Open AccessArtificial Neural Network Based Economic Generation Scheduling in Nigeria Power Network
Author(s) -
Omorogiuwa Eseosa,
Onohaebi S.O
Publication year - 2014
Publication title -
international journal of advances in applied sciences
Language(s) - English
Resource type - Journals
eISSN - 2722-2594
pISSN - 2252-8814
DOI - 10.11591/ijaas.v3.i4.pp206-214
Subject(s) - artificial neural network , scheduling (production processes) , economic dispatch , power network , matlab , electricity generation , mathematical optimization , computer science , power (physics) , electric power system , operations research , reliability engineering , engineering , artificial intelligence , mathematics , physics , quantum mechanics , operating system
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.