A comprehensive opposition Multi-Verse Optimizer ensemble coordination constraint handling technique for hybrid hydro-thermal-wind problem.

• An improved Multi-Verse Optimizer named COMVO is proposed. • The modified normalized inflation rate is adjusted to increase the exploration ability of the universe individuals. • The personal best-known universe is introduced to provide the desired search direction. • The comprehensive opposition learning is selected to enhance the exploration accuracy. • COMVO combines a new constraint-handling technique to solve the hydro-thermal-wind hybrid systems. In this paper, a Comprehensive Opposition Multi-Verse Optimizer (COMVO) is proposed to find the optimal solution to the scheduling problem of hybrid hydro-thermal-wind systems. In COMVO, three improvement mechanisms are introduced to enhance the search performance of the original MVO. The proposed method is analyzed and statistically tested against existing state-of-the-art methods in 23 classic benchmark problems and CEC2009 test suite, which demonstrate the superiority of the proposed method. Meanwhile, a constraint-handling technique is developed to solve the complex coupling constraints in the HTW problem and is finally evaluated on a 4 hydro-3 thermal-2 wind system. The results of the comparative analyses show that the proposed method is able to achieve lower costs and fewer emissions than the existing popular methods. In addition, the proposed method reduces emissions by 54%, 81%, 3%, 44%, 17% and 5% in the mean value metrics compared to DA, FFA, GWO, HS, MFO and MVO at 2% wind penetration rate, which fully demonstrates the practicability of the proposed methodology and constraint-handling technique. [ABSTRACT FROM AUTHOR]