A Cultural Algorithm for Scheduling of Hydro Producer in the Power Market

This paper proposes an enhanced cultural algorithm to solve the profit-based optimal self-scheduling of a hydro producer in the electricity market. In the proposed method, differential evolution is embedded into cultural algorithm as its population space and situational and normative knowledge sources in belief space are applied to influence the variation operator of differential evolution. Furthermore, it uses three simple selection criteria based on feasibility to handle constraints effectively. Finally, self-scheduling of a hydro producer with four cascaded hydro plants along a river basin is used to illustrate the feasibility and effectiveness of the proposed method.