International Journal of Advances in Applied Sciences
Vol 3, No 4: December 2014

Artificial Neural Network Based Economic Generation Scheduling in Nigeria Power Network

Omorogiuwa Eseosa (University Of Port Harcourt)
Onohaebi S.O (University of Benin)



Article Info

Publish Date
01 Dec 2014

Abstract

Economic generation scheduling determines the most efficient and economic means of dispatch of generated energy to meet the continuously varying load demand at the most appropriate minimum cost, while meeting all the units equality and inequality constraints in  power network. This is currently not applicable in Nigeria power network. The network under study consists of seventeen (17) generating stations (Existing Network, National Integrated Power Projects and the Independent Power Producers). This work investigates economic generation and scheduling in Nigeria 330KV integrated power network at minimum operating cost using the classical kirmayer’s method and Artificial Neural Network (ANN) for its optimization in Matlab environment. ANN is trained to adopt its pattern at different load demands and acquires the ability to give load demand as soon as the set target and goal tends to equality. Cost function for each generating unit as well as a model for economic generation scheduling was developed.

Copyrights © 2014






Journal Info

Abbrev

IJAAS

Publisher

Subject

Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

Description

International Journal of Advances in Applied Sciences (IJAAS) is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of applied and theoretical sciences. The journal is designed to serve researchers, developers, professionals, graduate students and ...