Double Effects Progressive Optimality Algorithm for Optimization of Large-Scale Hydropower System

Abstract

Optimization of large-scale hydropower system (OLHS) is a complex problem because of various coupled constraints. The computational complexity will increase exponentially with the increasing number of hydropower plants, which is also called “curse of dimensionality”. Progressive optimality algorithm (POA) is a classical algorithm to relieve the problem, and it has been widespread utilized in OLHS. However, POA has an important precondition during OLHS, which neglects the benefit produced by water head variation. In order to solve the problem, an improved algorithm called double effects POA (DEPOA) which takes water discharge effect and water head effect into account is proposed. Finally, the proposed DEPOA is applied to the optimal scheduling of large-scale hydropower system in the Yangtze River basin. The results indicate that DEPOA can improve the total power generation of all plants when compared to POA, which fully verifies the effectiveness of DEPOA for OLHS.