Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling

Muhammad Salman Fakhar,Sanjeevikumar Padmanaban,Muhammad Ahmad Iqbal,Akhtar Rasool,Syed Abdul Rahman Kashif,Sheroze Liaquat,Muhammad Anas Baig,Baseem Khan

doi:10.1109/access.2021.3083528

Abstract

Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-model, non-convex, and multi-dimensional optimization problem that has been worked upon for about 5 decades. Many research articles have been published in solving different test cases of STHTS problem, while establishing the superiority of one type of optimization algorithm over the type, in finding the near global best solution of these complex problems. This paper presents the implementation of an improved version of a variant of the Particle Swarm Optimization algorithm (PSO), known as Accelerated Particle Swarm Optimization (APSO) on three benchmark test cases of STHTS problems. The adaptive and variable nature of the local and global search coefficients for the proposed APSO significantly improve its performance in obtaining the optimal solution for the STHTS test cases. Two of these cases are non-cascaded cases of STHTS problem (NCSTHTS) and one case is cascaded case of STHTS problem (CSTHTS). The results are compared with the results of the previous implementations of the other algorithms as presented in the literature. Due to the stochastic nature of the meta-heuristic algorithms, the parametric and non-parametric statistical tests have been implemented to establish the superiority of results of one type of algorithm over the results of the other type of algorithms.

Highlights

Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-modal, non-convex and multi-dimensional optimization problem in which combined NsPthi,m + Phydj,m = PDemand + Plosses (2)i=1 j=1 economic dispatch of the hydel and thermal generating units is implemented using an optimization algorithm
Out of several cases of non-cascaded cases of STHTS problem (NCSTHTS) and case of STHTS problem (CSTHTS), this paper presents solution of two cases of NCSTHTS problem and one case of CSTHTS problem by implementing accelerated particle swarm optimization (APSO) algorithm and a new improvement in Accelerated Particle Swarm Optimization (APSO) algorithm
This article presents the results of the implementations of APSO and its proposed improved version on the three test cases of STHTS problems and their comparison with other algorithms implemented on the same problems

Summary

Introduction

STHTS is a highly non-linear, multi-modal, non-convex and multi-dimensional optimization problem in which combined Ns. Pthi,m + Phydj,m = PDemand + Plosses (2). I=1 j=1 economic dispatch of the hydel and thermal generating units is implemented using an optimization algorithm. Extracting where, from reference [1], this problem can be defined mathematically in generic form by equations (1) to (9). The associate editor coordinating the review of this manuscript and approving it for publication was Fabio Mottola. Phydj,m = f (Vhydj,m , Qhydj,m ) (3).

Methods

Results

Conclusion