Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Scenarios Simulation and Analysis on Electric Power Planning Based on Multi-scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035

Version 1 : Received: 8 October 2021 / Approved: 12 October 2021 / Online: 12 October 2021 (12:53:37 CEST)

A peer-reviewed article of this Preprint also exists.

Kanté, M.; Li, Y.; Deng, S. Scenarios Analysis on Electric Power Planning Based on Multi-Scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035. Energies 2021, 14, 8515. Kanté, M.; Li, Y.; Deng, S. Scenarios Analysis on Electric Power Planning Based on Multi-Scale Forecast: A Case Study of Taoussa, Mali from 2020 to 2035. Energies 2021, 14, 8515.

Abstract

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.

Keywords

Electricity peak load; Taoussa’s energy sources; Long-term electricity demand planning; Scenarios simulation

Subject

Engineering, Energy and Fuel Technology

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