Short-term Hydropower Station Scheduling Under Deregulated Environment Based on Improved Evolutionary Programming

This paper proposes an efficient algorithm for short-term hydropower plant scheduling based on improved evolutionary programming (IEP). The water balance constraints, reservoir volume constraints, total water discharge constraints and the power constraints are taken into consideration. In common algorithm, the offspring is generated by adding a Gaussian random variable to the parent. In the improved evolutionary programming, a new chaotic mutation technique is used to generate the offspring. Numerical examples show that the improved evolutionary programming has quick convergence property and the desirable optimal solution can be fast and easily obtained through the proposed algorithm