Wind energy conversion systems such as wind farms are growing in numbers and capacity all over the globe. The onshore wind energy generation sector witnessed an increase of approximately 144 TWh during 2020, with onshore wind farms capacity addition of 108 GW, which is twice as much as the added capacity during 2019 (IEA, 2021). This staggering increase in capacity imposes higher needs for improved methodologies and expertise, in measuring the performance of wind farms and improving it. Cold climate regions are known to have an appealing potential for attracting wind farms installation and investments. However, the weather conditions in the cold climate regions impose risks and challenges to the operation and maintenance of wind turbines, and to the workers at the wind farms. Another challenge prevails in the lack of data and expertise related to wind energy projects in cold climate regions, due to the fact that wind farms instalments are relatively new in these regions. In addition, parts of the cold climate regions, such as the Arctic region, are known for their sensitive environment, and industrial projects could impact that sensitivity.
The risks and challenges discussed in this thesis can be classified in different ways, there are risks that are induced by the weather conditions that affect the operation and performance of wind turbines, such as the reliability, availability and maintainability of the wind turbines, and there are the risks that are induced by the wind farms that will affect the societal, the economic, and the environmental status of the surroundings of the wind farms.
This thesis introduces applicable methodologies that can be used to measure performance-related aspects of wind farms in cold climate regions, on different levels and operating under different scenarios. Moreover, in a performance-related context, a methodology for measuring the resilience of wind farms facing disruptive events is introduced, and lastly the different risks related to the operation of wind farms in cold climate regions are identified and analyzed through a methodology that allows for proper ranking of risks to prioritize the measures that can be used to mitigate those risks
