Finding optimal solutions for reaching maximum power energy of hydroelectric plants in cascaded systems


Nguyen T.T., Nguyen T.T., Pham T.D.

Source title

Journal of Ambient Intelligence and Humanized Computing

Publication year

In this paper, independent optimization operation strategy and global optimization operation strategy for cascaded hydropower plants are studied in aim to maximize total power energy of all the cascaded hydropower plants. In the first strategy, upstream hydropower plants are optimally operated first and then obtained results are used to operate downstream hydropower plants. On the contrary, all hydropower plants are operated simultaneously in the second strategy. The two strategies are accomplished by using an improved cuckoo search algorithm (ICSA) together with particle swarm optimization (PSO), cuckoo search algorithm (CSA), Salp Swarm Algorithm (SSA), sunflower optimization algorithm (SFO), equilibrium optimizer (EO) and marine predator algorithm (MPA). Result comparisons can lead to the evaluation that the first strategy can bring more benefits for upstream plants whereas the second strategy is more suitable for downstream hydroelectric plants. For the purpose of maximizing total energy of all plants, the second strategy is more effective than the first strategy. Compared to PSO, CSA, SSA, SFO, EO and MPA, ICSA method finds higher energy with a highly faster speed. Thus, the paper suggests the second strategy should be executed for hydroelectric plants in cascaded reservoir systems and ICSA can be a favorable method for implementing the recommended optimization operation strategy.