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All Journal International Journal of Renewable Energy Development International Journal of Renewable Energy Development
Seydou Ouedraogo
Laboratoire de Recherche en Sciences de l’Ingénieur (LARSI), Département de Génie Électrique, Institut Universitaire de Technologie, Université Nazi BONI, 01 BP 1091 Bobo-Dioulasso 01
Chemistry Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering

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Modelling the Optimal Electricity Mix for Togo by 2050 Using OSeMOSYS Esso-Wazam Honoré Tchandao; Akim Adekunlé Salami; Koffi Mawugno Kodjo; Amy Nabiliou; Seydou Ouedraogo
International Journal of Renewable Energy Development Vol 12, No 2 (2023): March 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.50104

Abstract

This work uses bottom-up modeling to explore the future evolution trajectories of the electricity mix in Togo by 2050. The objective is to investigate the evolution of the mix and the future investments needed to achieve the sustainable energy and climate change goals. Three scenarios were developed using OSeMOSYS. The reference scenario, named Business As Usual, closely reflects the evolution of the Togolese electricity sector under a business-as-usual assumption and planned capacity increases up to 2030. The second scenario, Net Zero by 2050, is based on the first scenario while ensuring that CO2 emissions cancel out in 2050 by following the Weibull law. The third scenario called Emission Penalty aims not only at the integration of renewable energies like the second one but also at the least cost electricity mix if emission penalties are applied. The results of the cost optimization indicate that photovoltaic and importation are the optimal choices ahead of gas and hydropower. The renewable energy aspect of the electricity mix is more highlighted in the last scenario. At the same time, the model shows that greater energy independence is achievable at the cost of a transitory increase in the cost of the electricity system. A tenfold investment effort is needed in 2030 to ensure either continuity of the status quo or a shift in strategy.
Modelling the Optimal Electricity Mix for Togo by 2050 Using OSeMOSYS Esso-Wazam Honoré Tchandao; Akim Adekunlé Salami; Koffi Mawugno Kodjo; Amy Nabiliou; Seydou Ouedraogo
International Journal of Renewable Energy Development Vol 12, No 2 (2023): March 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.50104

Abstract

This work uses bottom-up modeling to explore the future evolution trajectories of the electricity mix in Togo by 2050. The objective is to investigate the evolution of the mix and the future investments needed to achieve the sustainable energy and climate change goals. Three scenarios were developed using OSeMOSYS. The reference scenario, named Business As Usual, closely reflects the evolution of the Togolese electricity sector under a business-as-usual assumption and planned capacity increases up to 2030. The second scenario, Net Zero by 2050, is based on the first scenario while ensuring that CO2 emissions cancel out in 2050 by following the Weibull law. The third scenario called Emission Penalty aims not only at the integration of renewable energies like the second one but also at the least cost electricity mix if emission penalties are applied. The results of the cost optimization indicate that photovoltaic and importation are the optimal choices ahead of gas and hydropower. The renewable energy aspect of the electricity mix is more highlighted in the last scenario. At the same time, the model shows that greater energy independence is achievable at the cost of a transitory increase in the cost of the electricity system. A tenfold investment effort is needed in 2030 to ensure either continuity of the status quo or a shift in strategy.
Influence of the Random Data Sampling in Estimation of Wind Speed Resource: Case Study Adekunlé Akim Salami; Seydou Ouedraogo; Koffi Mawugno Kodjoa; Ayité Sénah Akoda Ajavona
International Journal of Renewable Energy Development Vol 11, No 1 (2022): February 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.38511

Abstract

In this study, statistical analysis is performed in order to characterize wind speeds distribution according to different samples randomly drawn from wind speed data collected. The purpose of this study is to assess how random sampling influences the estimation quality of the shape (k) and scale (c) parameters of a Weibull distribution function. Five stations were chosen in West Africa for the study, namely: Accra Kotoka, Cotonou Cadjehoun, Kano Mallam Aminu, Lomé Tokoin and Ouagadougou airport. We used the energy factor method (EPF) to compute shape and scale parameters. Statistical indicators used to assess estimation accuracy are the root mean square error (RMSE) and relative percentage error (RPE). Study results show that good accuracy in Weibull parameters and power density estimation is obtained with sampled wind speed data of 30% for Accra, 20% for Cotonou, 80% for Kano, 20% for Lomé, and 20% for Ouagadougou site. This study showed that for wind potential assessing at a site, wind speed data random sampling is sufficient to calculate wind power density. This is very useful in wind energy exploitation development.
Co-Authors Adekunlé Akim Salami Akim Adekunlé Salami Amy Nabiliou Ayité Sénah Akoda Ajavona Esso-Wazam Honoré Tchandao Koffi Mawugno Kodjo Koffi Mawugno Kodjoa