Proceedings of 6th International Symposium on Intelligent and Manufacturing Systems, October 14-16, 2008: 42-53 ©Sakarya University, Department of Industrial Engineering 42 Wind Energy: Intelligent Manufacturing Perspective Andrew Kusiak Mechanical and Industrial Engineering 2139 Seamans Center The University of Iowa Iowa City, Iowa 52242 – 1527 USA Tel: 319-335-5934 Fax: 319-335-5669 Email: andrew-kusiak@uiowa.edu http://www.icaen.uiowa.edu/~ankusiak Abstract The growing demand for wind power has resulted in a market that naturally favors development of new wind farms over improvement of their performance. A chain of opportunities for performance improvement of any wind energy project parallels the supply chain activities. Raising energy and transportation costs are a complicating factor of the performance improvement projects. One of the weakest points in wind power generation is the low predictive accuracy of the energy output. Similar to industrial corporations managed by enterprise-wide systems, a software solution for prediction of wind farm performance (including the amount of energy produced) is needed. The envisioned wind farm performance prediction software should be able to predict the amount of energy to be produced on different time scales, ranging from seconds to days. Such software would transform a wind farm into to a wind power plant. A novel approach to modeling the performance of individual wind turbines as well as their collection (a wind farm) is discussed. Besides the utility scale applications, the proposed solution can be scaled down to optimize residential wind turbines (KW range) dispersed over large areas. The lower sensory capability of household turbines will be mitigated by the wide availably of wireless communication and internet connectivity.