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<span>Reservoirs are often built in cascade on the same river system, introducing inexorable constraints. It is therefore strategically important to scheme out an efficient commitment of thermal generation units along with the scheduling of hydro generation units for better operational efficiency, considering practical system conditions. This paper develops a comprehensive, unit-wise hydraulic model with reservoir and river system constraints, as well as gas constraints, with head effects, to commit thermal generation units and schedule hydro ones in the short-term. A mixed integer linear programming (MILP) methodology, using the branch and bound &amp; cut (BB&amp;C) algorithm, is employed to solve the resultant problem. Due to the detailed modelling of individual hydro units and cascaded dependent reservoirs, the problem size is substantially swollen. Multithread computing is invoked to accelerate the solution process. Simulation results, conducted on various test systems, reiterate that the developed MILP-based hydrothermal scheduling approach outperforms other techniques in terms of cost efficiency.</span>

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In many utilities, it is essential to devise an optimum commitment solution of generating units for better operational efficiency, under empirical conditions. Among the methods reported in the technical literatures, Dynamic Programming (DP), Lagrangian Relaxation (LR), and Mixed-Integer Programming (MIP) are the most industry proven algorithms in the line of business. This paper improves the available solution offered in LR technique, which was mainly suffered from high fluctuation of duality gap between the primal and dual solutions. As a remedy, a Cuckoo Search Algorithm (CSA) is proposed to optimize the gap progress throughout the LR solution process. Simulation results reiterate that the developed LR-UC integrating CSA enhances the solution quality.