Exploring the economic prospects of wind energy in Zambia

Figures & data

Table 1. Adapted from World Bank. 2019. Wind resource mapping in Zambia: 24-month site resource report. Washington, DC, USA: World Bank. Renewable energy wind mapping for Zambia (Odoi-Yorke et al. 2022.).

Site	Distance from theCapital City (km)	Brief Site Description
Choma	292.10	The site is located in an area of rural agricultural land approximately 20 km west of the town of Choma in the Southern Province.
Mwinilunga	913.70	The site is located on a slightly elevated and lightly forested plateau approximately 60 km southeast of the town of Mwinilunga in the North-West Province.
Lusaka	70.00	The site is located in an area of flat, rural agricultural land approximately 70 km northwest of the city of Lusaka in the Central Province.
Mpika	646.00	The site is located in an area of low-lying bush and rural agricultural land approximately 25 km northwest of the town of Mpika in the Northern Province.
Chanka	913.10	The site is located in an area of rural agricultural land approximately 80 km northeast of the town of Isoka in the Northern Province. The site is located between 35 and 50 km from the Malawi and Tanzanian borders, respectively, on the crest of a plateau.
Petauke	403.00	The site is located in an area of rolling hills approximately 15 km northwest of the town of Petauke in the Eastern Province.
Mansa	765.00	The site is located on a small southwest–northeast ridge approximately 35 km north of the town of Mansa in the Luapula Province.
Malawi	477.86	The site is located in an area of flat, rural agricultural land approximately 80 km east of the town of Chipata in the Eastern Province.

Figure 1. Shows wind regime measurements conducted at eight meteorological (met) mast sites across the country.

Wind regime measurements were conducted at eight meteorological mast sites across Zambia.

Table 2. Proposed wind turbine model parameters (DNV Report 2023).

Turbine	Rated Power [MW]	Hub Height [m]	Peak Power Coefficient [Cp]	Valid PC Density [kg/m^3]	Valid PC Turbulence Intensity Range [%]
Generic 4 MW	4.0	130	0.44	1.225	6–12

Table 3. Adapted from World Bank. 2019. Wind resource mapping in Zambia: 24 month site resource report. Washington, DC, USA: World Bank. Renewable energy wind mapping for Zambia.

Site	Average Turbine Wind Speed at 130 m (m/s)
Choma	7.1
Mwinilunga	7.2
Lusaka	8.0
Mpika	7.0
Chanka	7.2
Petauke	6.9
Mansa	7.2
Malawi	7.1

Table 4. Adapted from World Bank. 2019. Wind resource mapping in Zambia: 24 month site resource report. Washington, DC: World Bank. Renewable energy wind mapping for Zambia.

Site	Choma	Mwinilunga	Lusaka	Mpika	Chanka	Petauke	Mansa	Malawi
Wind Farm Rated Power [MW]	100	100	100	100	100	100	100	100
Gross Energy Output [GWh/annum]	356.6	374.8	435.9	364.2	387.5	337.3	355.6	345.3
Net Energy Output [GWh/annum]	303.0	323.3	386.0	320.3	345.6	291.5	314.7	303.7
Net Capacity Factor [%]	34.6	36.9	44.0	36.5	39.4	33.2	35.9	34.6

Figure 2. Methodology flow chart used to evaluate the economic feasibility of the wind farms.

An economic evaluation methodology was developed to evaluate the economic feasibility using the present value of costs (PVC), simple payback period (SPP), internal rate of return (IRR), and levelized cost of electricity production (LCOE). Figure 2 shows the flowchart used in this study. The calculation of the economic result is based on the assumption of the price per kWh produced using the most likely price. This assumption is a critical factor for estimating the economic viability of a project. The developed model was analysed using MATLAB 2022. The electricity cost and sensitivity analysis results compared the current electricity cost for Zambia at 0.07 USD/kWh with the model results.

Table 5. Summary of financial assumptions.

