The challenges that large windfarms face relate to the ones that the oil and gas industry has. The accessibility of wind turbines is due to remote locations sometimes as bad as for remote well sites. Similar to downhole equipment in oil and gas operations, wind turbine parts that require maintenance are located in areas that are not easily reachable.
The previous assignment fixed the jupyter notebook that is required for accessing the windfarm dataset and gave you insights about what the dataset has to offer. In this project, you will explore the dataset by changing the code and answer following questions:
- When and from which turbine cluster does AGL get the most energy (daytime or nighttime and which season)?
- What are the most important factors that influence the active power?
- Which single turbine in which cluster is the best producer and where is it located?
- Which turbine cluster shows the highest number of not working turbines and where is it located?
- Search for the costs of a repair crew to send to this location and state if it makes sense considering the current energy price level in Australia
- What are the operational characteristics that an operator could use to anticipate failure of a wind turbine?
Prepare a 10-minute presentation to your management and submit a report stating your findings.