Self-scheduling of cascaded hydropower stations based on Nonlinear Complementarity approach

A self--scheduling model of cascaded hydropower stations in day-ahead energy market is established in the paper. The objective of the model is to maximize generation profit. The multi stage model is nonlinear and contains complex constraints. To solve such a model is a challenging task. In this paper, Nonlinear Complementarity Method is proposed to solve the model The Karush-Kuhn-Tucker condition of the model is derived. By introducing the Fischer-Burmeister function, the model is solved as a sequence of nonlinear algebraic equations. In given example, the result of nonlinear complementarity method is compared with the improved genetic algorithm. And the numeric analysis verifies the correctness and effectiveness of the model and the algorithm.