Parameter	Value
Corporate tax (%)	5
Depreciation period (Years)	20
Depreciation method	linear approximation
Depreciation period (%)	5
Operations period (Years)	20
Real interest rate (%)	10.1
Electricity tariff (USD/KWh)	0.07 (Renewable Energy Strategy and Action Plan, Energy Regulation Board 2023)

Table 6. Adapted from Techno-economic assessment of wind energy potential at three locations in South Korea using long-term measured wind data (Langer et al. 2022).

Monopole-Type Foundation
Parameter	Value
Height (m)	130 (DNV Report 2023)
Steel cost $\left(\mathrm{USD}/\mathrm{kg}\right)$	0.64
Steel density (kg/m^3)	7870
Monopole diameter $\left(\mathrm{m}\right)$	5.5695
Monopole thickness $\left(\mathrm{m}\right)$	0.075

Table 7. Techno-economic parameters for the eight sites using electricity tariff of 0.07 USD/KWh.

Site	AEP (GWh)	CF (%)	NPV (USD)	IRR(%)	LCOE (USD/kWh)	SPP (Years)
Choma	303.0	34.6	−104,619,341	4.87	0.233	−9
Mwinilunga	323.3	36.9	−105,555,910	15.4	0.235	−9
Lusaka	386.0	44.0	−49,052,832	82.1	0.185	−19
Mpika	320.3	36.5	−101,505,602	16.1	0.184	−9
Chanka	345.6	39.4	−92,088,088	35.3	0.206	−10
Petauke	291.5	33.2	−113,363,194	−6.4	0.204	−8
Mansa	314.7	35.9	−107,314,348	9.7	0.226	−9
Malawi	303.7	34.6	−107,718,668	3.7	0.233	−9

Figure 3. Wind turbine economics at 0.07 USD/kWh electricity tariff for Choma site.

The results of the model showed negative NPV values for the 20 years. Towards the end of the turbine lifetime, the values approach a positive NPV, which can be explained by the negative payback period. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 4. Average electricity tariff (0.07 USD/kWh) and (0.617 USD/kWh) sensitivity analysis for the Choma site.

shows the results of the sensitivity analysis for the Choma plant. The highest value of LCOE was 0.617 USD/kWh, and the lowest was 0.232 USD/kWh.

Figure 5. Wind turbine economics at 0.07 USD/kWh electricity tariff for Mwinilunga site.

shows the techno-economic parameters at a 130 m hub height for the Mwinilunga site using Zambia’s average electricity tariff of 0.07 USD/kWh. The results of the model showed negative NPV values for the 20 years. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 6. Average electricity tariff (0.07 USD/kWh) and (0.624 USD/kWh) sensitivity analysis for Mwinilunga.

shows the results of the sensitivity analysis for the Mwinilunga plant. The highest value of LCOE was 0.624 USD/kWh, and the lowest was 0.235 USD/kWh.

Figure 7. Wind turbine economics at 0.07 USD/kWh electricity tariff for Lusaka site.

shows the techno-economic parameters at a 130 m hub height for the Lusaka site using Zambia’s average electricity tariff of 0.07 USD/kWh.

Figure 8. Average electricity tariff (0.07 USD/kWh) and (0.482 USD/kWh) sensitivity analysis for Lusaka.

shows the sensitivity analysis results for the Lusaka plant. The highest value of LCOE was 0.482 USD/kWh, while the lowest was 0.182 USD/kWh.

Figure 9. Wind turbine economics at 0.07 USD/kWh electricity tariff for Mpika site.

displays the techno-economic parameters at a 130 m hub height for the Mpika site using Zambia’s average electricity tariff of 0.07 USD/kWh. The model re-sults showed negative NPV values for the 20 years. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 10. Average electricity tariff (0.07 USD/kWh) and (0.487 USD/kWh) sensitivity analysis for Mpika.

shows the sensitivity analysis results for the Mpika plant. The highest value of LCOE is USD 0.487 USD/kWh, and the lowest is USD 0.487 USD/kWh.

