**1. Introduction**

Over the last few years, we are in a shortage of energy and facing the environmental pollution problem. So, now a day's wise utilization of energy and the operating cost minimization are major issues in the energy field. This signifies constraints of hydrothermal systems must be modified and more robust technique is required to provide more accurate scheduling results. The main aim of optimal HTS of an electrical system is to optimize hydrothermal generations so that the load demand is fulfilled in a scheduled time with accommodating several system constraints of the hydrothermal system. It is very complicated than that of the thermal system due to nonlinearity.

The Stochastic methods like Genetic Algorithm (GA) [1], Quick Evolutionary Programming (QEP) [2], Improved Particle Swarm Optimization (IPSO) [3], Teaching Learning Based Optimization (TLBO) TLBO [4], Symbiotic Organisms Search (SOS) [5], Intensified water cycle approach (IWCA) [6] have used for solving STH problems. GWO [7] is a simple, fast and effective global optimization method. GWO algorithm has been applied for the solution of non-convex and dynamic economic load dispatch problem (ELDP) of electric power system [8]. GWO has successfully solved various ELD problems [9]. Many researchers have demonstrated that an opposite candidate gives a more optimal solution than the candidate. Opposition Based Gray Wolf Optimizer (OGWO) has been implemented in solving ELD problem [10] for thermal power generators which increases the success rate and the convergence speed of GWO.

This study applies Quasi Opposition based GWO (QOGWO) for solving HTS problem of a hydrothermal system which prime objective is to allocate the hydro generation between the multi-reservoir cascaded units with PDZ and thermal units with VPL effect. The objective is to cut the total fuel cost of the thermal system with accommodating several limitations of the hydrothermal system which makes it a nonconvex problem. To establish that the intended approach is better, a rigorous exercise of the QOGWO for a hydrothermal system, with the gradual increase of complexity and dimension, is considered in this study. In contrast to recent techniques, the outcomes of the QOGWO technique exhibits superiority for operating cost as well as the convergence characteristics to achieve the optimal result in all the cases tested here.
