Formulating short-term electricity demand forecasting for Lesotho
| dc.contributor.author | Lefela, Lereko | |
| dc.contributor.supervisor | Thamae, Leboli Zak | |
| dc.date.accessioned | 2026-06-16T11:41:09Z | |
| dc.date.available | 2026-06-16T11:41:09Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Electricity demand forecasting is an important process in the planning and operation of the electricity industry. Providing uninterrupted energy to consumers requires electricity demand to be predicted accurately. This study utilizes ABB Nostradamus short-term demand forecasting software, which accepts historical demand data, days of the week, time of the year and Lesotho public holidays for electricity demand forecasting. It produced day-ahead, week-ahead and hourahead electricity demand forecasting results with 3.06%, 4.06% and 5.09% accuracy. These MAPE results are close to or within the acceptable 5% accuracy for short-term demand forecasting, and provide crucial confidence levels for LEC to engage in power pool trading in the SAPP market for optimal power procurement. LEC utilizes bilateral agreements with LHDA, Eskom and EDM to supply the electricity demand. During the high demand season, bilateral imports from Eskom and EDM costs LEC around 3.27 Million US Dollars (M49 Million) which is twice the money incurred (1.60 Million US Dollars (M24 Million)) during the low demand season. Compared to the average SAPP DAM, IDM and FPM-W prices, Eskom’s 20 USc/kWh peak cost is higher than SAPP’s 12 USc/kWh DAM and IDM, and 13 USc/kWh FPM-W peak charges. Again, EDM’s 4 USc/kWh off-peak cost is higher than SAPP’s 3 USc/ kWh DAM, IDM and FPM-W off-peak charges. The study therefore recommends bilateral contracts use to meet intermediate demand of around 103 MW. For demand above 103 MW, utilizing SAPP market can assist to reduce bulk purchases costs. | |
| dc.description.sponsorship | National Manpower Development Secretariat | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14155/2348 | |
| dc.language.iso | en | |
| dc.publisher | National University of Lesotho | |
| dc.title | Formulating short-term electricity demand forecasting for Lesotho |