IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 8, No 3: September 2019

Multi-verse optimization based evolutionary programming technique for power scheduling in loss minimization scheme

Muhamad Hazim Lokman (Universiti Teknologi MARA (UiTM))
Ismail Musirin (Universiti Teknologi MARA (UiTM))
Saiful Izwan Suliman (Universiti Teknologi MARA (UiTM))
Hadi Suyono (Universitas Brawijaya (UB))
Rini Nur Hasanah (Universitas Brawijaya (UB))
Sharifah Azma Syed Mustafa (Universiti Teknologi MARA (UiTM))
Mohamed Zellagui (Université du Québec)



Article Info

Publish Date
01 Sep 2019

Abstract

The growth of computational intelligence technology has witnessed its application in numerous fields. Power system study is not left behind as far as computational intelligence trend is concerned. In power system community, optimization process is one of the crucial efforts for most remedial action to maintain the power system security. Basically, power scheduling refers to prior to fact action (such as scheduling generators to generate certain powers for next week). Power scheduling process is one of the most important routines in power systems. Scheduling of generators in a power transmission system is an important scheme; especially its offline studies to identify the security status of the system. This determines the cost effectiveness in power system planning. This paper investigates the performance of multi-verse based evolutionary programming (lowest EP) technique in the application of power system scheduling to ensure loss is gained by the system. Losses in the system can be controlled through this implementation which can be realized through the validation on a chosen reliability test system as the main model. Validation on IEEE 30-Bus Reliability Test System resulted that both techniques are reliable and robust in addressing this issue.

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Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...