Design of Fractional Swarm Intelligent Computing With Entropy Evolution for Optimal Power Flow Problems

Yasir Muhammad,Yigang He,Farman Ullah,Naveed Ishtiaq Chaudhary,Muhammad Asif Zahoor Raja,Rahimdad Khan

doi:10.1109/access.2020.3002714

Abstract

Optimal reactive power dispatch (ORPD) problems in power system have been solved by using several variants of traditional nature inspired particle swam optimization (PSO) with aim to achieve a promising solution for a given objective such as line loss, voltage deviation and overall cost minimization. Several schemes have been designed to improve the performance of the optimization technique in tunning the operational variables and analyzed by evaluating the final results. In this article, a different method is designed to solve ORPD problems, by introducing Shannon entropy based diversity in the fractional order PSO dynamics, i.e., FOPSO-EE. The results show that synergy of both, the Shannon entropy and the fractional calculus can be used as the useful tools for enhancing the optimization strength of algorithm while solving the ORPD problems in standard IEEE 30 and 57 bus power systems. The performance of the design FOPSO-EE is further validated through results of statistical interpretations in terms of histogram analysis, box plot illustration, quantile-quantile probability plot and empirical probability distribution function.

Highlights

LITERATURE REVIEW In the literature, several arithmetic, stochastic, evolutionary, social-based and meta-heuristic optimization techniques are developed since last few decades including the differential evolution [2], genetic algorithm [3]–[8], particle swarm optimization (PSO) etc
A novel optimization approach FOPSO-EE is presented for solving the Optimal reactive power dispatch (ORPD) problems in the power system by exploitation of entropy diversity in fractional swarm intelligence
In the designed method FOPSO-EE, two important mathematical tools, namely the Shanon entropy and fractional calculus are integrated with traditional PSO algorithm

Summary

Introduction

A. MOTIVATION AND INCITEMENT Optimal reactive power dispatch (ORPD) aims to improve the performance of a power system by reducing the voltage deviation, transmission line losses, operational cost, improving system security, stability index, and line capacity. MOTIVATION AND INCITEMENT Optimal reactive power dispatch (ORPD) aims to improve the performance of a power system by reducing the voltage deviation, transmission line losses, operational cost, improving system security, stability index, and line capacity Most of these objectives are achieve by tunning the operational variables of the network such as the transformers tap positions, generator output voltages, capacitor banks and solid state flexible AC transmission systems (FACTS) devices [1]. B. LITERATURE REVIEW In the literature, several arithmetic, stochastic, evolutionary, social-based and meta-heuristic optimization techniques are developed since last few decades including the differential evolution [2], genetic algorithm [3]–[8], particle swarm optimization (PSO) etc. Since the development of the canonical PSO, a considerable number of its variants based on different numerical tools have been proposed in order to enhance the algorithm performance, and significantly applied in a plethora of applications [9]–[14]

Methods

Results

Conclusion