AHMED GUEYE - Academia.edu (original) (raw)

Papers by AHMED GUEYE

Research paper thumbnail of On the Characterization of Cloud Occurrence and Its Impact on Solar Radiation in Mbour, Senegal

Journal of atmospheric and solar-terrestrial physics, Jun 1, 2024

Research paper thumbnail of Enhancing PM2.5 Predictions in Dakar Through Automated Data Integration into a Data Assimilation Model

Aerosol science and engineering, May 15, 2024

Research paper thumbnail of Seasonal Performance of Solar Power Plants in the Sahel Region: A Study in Senegal, West Africa

Smart grid and renewable energy, 2024

The main objective of this study is to evaluate the seasonal performance of 20 MW solar power pla... more The main objective of this study is to evaluate the seasonal performance of 20 MW solar power plants in Senegal. The analysis revealed notable seasonal variations in the performance of all stations. The most significant yields are recorded in spring, autumn and winter, with values ranging from 5 to 7.51 kWh/kWp/day for the reference yield and 4.02 to 7.58 kWh/kWp/day for the final yield. These fluctuations are associated with intense solar activity during the dry season and clear skies, indicating peak production. Conversely, minimum values are recorded during the rainy season from June to September, with a final yield of 3.86 kWh/kW/day due to dust, clouds and high temperatures. The performance ratio analysis shows seasonal dynamics throughout the year with rates ranging from 77.40% to 95.79%, reinforcing reliability and optimal utilization of installed capacity. The results of the capacity factor vary significantly, with March, April, May, and sometimes October standing out as periods of optimal performance, with 16% for Kahone, 16% for Bokhol, 18% for Malicounda and 23% for Sakal. Total losses from solar power plants show similar seasonal trends standing out for high loss levels from June to July, reaching up to 3.35 kWh/kWp/day in June. However, using solar trackers at Sakal has increased production by up to 25%, demonstrating the operational stability of this innovative technology compared with the plants fixed panel. Finally, comparing these results with international studies confirms the outstanding efficiency of Senegalese solar power plants, other installations around the world.

Research paper thumbnail of PM2.5 Hotspot Identification in Dakar area: An Innovative IoT and Mapping-Based Approach for Effective Air Quality Management

Research paper thumbnail of Analysis and simulation of six solar power plants seasonal production in Senegal, West Africa

Modeling Earth Systems and Environment, Dec 20, 2023

Research paper thumbnail of Comparative Study of Available Solar Potential for Six Stations of Sahel

Smart Grid and Renewable Energy, Dec 31, 2022

Research paper thumbnail of Enhancing daily PM2.5 air quality forecasts in Dakar, Senegal, through the integration of data from the automatic measuring station into a server using data assimilation

Research Square (Research Square), Feb 22, 2024

The objective of this work is to predict daily PM2.5 air quality in Dakar, Senegal using data fro... more The objective of this work is to predict daily PM2.5 air quality in Dakar, Senegal using data from an automated measurement station integrated into a server using a data assimilation model. Initially, a 3-year data set was used to identify and validate an appropriate ARIMA data assimilation model. The data was split into an 80% training set and a 20% test set. The Augmented Dickey-Fuller (ADF) test was used to check the normality of the data series. Subsequently, we used the AutoArima method to determine the optimal model to represent the time series. Preliminary results show that a model with order (2,1,1) accurately represents the series. Additional analysis using model fit tests showed that the (3, 0, 1) model was most effective in representing and predicting the data. The statistical validation performance of this model demonstrates its capability to forecast PM2.5 concentrations for up to 72 hours (3 days), achieving correlation coefficients exceeding 80%. However, after three days, the predictions returned to background levels. In the final stage of the study, data from automatic stations were integrated into a server hosting the assimilation model to improve daily PM2.5 forecasts for Dakar. An interactive platform was developed to visualize measurements and forecasts over two days. The results show that by integrating the data with the assimilation model, predictions are significantly improved.

Research paper thumbnail of Temporal dynamics of energy production at the Taïba Ndiaye wind farm in Senegal

Discover Energy

The study presented in this article focuses on the temporal dynamics of wind energy production at... more The study presented in this article focuses on the temporal dynamics of wind energy production at the Taïba Ndiaye wind farm in Senegal, with a capacity of 158.7 MW. The monthly and seasonal distribution of production shows a strong trend, with maximums recorded between December and May (winter and spring) at around 1800 MWh, and minimums between July and November (summer and autumn) with production below 500 MWh. The diurnal cycle representation exhibits variation with a marked cycle, particularly between November and April. Night-time production is higher than daytime production by more than 43%. The effects of 100-m wind on the farm production are also analysed and show a positive correlation between wind speed and production throughout the year. Production peaks observed in winter and spring are caused by strong winds (approximately 8.5 m/s), while the lowest levels recorded during the summer season are due to weather conditions characterized by weak winds (less than 4 m/s). Sim...

