A Framework for Optimal Design Life as Applied to Wind Energy System Operation

Traditionally, engineers view the durability of a product as a requirement. However, the durability can also be a variable that is decided by the enterprise. The system life decision has global, social, environmental, and economic impacts. The proper choice of system life becomes even more important as companies change their business model to take advantage of the benefits offered in Industry 4.0 technology. Namely, the businesses can use technology to collect real-world data, in real time to make educated decisions. This decision seeks to balance the system cost per day and the obsolescence risk. For example, if a system is designed for long life, it may become obsolete sooner due to system innovation making the cost per day savings overestimated. A review of the literature indicates that there is a need to study the decision of durability, especially in upgradeable systems. In these particular systems, parts can be substituted during the life of the system to improve performance and mitigate obsolescence. Although the durability decision is important to virtually all objects, this research focuses on renewable energy systems. To determine the optimal life of a wind turbine, one must first have design tools that can accurately predict the fatigue life of various components of the wind turbine. Accordingly, this work proposes a framework for designing wind turbine component life that is optimized with respect to cost and service life. Four wind turbine tower designs with fatigue life of 20, 30, 40, and 80 years are compared in terms of cost. The results show that the tower with the longest design life is the optimal selection. These results can be improved by connecting the quality of life for the users of the energy collected. This can be done through the use of Industry 4.0 data derived from digital twin formulations, and cyber-physical-social (CPS) systems.