Figure 1.
Satellite location for Mimosa Mine (Source: Google maps).
Figure 1.
Satellite location for Mimosa Mine (Source: Google maps).
Figure 2.
Monthly GHI and DNI for the Mimosa mine.
Figure 2.
Monthly GHI and DNI for the Mimosa mine.
Figure 3.
Typical Winter Day Profile.
Figure 3.
Typical Winter Day Profile.
Figure 4.
Typical Summer Day Profile.
Figure 4.
Typical Summer Day Profile.
Figure 5.
The 2015 monthly energy consumption and maximum demand for the Mimosa mine.
Figure 5.
The 2015 monthly energy consumption and maximum demand for the Mimosa mine.
Figure 6.
Time of Use monthly consumption of the Mimosa mine in 2015.
Figure 6.
Time of Use monthly consumption of the Mimosa mine in 2015.
Figure 7.
Dispatch control for CSP and TES in SAM.
Figure 7.
Dispatch control for CSP and TES in SAM.
Figure 8.
Variation of the annual energy and the LCOE with a tilt angle.
Figure 8.
Variation of the annual energy and the LCOE with a tilt angle.
Figure 9.
Variation of the annual energy and the LCOE with an azimuth angle.
Figure 9.
Variation of the annual energy and the LCOE with an azimuth angle.
Figure 10.
Variation of the annual energy and the LCOE with the Ground Cover Ratio.
Figure 10.
Variation of the annual energy and the LCOE with the Ground Cover Ratio.
Figure 11.
Monthly variation of load vs. generated PV energy.
Figure 11.
Monthly variation of load vs. generated PV energy.
Figure 12.
Two typical consecutive days with good PV production.
Figure 12.
Two typical consecutive days with good PV production.
Figure 13.
Monthly electricity bill with the PV system vs. without.
Figure 13.
Monthly electricity bill with the PV system vs. without.
Figure 14.
Three-dimensional graph showing the battery and PV capacity optimisation.
Figure 14.
Three-dimensional graph showing the battery and PV capacity optimisation.
Figure 15.
Energy distribution of the PV and battery system.
Figure 15.
Energy distribution of the PV and battery system.
Figure 16.
Two typical consecutive days with good PV production.
Figure 16.
Two typical consecutive days with good PV production.
Figure 17.
Two typical consecutive days with bad PV production.
Figure 17.
Two typical consecutive days with bad PV production.
Figure 18.
Monthly electric bill with the PV and battery system vs. without.
Figure 18.
Monthly electric bill with the PV and battery system vs. without.
Figure 19.
Design point optimisation.
Figure 19.
Design point optimisation.
Figure 20.
Solar multiple optimisation.
Figure 20.
Solar multiple optimisation.
Figure 21.
Optimisation of the number of field subsections.
Figure 21.
Optimisation of the number of field subsections.
Figure 22.
Monthly generated CSP vs. the monthly demand.
Figure 22.
Monthly generated CSP vs. the monthly demand.
Figure 23.
Two typical consecutive days with good CSP production.
Figure 23.
Two typical consecutive days with good CSP production.
Figure 24.
Two typical consecutive days with bad CSP production.
Figure 24.
Two typical consecutive days with bad CSP production.
Figure 25.
Monthly electricity bill with the CSP system vs. without.
Figure 25.
Monthly electricity bill with the CSP system vs. without.
Figure 26.
Three-dimensional graph showing the optimisation of the storage hours and the solar multiple.
Figure 26.
Three-dimensional graph showing the optimisation of the storage hours and the solar multiple.
Figure 27.
Monthly generated energy from CSP and TES vs. monthly load.
Figure 27.
Monthly generated energy from CSP and TES vs. monthly load.
Figure 28.
Two typical consecutive days with good CSP production.
Figure 28.
Two typical consecutive days with good CSP production.
Figure 29.
Two typical consecutive days with bad CSP production.
Figure 29.
Two typical consecutive days with bad CSP production.
Figure 30.
Monthly electric bill with the CSP and TES system vs. without.
Figure 30.
Monthly electric bill with the CSP and TES system vs. without.
Table 1.
Selected techno-economic analysis of renewable energy existing in the literature.
