E. E. Hassan
Universiti Teknikal Malaysia Melaka

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Sustainable Environmental Economic Dispatch Optimization with Hybrid Metaheuristic Modification M. R. M. Ridzuan; E. E. Hassan; A. R. Abdullah; A. F. A. Kadir
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp161-168

Abstract

Today’s Economic Dispatch (ED) solutions are featured with environmental obligations. Hence, the significant objective functions contribute to cost minimization, lower emission and less total system losses. As an alternative, New Meta Heuristic Evolutionary Programming (NMEP) technique was proposed to optimize the individual ED problem categorized as Single Objective Environmental Economic Dispatch (SOEELD), developed from an integration of original Meta Heuristic Evolutionary Programming (Meta-EP) with Artificial Immune System (AIS) with new arrangement in the mutation and cloning processes. The comparative analysis was conducted between the original Meta-EP and classical method of Hadi Saadat to verify the performance of NMEP method. Each particular objective function identified the best possible outcomes through the NMEP method. The simulations were conducted using MATLAB programming which tested both standard IEEE 26 and 57 bus systems.
Multi objective Adaptive Tumbling Bacterial Foraging in VAR Solutions for Sustainable Power System Operation E. E. Hassan; T. K. A. Rahman; Z. Zakaria; N. Bahaman; M. H. Jifri
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp129-136

Abstract

The application of the developed optimization technique Multi Objective Adaptive Tumbling Bacterial Foraging (MOATBFO) was introduced to solve the multi objective Reactive Power Planning (RPP) problems. The objective of conventional RPP problems is to minimize the total power losses in a system. However, in this study, the aspect of security was also taken into consideration in terms of voltage stability condition in solving RPP problems. Hence, the RPP problem is now termed as security constrained RPP (SCRPP) and generalized into a multi objective function via weighted sum method that labeled as MOSCRPP. The best minimum voltage solution for the network is aimed in ensuring the sustainable power system operation.  In order to verify the performance of the proposed technique were used for MOSCRPP in the IEEE 57 bus system thus the comprehensive analyses were also conducted with other multi objective Meta heuristic Evolutionary Programming (Meta-EP). From the results it shows that the multi objective ATBFO optimization is able to give better overall improvement in the objective functions for SCRPP problems.