Table 1.
Input data and modeling results
| Name | Wind | PV | RES | BESS |
|---|---|---|---|---|
| Input data | ||||
| Specific CAPEX,$/kW | 1350.0 | 700.0 | 925.0 | 80.0 |
| Specific CAPEX, $/kWh | – | – | – | 385.0 |
| Specific fixed costs, $/kW | 4.0 | 10.9 | 5.0 | 2.0 |
| Specific variable costs and fuel, $/kWh | – | – | 35.5 | – |
| CAPEX, million € | 1.7 | 1.1 | 1.2 | 1.0 |
| Capacity factor, % | 36.0 | 14.7 | 15.0 | 25.0 |
| Production (storage) energy, GWh/year | 3.2 | 1.7 | 1.3 | 0.2 |
| LCOE (LCOS), €/MWh | 81.2 | 108.1 | 189.8 | 377.2 |
| Modeling results (before optimization) | ||||
| Installed capacity, MW | 3.6 | 14.0 | 3.7 | 16.0 |
| Nominal capacity, MWh | – | – | – | 40.0 |
| CAPEX, million € | 6.2 | 12.1 | 4.4 | 15.4 |
| Capacity factor, % | 33.1 | 16.2 | 15.8 | 31.6 |
| Production (storage) energy, GWh/year | 10.5 | 15.3 | 5.1 | 3.7 |
| Volume of curtailment at the solar, GWh/year | – | – | – | 0.4 |
| LCOES, €/MWh | 147.9 | |||
| Modeling results (after optimization) | ||||
| Installed capacity, MW | 3.6 | 14.0 | 3.7 | 3.9 |
| Nominal capacity, MWh | – | – | – | 9.7 |
| CAPEX, million € | 6.2 | 12.1 | 4.4 | 3.8 |
| Capacity factor, % | 33.1 | 16.2 | 15.8 | 48.5 |
| Production (storage) energy, GWh/year | 10.5 | 15.3 | 5.1 | 1.4 |
| Volume of curtailment at the solar, GWh/year | – | – | – | 2.7 |
| LCOES, €/MWh | 136.7 | |||
Figure 1.
The daily amount of excess electrical energy of the solar power plant, the amount of electrical energy transfer using the BESS before optimization and after optimization for March and April of the year studied