Figure 11. Wind turbine economics at 0.07 USD/kWh electricity tariff for Chanka site.

shows the techno-economic parameters at a 130 m hub height for the Chanka site using Zambia’s average electricity tariff of 0.07 USD/kWh. The results of the model showed negative NPV values for the 20 years. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 12. Average electricity tariff (0.07 USD/kWh) and (0.547 USD/kWh) sensitivity analysis for Chanka.

shows the sensitivity analysis results for the chanka plant. The highest LCOE value was 0.547 USD/kWh, whereas the lowest was 0.206 USD/kWh.

Figure 13. Wind turbine economics at 0.07 USD/kWh electricity tariff for Petauke site.

displays the techno-economic parameters at a 130 m hub height for the Petauke site using Zambia’s average electricity tariff of USD 0.07/kWh. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 14. Average electricity tariff (0.07 USD/kWh) and (0.542 USD/kWh) sensitivity analysis for Petauke.

shows the sensitivity analysis results for the Petauke plant. The highest LCOE value was 0.542 USD/kWh, whereas the lowest was 0.204 USD/kWh.

Figure 15. Wind turbine economics at 0.07 USD/kWh electricity tariff for Mansa site.

displays the techno-economic parameters at a 130 m hub height for the Mansa site using Zambia’s average electricity tariff of 0.07 USD/kWh. The results of the model showed negative NPV values for the 20 years. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 16. Average electricity tariff (0.07 USD/kWh) and (0.599 USD/kWh) sensitivity analysis for Mansa.

shows the sensitivity analysis results for the Mansa plant. The highest and lowest values of LCOE were 0.599 USD/kWh and 0.226 USD/kWh.

Figure 17. Wind turbine economics at 0.07 USD/kWh electricity tariff for Malawi site.

displays the techno-economic parameters at a 130 m hub height for the Malawi site using Zambia’s average electricity tariff of 0.07 USD/kWh. The results of the model showed negative NPV values for the 20 years. The LCOE was at a minimum towards the end of the turbine lifetime.

Figure 18. Average electricity tariff (0.07 USD/kWh) and (0.617 USD/kWh) sensitivity analysis for Malawi.

shows the sensitivity analysis results for the Malawi plant. The highest value of LCOE was 0.617 USD/kWh, and the lowest was 0.233 USD/kWh.

Table 8. Techno-economic parameters using the average electricity tariff of 0.182 USD/kWh.

Site	Installation Cost (USD)	Wind Speed (m/s)	AEP (GWh)	CF (%)	NPV (USD)	IRR(%)	LCOE (USD/kWh)	SPP (Years)
Choma	143,007,883	7.1	303.0	34.6	182,139,859	4.87	0.233	5.1
Mwinilunga	144,539,720	7.2	323.3	36.9	200,415,210	15.4	0.235	4.6
Lusaka	142,241,965	8.0	386.0	44.0	316,257,568	82.1	0.185	2.9
Mpika	143,850,393	7.0	320.3	36.5	201,626,318	16.1	0.184	4.6
Chanka	144,506,895	7.2	345.6	39.4	234,987,752	35.3	0.206	3.9
Petauke	143,237,659	6.9	291.5	33.2	162,512,406	(6.40)	0.204	5.7
Mansa	144,145,819	7.2	314.7	35.9	190,517,732	9.7	0.226	4.9
Malawi	143,423,668	7.1	303.7	34.6	179,703,012	3.7	0.233	5.1

Figure 19. Parameter estimations of the sites: (a) EYA and wind speed; (b) EYA and CF; (c) SPP and IRR; (d) IRR and PBP.

illustrates parameter estimations of the sites. Initially, a site-specific analysis of wind characteristics was conducted. Subsequently, the selection of wind turbines was examined by considering the mechanical configuration suitable for the site.

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Data availability statement

The data that support the findings of this study are available from the corresponding author, S.M, upon reasonable request.