ABSTRACT
Composed of many subsystems, wind turbines are characterized by a high degree of systemic complexity. This chapter examines two different instances of the evolution of learning by using in relation to wind turbines and the resulting consequences for wind turbine siting and design. First, learning by using may usefully be construed as a complex, historical process characterized by varying degrees of contingency. Second, the agency of users is distributed and heterogeneous. Users depend on learning-for-using devices for the collection and systematization of knowledge. To assess the importance of the user assemblage of wind turbine owners, it is necessary to include the specific learning-by-using devices that were employed, such as the members' statistic and surveys, and to examine other types of input to changes in users' practices, such as the Wind Atlas method. Predictive knowledge about the expected power production of specific wind turbines at specific sites was important to wind turbine users.
