Artificial Neural Network Based Economic Generation Scheduling in Nigeria Power Network

Omorogiuwa Eseosa, Onohaebi S.O


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.

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International Journal of Advances in Applied Sciences (IJAAS)
p-ISSN 2252-8814, e-ISSN 2722-2594
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