An Optimization Approach for Potential Power Generator Outputs Based on Parallelized Firefly Algorithm

The parallel processing plays an important role in efficient and effective computations of function optimization. This paper proposes a parallel optimization algorithm for the committed generating electric powers of thermal plants based on Firefly Algorithm (FA). An economic condition for the power systems can be determined through the optimization techniques for transmission loss, power balance and generation capacity. The aim of the proposed parallel algorithm with communication strategies is to correlate agents in subgroups and to share the computation load over several machines. The expense criteria for each generation unit and the coefficient matrix are formulated as the objective function, which is to be computed in our parallel optimization for electricity flow of the transmission losses in the power systems. Four selected functions and two cases of six units and fifteen units of thermal plants are tested in our experiments for optimization. Through a comparison between different methods in related works, our experimental results show that the proposed method results in the higher effect and accuracy.