Green power has attracted the world's attention and the proliferation of wind farms serve this purpose. However, wire connections among power sources and loads can be very costly in addition to the investment on the equipment. The geographical terrains also affect the routing cost, because the connection between two coordinates are often impractical to be a straight Euclidean distance. The Earth is a globe shape with curvature and a terrain can have rugged floors or water surfaces that hinder the convenience of wiring. The objective of this paper is to take advantage of a developed heuristic and apply learning algorithms to determine the best wind power sites. The goal is to conserve wiring expense and accommodate power loads. Terrain knowledge is incorporated by utilizing the geographical databases. Experiments are conducted to demonstrate the approach and justify cost savings. It is expected that this paradigm can be expanded to address more factors and support other green energy application domains.
All Science Journal Classification (ASJC) codes
- Computer Science(all)