Publications (6)
ARTICLE
Predicting power and solar energy using neural networks and PCA with meteorological parameters from Diass and Taïba Ndiaye
Sambalaye Diop, Papa Silly Traore, Mamadou Lamine Ndiaye, Issa Zerbo, Vincent Sambou
The excessive reliance on conventional fossil fuel-based resources poses a significant threat to our environment. To mitigate this impact, it has become increasingly crucial to increase the integration of intermittent and non-polluting energy sources into our electrical grids. However, while this higher penetration rate brings benefits such as(...)
Renewable energies, Prediction, Artificial neural networks, Vulnerability
ARTICLE
Optimization of a hybrid photovoltaic/grid power source system supplemented by a storage unit: case study
Sidiki Zongo, Madi Ouedraogo, Ali Diané, Fabrice Bado, Zacharie Sié Kam, Moussa Sougoti, Alfa Omar Dissa, Antoine Béré
Hybrid power systems have significantly increased in the last decade to supply energy in both industrial and commercial sectors. Because of the abundance of solar radiation, Burkina Faso has the potential to develop solar and or hybrid energy systems to meet its energy demand. In the present case study, solar radiation data have been analysed(...)
Hybrid system, photovoltaic, storage unit, optimization, reliability business company
ARTICLE
Using Artificial Intelligence Models to Predict the Wind Power to be fed into the Grid
Sambalaye Diop , Papa Silly Traore, Mamadou Lamine Ndiaye, Issa Zerbo
The Taïba Ndiaye wind farm, connected to the SENELEC grid, plays a key role in offsetting shortfalls in electricity consumption, with an installed capacity of 158.7 MW. Moreover, as an intermittent power station, its production is highly dependent on the environmental conditions in the region. Bad weather can disrupt the electricity network, r(...)
Taïba Ndiaye, Wind power, SENELEC grid, forecast, machine learning, artificial intelligence models
ARTICLE
System Faults Diagnosis in a Photovoltaic Generator Using Artificial Neural Network Approach
O. W. Compaore, G. Hoblos and Z. Koalaga, "
Thanks to acquisition systems, fault diagnosis methods in Photovoltaic Generators (PVG) find themselves confronted with large quantities of voluminous data that are sometimes unused. The international scientific community, through the application of artificial intelligence (AI) methods, considered it as a promising solution. They allow large d(...)
Diagnosis , Photovoltaïc Generator , System Fault , Artificial Neuronal Network , Classification
ARTICLE
Assessing the Efficiency of the Zagtouli Solar Plant: A Large-Scale Grid Connected PV System in Burkina Faso
Abdoulaye Kabore, Samuel Ouoba, Kayaba Haro, Tongonmanegde Leonard Ouedraogo, Boubou Bagre, Bowendkuni Armand Korsaga, Antoine Bere
This paper presents an evaluation and analysis of the energy perfonnance of a 33.7 MWp solar photovoltaic plant. Monitoring data for 36 months (January 2019-December 2021) have been used to evaluate the perfonnance of the power plant according to the IEC 61724 standard. Nonnalized parameters that are (i) perfonnance ratio, (ii) reference yield(...)
Perfonnance analysis, Grid-connected, No1malized yields, Sudano-sahelian zone
ARTICLE
Performance Assessment of a Box Type Solar Cooker Using Jatropha Oil as a Heat Storage Material
Jacques Nébié, Sidiki Zongo, Guy C. Tubreoumya, Augustin S. Zongo, Ilyassé Konkobo,Boubou Bagré, Ali Diané, Tizane Daho, Serges W. Igo, Belkacem Zeghmati, Antoine Béré
Solar cookers are a good option in developing countries with high solar po-tential for environmentally friendly cooking and reduced pressure on forests.However, they are still affected by the intermittency of the sun. In order toovercome this problem, in this work, a box type solar cooker integrated Ja-tropha oil as a heat storage material is(...)
Solar Cooker, Kapok Wool, Performance, Heat Storage, Jatropha oil