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

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.