Moussa Kanté

Dr. Moussa Kanté

Key Laboratory of Efficient Utilization of Low and Medium Grade Energy, Tianjin University, MOE, Tianjin 300350, China
orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 December 2021 in Energies
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Journal Article
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MKMoussa Kanté
Moussa Kanté
YLYang Li
Yang Li
SDShuai Deng
Shuai Deng
The increase in electricity demand is caused by population density, gross domestic product growth and technological conditions. A long-term forecast study on the electricity demand could be a promising alternative to the investment planning of power systems and distribution. In this study, the main aim is to forecast and understand the long-term electricity demand of the Taoussa area for the sustainable development of the regions of northern Mali, by using the Model for Analysis of Energy Demand (MAED) from the International Atomic Energy Agency. To fill such a knowledge gap, the long-term evolution of electricity demand is calculated separately for four consumption sectors: industry, transportation, service and household from 2020 to 2035. The demand for each end-use category of electricity is driven by one or several socioeconomic and technological parameters development of the country, which are given as part of the reference scenario (RS) and two alternative scenarios (Low and High). These scenarios were developed based on four groups of coherent hypotheses concerning demographic evolution, economic development, lifestyle change and technological change. The results showed that the annual growth rate of electricity demand in Taoussa area in all scenarios is expected to increase by only 8.13% (LS), 10.31% (RS) and 12.56% (HS). According to the seasonal variations of electricity demand, dry season electricity demand was higher than the demand in cool season during the study period. Such a conclusion demonstrates that the proposed long-term method and related results could provide powerful sustainable solutions to the electricity development challenges of Africa.

10 December 2022 in Energy Reports
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Journal Article
Open access
MKMoussa Kanté
Moussa Kanté
SDShuai Deng
Shuai Deng
YLYang Li
Yang Li
MKMansa Kanté
Mansa Kanté
SCSouleymane Coulibaly
Souleymane Coulibaly
Optimization for a long-term electricity supply strategy with renewable energy is essential for electricity security and financial and environmental sustainability. The main goal of this study is to find the equilibrium between electricity demand and sustainable optimal electricity supply mix scenarios of the Taoussa area at the least cost for the development of north in Mali, by using the Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE) from the International Atomic Energy Agency (IAEA) for the period 2020-2035. This model is applied to obtain the least-cost electricity and supply of electricity under electricity demand forecasted by reference scenario (RS) and two alternative scenarios (Low scenario, LS; High scenario, HS), technical information on power generation per technology and regional information. The result obtained from the optimization of the power management strategy shows that the final electricity generation is 1.02 times greater than the electricity demand and the annual increase of power generation is equivalent to 8.13%, 10.32% and 12.56%, under different scenarios. The maximum power from PV and hydropower by scenarios are from April to May in the hot season. Thus, the proposed MESSAGE model is useful in improving the economical-environmental optimization of the operation of large-scale hybrid renewable electricity supply.

12 October 2021 in Preprints.org
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Open access
MKMoussa Kanté
Moussa Kanté
YLYang Li
Yang Li
SDShuai Deng
Shuai Deng
A long-term forecast study on the electricity demand of Taoussa of Mali is conducted in this paper, with various scenarios of socioeconomic and technological conditions. The analysis tool, which is applied in scenarios simulation, is the Model for Analysis of Energy Demand from the International Atomic Energy Agency. The analysis results are annual electricity demand and peak load forecast for the electrification from the period 2020 to 2035. During the planning period, the analysis results show that the electricity demand will increase to 49.40 MW (332.57 GWh) for the low scenario (LS), 66.46 MW (472.61 GWh) for the reference scenario (RS), and 89.47 MW (635 GWh) for the high scenario (HS). In addition, the total electricity demand increased at an average rate of 8.13% in the LS, 10.31% in the RS and 12.56% in the HS in all sectors. The electricity peak demand is expected to grow at 7.92%, 10.53% and 12.91% corresponding to the three scenarios; in this case, the system peak demand in 2035 will increase to 64.88 MW for the LS, 92.2 MW for the RS and 126.22 MW, the days of peak load are between 17th -23rd in May. The Industry sector will be the biggest electricity consumer of Taoussa area.

2 July 2026 in International Journal of Hydrogen Energy
Verified
Journal Article
Closed access
MKMoussa Kanté
Moussa Kanté
SDShuai Deng
Shuai Deng
YLYang Li
Yang Li
Usman Haladu GarbaUsman Haladu Garba
Usman Haladu Garba
QZQi Zhang
Qi Zhang
YTYoussouf Traoré
Youssouf Traoré