Table 1.
Selected techno-economic analysis of renewable energy existing in the literature.
Name of Article | Aim of Article | Year | Reference |
---|
Techno-Economic analysis of Renewable Energy System: Case study in Zimbabwe | To carry out a techno-economic comparison of standalone wind and solar photovoltaic and the hybrid of PV and Wind | 2020 | [9] |
Making the sun shine at night: comparing the cost of dispatchable CSP with PV + storage | Comparing PV + BESS, PV + TES and CSP with TES | 2021 | [10] |
Comparing of Dispatchable Renewable electricity options | To obtain a better understanding of various technology combinations for dispatchable renewable electricity to contribute to system reliability | 2018 | [11] |
Comparing the net cost of CSP + TES to PV deployed with battery storage | To determine if the advantages of CSP + thermal energy surpasses the benefits of PV deployed with battery storage | 2016 | [12] |
Table 2.
Mining companies in sub-Sahara Africa that have integrated renewable energy.
Table 2.
Mining companies in sub-Sahara Africa that have integrated renewable energy.
Mining Company | Mineral | Country | Renewable Technology | Reference |
---|
Croniment Mining DG | Platinum | South Africa | Solar PV—1 MW | [21] |
SNIM | Iron ore | Mauritania | Wind—5 MW | [16] |
Gold fields | Gold | South Africa | Solar PV—40 MW | [16] |
IAMGOLD Essakane | Gold | Burkina Faso | Solar PV—15 MW | [16] |
Table 3.
Methodology.
Stage | System/Description | Aim | Steps |
---|
1 | Demand profile | To develop the typical hourly load profile from the given monthly data | Understand the given load data and the billing structure |
Analyse the typical working pattern and use it to develop an hourly profile |
2 | PV | To analyse the viability of integrating Solar PV at Mimosa mine | Design the capacity and optimise technical parameters (tilt angle, orientation, and interrow distance) |
Analyse the technical and economic metrics of the modelled results (annual energy produced, LCOE, Savings, net present value) |
3 | PV and Battery | To analyse the viability of integrating Solar PV and Battery at the Mimosa mine | Design and determine the optimal size for PV and Battery for a given dispatch |
Analyse the technical and economic metrics of the modelled results (annual energy produced, LCOE, savings, net present value) |
4 | CSP | To analyse the viability of integrating CSP at the Mimosa mine | Design the capacity and optimise the technical parameters (solar multiple, design point DNI) |
Analyse the technical and economic metrics of the modelled results (annual energy produced, LCOE, savings, net present value) |
5 | CSP and Thermal Energy Storage | To analyse the viability of integrating CSP + TES at the Mimosa mine | Design and determine the optimal size for CSP and TES for a given dispatch |
Analyse the technical and economic metrics of the modelled results (annual energy produced, LCOE, savings, net present value |
6 | Repeat stage 2 to 5 but considering the energy export | To analyse the techno-economic performance of the systems when exports are allowed | Design and determine the optimal size for PV, CSP and TES/Battery |
Analyse the technical and economic metrics of the modelled results (annual energy produced, LCOE, savings, net present value |
Table 4.
Key performance indicators used for evaluation.
Table 4.
Key performance indicators used for evaluation.
KPI | Calculation/Comment |
---|
Base case |
Renewable Energy Contribution | This is shown as a percentage of the energy offset by the renewable energy system. Calculated as Equation (1) |
Levelised Cost of Electricity (LCOE)—applies to export case | This metric will allow comparisons of energy systems being considered based on technical performance, capital cost and operations and maintenance costs. The formula used is given in Appendix A |
Net Present Value (NPV)—applies to export case | This will be used to analyse the profitability of the system The formula used is given in Appendix A |
Export case |
Energy exported | This shows the percentage of energy exported from the system calculated as: Equation (2) |
Energy used locally | This shows the percentage of the energy used to meet local generation from the system calculated as: Equation (3) |
Renewable Energy contribution | This shows the percentage of the energy offset by the renewable energy system calculated as: Equation (4) |
Grid contribution (applies to base case as well) | This shows the percentage of energy used to meet the mine demand from the grid calculated as: Equation (5) |
Table 5.
