Oppositional real coded chemical reaction based optimization to solve short-term hydrothermal scheduling problems

This paper presents an Oppositional Real Coded Chemical Reaction based (ORCCRO) algorithm to solve the short-term hydrothermal scheduling (STHS) problem. Being complex, the hydrothermal system relates with every problem variables in a non-linear way. The objective of the STHS is to determine the optimal hourly schedule of power generation for different hydrothermal power system for certain intervals of time to minimize the total cost of power generations. Chemical Reaction Optimization (CRO) imitates the interactions of molecules in terms of chemical reaction to reach a lower energy stable state. A real coded version of CRO, known as Real-Coded Chemical Reaction Optimization (RCCRO) is considered here. Oppositional based RCCRO (ORCCRO) added here to improve the quality of solutions with minimum time. The proposed opposition-based RCCRO (ORCCRO) employs opposition-based learning i.e., generation of quasi-opposite numbers for population initialization instead of pseudo random numbers to improve the convergence rate of the RCCRO. To check the effectiveness of the ORCCRO, 3 test systems are considered, mathematically remodeled to make it apt for solving short-term hydrothermal scheduling problem. Results prove that the proposed approach is better than all existing optimization techniques in terms quality of solution, computational efficiency and robustness to solve STHS problems.