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