This research examines the risk of natural disasters for offshore wind turbines together with their potential wind energy capacity to help the site selection of offshore wind power farms. Through evaluations of expert questionnaires, we use the fuzzy analytic hierarchy process to weight how natural disasters damage the sub-assemblies of an offshore wind turbine, then obtain the natural disaster risk assessment model, and finally utilize ArcGIS Pro 3.2 to map the potential wind farm sites for the waters off Taiwan’s west coast. We identify that typhoons are the most threatening type of disaster to generators, rotor blades, and rotor hubs; earthquakes are the most threatening to towers; and lightning is the most threatening to transformers. For the whole wind turbine, wind is ironically the most threatening natural disaster, followed by lightning, sea waves, and then earthquakes. Lastly, we examine the results by overlapping the offshore wind farms developed and planned in Taiwan, which coincide with locations in relatively low risk and high wind speed areas.

Renewable energy is produced using renewable natural resources, including wind power. The Taiwan government aims to have renewable energy account for 20% of its total power supply by 2025, in which offshore wind power plays an important role. This paper explores the application of index insurance to renewable energy for offshore wind power in Taiwan. We employ autoregressive integrated moving average models to forecast power generation on a monthly and annual basis for the Changhua Demonstration Offshore Wind Farm. These predictions are based on an analysis of 39 years of hourly wind speed data (1980–2018) from the Modern-Era Retrospective analysis for Research and Applications, Version 2, of the National Aeronautics and Space Administration. The data analysis and forecasting models describe the methodology used to design the insurance contract and its index for predicting offshore wind power generation. We apply our forecasting results to insurance contract pricing.