Backtracking search optimization applied to solve short-term electrical real power generation of hydrothermal plant

Abstract

This article aims to determine the feasible optimal solution for the short-term hydrothermal scheduling (STHS) problem using the efficient backtracking search optimization technique. The problem formulation for hydrothermal systems is highly complex owing to its nonlinear nature. Hydrothermal scheduling is considered with two decision variables simultaneously: thermal states and water discharge. These two variables are instrumental in determining the optimal hourly schedule of power generation in hydrothermal power plants. The optimum solution is obtained using the backtracking search algorithm (BSA) with two primary operations, namely, mutation and crossover. The BSA is an optimization technique free from high-sensitivity control parameters, because it has only one control parameter for finding the optimal solution. It also has powerful exploration and exploitation capabilities. The simulation results corroborate that BSA is highly efficient compared to existing optimization techniques (e.g. oppositional real coded chemical reaction-based optimization, differential evolution) in terms of overall efficiency and the quality of the solutions.