Fractional order swarming intelligence for multi-objective load dispatch with photovoltaic integration

Abstract

In this research work, the concept of fractional calculus is integrated inside the mathematical model of the canonical particle swarm optimization (i.e., FPSO) to enhance its optimization characteristics, namely its convergence rate, for solving the combined economic emission and load dispatch problems in the power systems. The proposed FPSO is exploited by tuning the output of the thermal and photovoltaic generation to reduce the overall operational cost, emissions, and line losses while meeting the consumer power demand in the standard Institute of Electrical and Electronic Engineering (IEEE) 30 bus network. The outcomes of the FPSO are compared with their recent state-of-the-art counterparts to endorse its efficacy for solving economic load dispatch problem, while the reliability and consistency of the FPSO are additionally confirmed through statistical illustrations that include the minimum fitness gauges in each independent execution, boxplot illustrations, histograms, plots for normal distribution, boxplots for time complexity, plots for Weibull distribution, plots for the cumulative distribution function, and quantile–quantile plots as a gauge of the diversity and central tendency.