Time of use periods and corresponding tariff.
Table 5.
Time of use periods and corresponding tariff.
| Hours | Legend | |
---|
Day of Week | 0–6 | 7–10 | 11 | 12–16 | 17–19 | 20 | 21 | 22–23 | Category | Colour | Tariff/USD per kWH |
---|
Sunday/Holiday | | | | | | | | | Peak | | 0.13 |
Weekday | | | | | | | | | Standard | | 0.07 |
Saturday | | | | | | | | | Off-peak | | 0.04 |
Table 6.
Technical parameters for the PV plant.
Table 6.
Technical parameters for the PV plant.
Parameter | Unit | Value (and Comment) |
---|
Module type | - | Polycrystalline |
Module DC capacity | W | 345 |
Module Efficiency | % | 17.8 |
Inverter | - | String inverter |
Inverter Capacity | kW | 40 |
Tilt angle | Degrees | 0–60 (optimisation range) |
Azimuth | Degrees | 0–270 (optimisation range) |
Module configuration | - | Landscape |
Far shading | - | Assumed no far shadings |
DC/AC ratio | - | 1.05 |
Ground cover ratio | - | 0.05–0.95 (optimisation range to determine interrow distance) |
Soiling loss | % | 5 [30] |
DC losses | % | 4.4 (including module mismatch) [30] |
AC cabling losses | % | 2 [30] |
Degradation | %/year | 0.5 [30] |
Table 7.
Commercial parameters for PV module. Adapted from [
36].
Table 7.
Commercial parameters for PV module. Adapted from [
36].
Parameter | Unit | Value |
---|
Direct Capital Cost | | |
Module cost | USD/Wdc | 0.30 |
Inverter cost | USD/Wac | 0.05 |
Balance of System | USD/Wdc | 0.17 |
Installation cost | USD/Wdc | 0.10 |
Installer margin and overhead | USD/Wdc | 0.05 |
Contingency | % | 3 |
Indirect Capital Cost | | |
Sales tax | % | 5 |
Land purchase | USD/acre | 11,000 |
Operations and maintenance cost | USD/kW-year | 9 |
Analysis Parameters | | |
Project life | Years | 25 |
Inflation | % | 2.5 |
Discount rate | % | 6.4 |
Interest rate | % | 5 |
Table 8.
Battery technical properties. Adapted from [
30].
Table 8.
Battery technical properties. Adapted from [
30].
Description | Unit | Value |
---|
Battery type | - | Lithium ion: Nickel Manganese Cobalt Oxide (NMC/Graphite) |
Maximum charge power | MWac | 30 |
Maximum discharge power | MWac | 30 |
Life cycle at 80% DOD | cycles | 2500 |
Minimum State of Charge | % | 15 |
Maximum State of Charge | % | 95 |
Battery replacement threshold capacity | % | 50 |
DC—AC efficiency | % | 96 |
AC—DC efficiency | % | 96 |
Table 9.
Economic parameters for battery storage. Adapted from [
36].
Table 9.
Economic parameters for battery storage. Adapted from [
36].
Description | Unit | Value |
---|
Battery Storage System | | |
Cost of storage | USD/kWh | 209 |
Conversion system | USD/kW | 70 |
Balance of System | USD/kW | 80 |
Operations and Maintenance (O/M) | | |
Fixed O/M | USD/kW-year | 6.9 |
Variable O/M | USD/MWh | 2.1 |
Battery Replacement Cost | USD/kWh | 2/3 of Cost of Storage |
Analysis Parameters | | |
Project life | Years | 25 |
Inflation | % | 2.5 |
Discount rate | % | 6.4 |
Interest rate | % | 5 |
Table 10.
Technical parameters for CSP. Data from [
30].
Table 10.
Technical parameters for CSP. Data from [
30].
