Hydro Generation Scheduling Using Refined Genetic Algorithm

This paper presents a novel solution algorithm based on a refined genetic algorithm for solving the hydro generation scheduling problem. In this work, complete solution algorithms and encoding/decoding techniques are proposed for solving different types of hydro plants involving hydraulically independent plants, hydraulically coupled plants, and pump-storage plants. In the proposed approach, the hydraulically coupled plants which are located on the same river are solved concurrently as a multi-plant scheduling problem rather than as several single-plant scheduling problems in sequence. The difficult water balance constraints caused by hydraulic coupling are embedded and satisfied throughout the proposed encoding and decoding algorithm. The proposed approach is applied with great success to the actual Taipower system, which consists of two hydraulically independent plants, three hydraulically coupled plants, four pump-storage plants, and 34 thermal units.