**6. Conclusions**

In this paper, a Modified Adaptive Selection Cuckoo Search Algorithm (MASCSA) is implemented for determining the optimal operating parameters of a hydrothermal system and a wind-hydro-thermal system, to minimize the total electricity generation cost from all available thermal power plants. The fixed-head short-term model of hydropower plants is taken into consideration. All hydraulic constraints, such as initial and final reservoir volumes, the upper limit and lower limit of reservoir volume, and water balance of reservoir, are seriously considered. The proposed MASCSA competes with the conventional Cuckoo Search Algorithm (CSA) and Snap-Drift Cuckoo Search Algorithm (SDCSA). Two test systems are employed to run the proposed methods and those CSA methods. The comparison results indicate that the proposed method is more powerful than CSA and SDCSA in searching for optimal solutions, with much faster convergence. The proposed method can deal with all constraints more successfully and reach much better results. The success rate of the proposed method is 100% for all test cases, while the success rates of the other CSA methods are 0% or much lower than 100%. Furthermore, the proposed method can reach a speed that is twice as fast as CSA and SDCSA. The improvement of the proposed method is significant compared to CSA methods, even when it is over 2%. Consequently, the proposed method is effective for complicated problems with a set of complicated constraints.

**Author Contributions:** T.T.N. and L.H.P. have simulated results and written the paper. L.C.K. has collected obtained results and analyzed results. F.M. was responsible for supervising, writing, and editing. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflicts of interest regarding the publication of this paper.
