The Harmony Search (HS) method is an emerging meta-heuristic optimization algorithm. However, like most of the evolutionary computation techniques, it does not store or utilize the useful knowledge gained during its search procedure in an efficient way. In this paper, we propose and study a new optimization approach, in which the HS method is merged together with the Cultural Algorithm (CA). Our modified HS method, namely HS-CA, has the feature of embedded problem-solving knowledge. The HS-CA is further employed in an optimal wind generator design problem, and it can yield a superior optimization performance over the original HS method.