The model makes Dong Energy Wind Power able to predict which setup will be the most efficient from a cost benefit perspective evaluating compliance to maintenance programs, and the cost of the setup. The results from the model are fed directly downstream into Dong Energy Wind Power’s lifetime operational expense model that produces input to their financial forecast. Furthermore, the analysis team use the model to create risk profiles to identify and optimize the solution they recommend, and it can be developed to deliver risk profiles in the ongoing process as well. 

When applying the DES solution, it is possible to model a range of new logistic concepts that comes with maintaining wind farms. Often, one analysis is rarely enough, and with a DES model you will be presented with several scenarios that gives a better foundation for making important decisions. The model is mostly used to simulate the impact of a new process design by evaluating variants of the new design before initiating a costly implementation.

“It is a useful tool when we enter the building phase of a windmill farm, e.g. after winning a tender, because we can continually optimize the logistic part to make sure it runs as effectively as possible,” Hans Jacob Jørgensen says.

In his department, they are controlling the technical assumptions themselves and have made a procedure for collecting data from case to case. The data part is quite extensive so this is a core task for them. But as Hans Jacob Jørgensen says: “it is a tool that we can exploit even better as we get more familiar with it.”

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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