Optimizing Electrical Energy Dispatch in Goma (DRC) Using Artificial Neural Networks
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Masters Thesis | Electrical Power Engineering | Democratic Republic of the Congo | Volume 14 Issue 1, January 2025 | Popularity: 6.7 / 10


     

Optimizing Electrical Energy Dispatch in Goma (DRC) Using Artificial Neural Networks

Kambale Pawase Gershome, Baraka Mushage Olivier, Twizere Bakunda J. Daudet, Tsochounie Jules Hubert


Abstract: This study addresses the growing electricity demand in Goma, DRC, amidst limited energy resources. By integrating Artificial Neural Networks (ANNs) with optimization techniques, the research proposes an interconnection network to enhance resource sharing and improve forecasting for electricity production and demand. The ANN model achieved 90% accuracy in energy distribution, reducing computation time and optimizing costs. Results underscore the critical role of resource management and policy reforms in ensuring sustainable energy solutions.


Keywords: Optimal dispatch, power flow optimization, Artificial Neuronal Networks, energy management, electricity distribution


Edition: Volume 14 Issue 1, January 2025


Pages: 967 - 977


DOI: https://www.doi.org/10.21275/SR25120191055



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Kambale Pawase Gershome, Baraka Mushage Olivier, Twizere Bakunda J. Daudet, Tsochounie Jules Hubert, "Optimizing Electrical Energy Dispatch in Goma (DRC) Using Artificial Neural Networks", International Journal of Science and Research (IJSR), Volume 14 Issue 1, January 2025, pp. 967-977, https://www.ijsr.net/getabstract.php?paperid=SR25120191055, DOI: https://www.doi.org/10.21275/SR25120191055