A successful candidate strategy with Runge-Kutta optimization for multi-hydropower reservoir optimization

The hydropower problems are non-linear and non-convex in nature; therefore, optimizing the operations of multi-hydropower plants in a multi-reservoir system is always challenging and complicated. In order to develop an appropriate optimization technique to address such difficulties, an efficient search strategy with a high capacity to move from exploration to exploitation in the feasible domain is required. This paper provides a successful candidate strategy combined with Runge-Kutta optimization (ScsRUN) to quickly, accurately, and reliably optimize multi-reservoir hydropower problems. Specifically, the successful candidate strategy is used to improve the stability between exploration and exploitation phases; a modified version of enhanced solution quality implemented in the original RUN (MESQ) is utilized to enhance the efficiency of solutions and break free from local positions; and sequential quadratic programming is performed as a robust local search method to accelerate convergence. The new optimization method developed in this study was evaluated by using 29 test functions and a real-world, complicated multi-reservoir problem. It was demonstrated that ScsRUN outperformed other advanced optimization methods in terms of efficiency and reliability. ScsRUN can be widely used to solve a variety of complicated problems. The last source codes of RUN algorithm is publicly available at https://imanah madianfar.com.

Automated summary

This paper presents an efficient search strategy, ScsRUN, to optimize multi-reservoir hydropower problems. By improving the stability between exploration and exploitation phases, enhancing solution efficiency, and accelerating convergence, ScsRUN outperforms other optimization methods in terms of efficiency and reliability.