Subsection | Parameter | Description |
---|
Solar field | Solar multiple (Option 1) | Parametric analysis to determine—1 to 4 with 0.25 steps |
Number of field subsections | Parametric analysis to determine—1 to 12 |
HTF pump efficiency | 0.85 |
Irradiation at design point | Parametric analysis to determine—700 to 1000 W/m2 with steps of 20 |
Design loop inlet temperature/C | 295 |
Design loop outlet temperature/C | 550 |
Water usage per wash (L/m2) | 0.7 |
Number of SCA per loop | 14 |
Collectors (SCAs) | Configuration type | Solargenix SGX-1 |
Receivers (HCEs) | Configuration type | Schott PTR80 |
Power cycle | Design gross output | 32 MW |
Estimated gross to net conversion | 0.9 |
Rated cycle conversion efficiency (Rankine) | 0.4 |
Condenser type | Air cooled |
Ambient temperature at design point/C | 32 |
Table 11.
Economic parameters for CSP. Data from [
39].
Table 11.
Economic parameters for CSP. Data from [
39].
Description | Unit | Value |
---|
Solar field | USD/m2 | 150 |
Site improvements | USD/m2 | 25 |
Heat Transfer Fluid | USD/m2 | 60 |
Power plant | USD/kW | 910 |
Balance of Plant | USD/kW | 32 |
Contingency | % | 3 |
Land cost | USD/acre | 11,000 |
Sales tax | % | 5 |
Operations and Maintenance | | |
Fixed cost | USD/kW-year | 66 |
Variable cost by generation | USD/MWh | 4 |
Financial parameters | | |
Project life | Years | 25 |
Inflation rate | % | 2.5 |
Discount rate | % | 6.4 |
Interest rate | % | 5 |
Table 12.
TES technical and economic parameters. Data from [
30].
Table 12.
TES technical and economic parameters. Data from [
30].
Parameter | Units | Value |
---|
Storage fluid | - | Hitec Solar Salt |
Storage hours | h | Parametric analysis to determine—1 to 14 with steps of 1 |
Solar Multiple | - | Parametric analysis to determine—1 to 4 with 0.25 steps |
Tank orientation | - | Parallel |
Tank height | M | 15 |
Parallel tank pairs | - | 2 |
Cold tank heater temperature set point | °C | 238 |
Hot tank heater temperature set point | °C | 525 |
Economic parameter | | |
Storage cost | USD/kWht | 62 |
Table 13.
Methodology to simulate system with exports.
Table 13.
Methodology to simulate system with exports.
System | Description |
---|
PV | |
PV + Battery | The system will inherit the generic and optimised parameters for the base case scenario as described in Section 3.4The battery being simulated is behind the meter hence the exports from the hybrid system will be from excess PV generation. Behind the meter, batteries in SAM are used to meet the load and cannot export energy to the grid The desired battery capacity (storage capacity) and the corresponding plant size will be determined by parametric analysis. The battery storage size ranges from 2 h to 14 h in steps of 1 h and the PV plant size ranges from 55.5 MWdc to 185 MWdc in steps of 18.5 MW
|
CSP | |
CSP + TES | The system will inherit the generic and optimised parameters for the base case scenario as described in Section 3.6The desired gross power output, solar multiple and thermal storage hours will be determined by parametric analysis. The gross power output will range from 30 MW to 75 MW with steps of 5 MW, the solar multiple will range from 1 to 4 with steps of 0.25, and the thermal storage hours will range from 1 h to 14 h in steps of 1 h
|
Table 14.
Comparison between PVSyst and SAM.
Table 14.
Comparison between PVSyst and SAM.
Parameter | SAM | PVSyst | % Difference with Reference to PVSyst |
---|
Produced Energy (unlimited User) | 61.5 GWh | 60.5 GWh | +1.65% |
Specific production | 1662 kWh/kW/year | 1632 kWh/kW/year | +1.84% |
Performance ratio | 77% | 74.5% | +2.5% |
Table 15.
Economic performance indicators for the PV system.
Table 15.
Economic performance indicators for the PV system.
Parameter | Unit | Value |
---|
Levelised Cost of Electricity | USD/kWh | 0.048 |
Annual Electric Bill without PV system | USD | 13.69 Million |
Annual Electric Bill with PV system | USD | 8.021 Million |
Net annual savings | USD | 5.672 Million |
Net Present Value | USD | 41.39 Million |
Simple pay back | Years | 5.1 |
Table 16.
Economic performance indicators for the PV and battery system.
Table 16.