Research paper thumbnail of Gestion des ordures ménagères dans les villes secondaires du Sénégal : vers des politiques municipales incluant les quartiers périphériques

Research paper thumbnail of On the Characterization of Cloud Occurrence and Its Impact on Solar Radiation in Mbour, Senegal

Journal of atmospheric and solar-terrestrial physics, Jun 1, 2024

Research paper thumbnail of Enhancing PM2.5 Predictions in Dakar Through Automated Data Integration into a Data Assimilation Model

Aerosol science and engineering, May 15, 2024

Research paper thumbnail of Seasonal Performance of Solar Power Plants in the Sahel Region: A Study in Senegal, West Africa

Smart grid and renewable energy, 2024

The main objective of this study is to evaluate the seasonal performance of 20 MW solar power pla... more The main objective of this study is to evaluate the seasonal performance of 20 MW solar power plants in Senegal. The analysis revealed notable seasonal variations in the performance of all stations. The most significant yields are recorded in spring, autumn and winter, with values ranging from 5 to 7.51 kWh/kWp/day for the reference yield and 4.02 to 7.58 kWh/kWp/day for the final yield. These fluctuations are associated with intense solar activity during the dry season and clear skies, indicating peak production. Conversely, minimum values are recorded during the rainy season from June to September, with a final yield of 3.86 kWh/kW/day due to dust, clouds and high temperatures. The performance ratio analysis shows seasonal dynamics throughout the year with rates ranging from 77.40% to 95.79%, reinforcing reliability and optimal utilization of installed capacity. The results of the capacity factor vary significantly, with March, April, May, and sometimes October standing out as periods of optimal performance, with 16% for Kahone, 16% for Bokhol, 18% for Malicounda and 23% for Sakal. Total losses from solar power plants show similar seasonal trends standing out for high loss levels from June to July, reaching up to 3.35 kWh/kWp/day in June. However, using solar trackers at Sakal has increased production by up to 25%, demonstrating the operational stability of this innovative technology compared with the plants fixed panel. Finally, comparing these results with international studies confirms the outstanding efficiency of Senegalese solar power plants, other installations around the world.

Research paper thumbnail of PM2.5 Hotspot Identification in Dakar area: An Innovative IoT and Mapping-Based Approach for Effective Air Quality Management

Research paper thumbnail of Analysis and simulation of six solar power plants seasonal production in Senegal, West Africa

Modeling Earth Systems and Environment, Dec 20, 2023

Research paper thumbnail of Comparative Study of Available Solar Potential for Six Stations of Sahel

Smart Grid and Renewable Energy, Dec 31, 2022

Research paper thumbnail of Enhancing daily PM2.5 air quality forecasts in Dakar, Senegal, through the integration of data from the automatic measuring station into a server using data assimilation

Research Square (Research Square), Feb 22, 2024

The objective of this work is to predict daily PM2.5 air quality in Dakar, Senegal using data fro... more The objective of this work is to predict daily PM2.5 air quality in Dakar, Senegal using data from an automated measurement station integrated into a server using a data assimilation model. Initially, a 3-year data set was used to identify and validate an appropriate ARIMA data assimilation model. The data was split into an 80% training set and a 20% test set. The Augmented Dickey-Fuller (ADF) test was used to check the normality of the data series. Subsequently, we used the AutoArima method to determine the optimal model to represent the time series. Preliminary results show that a model with order (2,1,1) accurately represents the series. Additional analysis using model fit tests showed that the (3, 0, 1) model was most effective in representing and predicting the data. The statistical validation performance of this model demonstrates its capability to forecast PM2.5 concentrations for up to 72 hours (3 days), achieving correlation coefficients exceeding 80%. However, after three days, the predictions returned to background levels. In the final stage of the study, data from automatic stations were integrated into a server hosting the assimilation model to improve daily PM2.5 forecasts for Dakar. An interactive platform was developed to visualize measurements and forecasts over two days. The results show that by integrating the data with the assimilation model, predictions are significantly improved.

Research paper thumbnail of Temporal dynamics of energy production at the Taïba Ndiaye wind farm in Senegal

Discover Energy

The study presented in this article focuses on the temporal dynamics of wind energy production at... more The study presented in this article focuses on the temporal dynamics of wind energy production at the Taïba Ndiaye wind farm in Senegal, with a capacity of 158.7 MW. The monthly and seasonal distribution of production shows a strong trend, with maximums recorded between December and May (winter and spring) at around 1800 MWh, and minimums between July and November (summer and autumn) with production below 500 MWh. The diurnal cycle representation exhibits variation with a marked cycle, particularly between November and April. Night-time production is higher than daytime production by more than 43%. The effects of 100-m wind on the farm production are also analysed and show a positive correlation between wind speed and production throughout the year. Production peaks observed in winter and spring are caused by strong winds (approximately 8.5 m/s), while the lowest levels recorded during the summer season are due to weather conditions characterized by weak winds (less than 4 m/s). Sim...

Research paper thumbnail of Gestion des ordures ménagères dans les villes secondaires du Sénégal : vers des politiques municipales incluant les quartiers périphériques