A Double Action Genetic Algorithm for Scheduling the Wind-Thermal Generators

摘要

Scheduling of wind-thermal electrical generators is a challenging constrained optimization problem, where the main goal is to find the optimal allocation of output power among various available generators to serve the system load. Over the last few decades, a large number of solution approaches, including evolutionary algorithms, have been developed to solve this problem. However, these approaches are usually ineffective and time consuming. In this paper, we apply two variants of genetic algorithm (GA) for solving the problem where the first variant is to optimize the allocation and the second one is to rank the generators for allocation. The proposed algorithm is applied to a recent wind-thermal benchmark that comprises five thermal and 160 wind farms. The model includes a stochastic nature of wind energy and gas emission effects of thermal plants. The simulation results show that the proposed method is superior to those results of different variants of GA and the state-of-the-art algorithms.