Economic performance indicators for the PV and battery system.
Parameter | Unit | Value |
---|
Levelised Cost of Electricity | USD/kWh | 0.106 |
Annual Electric Bill without PV system | USD | 13.7 Million |
Annual Electric Bill with PV system | USD | 3.0 Million |
Net annual savings | USD | 10.7 Million |
Net Present Value | USD | 19.3 Million |
Simple pay back | Years | 10.8 |
Table 17.
Economic performance indicators for the CSP System.
Table 17.
Economic performance indicators for the CSP System.
Parameter | Unit | Value |
---|
Levelised Cost of Electricity | USD/kWh | 0.16 |
Annual Electric Bill without CSP system | USD | 13.69 Million |
Annual Electric Bill with CSP system | USD | 9.63 Million |
Net annual savings | USD | 4.06 Million |
Net Present Value | USD | −13.6 Million |
Simple pay back | Years | Not available |
Table 18.
Economic performance indicators for the CSP and TES system.
Table 18.
Economic performance indicators for the CSP and TES system.
Parameter | Unit | Value |
---|
Levelised Cost of Electricity | USD/kWh | 0.15 |
Annual Electric Bill without CSP system | USD | 13.69 Million |
Annual Electric Bill with CSP system | USD | 6.54 Million |
Net annual savings | USD | 7.15 Million |
Net Present Value | USD | −17.3 Million |
Simple pay back | Years | 20.9 |
Table 19.
Summary of key results.
Table 19.
Summary of key results.
Parameter | No Export (Base Case) | with Export |
---|
PV | PV + Battery | CSP | CSP + TES | PV | PV + Battery | CSP | CSP + TES |
---|
Installed capacity | 37 MWdc | 74 MW + 210 MWh (7 h) | 32 MW | 32 MW + 7 h | 60 MWdc | 74 MW + 210 MWh (7 h) | 50 MW | 40 MW + 7 h |
Annual Energy generated (first year)/GWh | 55.1 | 104 | 39.3 | 68.4 | 99.7 | 121 | 94.7 | 127 |
Renewable Energy contribution (to load)/% | 33.3 | 63 | 23.7 | 41.3 | 39 | 63 | 28 | 41 |
LCOE (US cents/kWh) | 4.76 | 10.67 | 16.32 | 15.44 | 4.34 | 9.4 | 12.13 | 10.45 |
NPV/USD Million | 41.4 | 19.3 | −13.9 | −17.3 | 47.7 | 31.4 | 3.96 | 28.6 |
Energy Exported by System/% | - | - | - | - | 35 | 14 | 51 | 46 |
Grid contribution (to load)/% | 72.7 | 37 | 76.3 | 58.7 | 61 | 37 | 72 | 59 |
Installation Cost/USD | 0.76/Wdc | 1.5/Wdc | 2.75/Wac | 5.6/Wac | 0.76/Wdc | 1.5/Wdc | 3.35/Wac | 5.5/Wac |
Land used/acres | 114 | 228.2 | 178 | 355 | 185 | 228.2 | 383 | 437 |
Capacity Factor/% | 19 | 18.6 | 20.6 | 40.5 | 19 | 18.6 | 24 | 40.4 |
Energy yield (kWh/kW) | 1662 | 1629 | 1802 | 3552 | 1662 | 1629 | 2105 | 3540 |
Simple pay back/years | 5.1 | 10.8 | - | 20.9 | 6.3 | 9.7 | 15.7 | 12.9 |
Annual Electric bill savings/USD Million | 5.67 | 10.7 | 4.1 | 7.15 | 7.52 | 12 | 9.68 | 13.2 |
Table 20.
Comparison of the LCOE (base case values) with the literature.
Table 20.
Comparison of the LCOE (base case values) with the literature.
Renewable Energy System | Base Case Values (USD cents/kWh) | IRENA Values (USD cents/kWh) [40] | Lazard Values (USD cents/kWh) [42] |
---|
PV | 4.76 | 6.8 | 3.1–4.2 |
PV + Battery | 10.67 | - | - |
CSP | 16.32 | 18.2 | - |
CSP + TES | 15.44 | - | 12.6–15.6 |