4.2 Key results of the use case studies
4.2.5 How sensitive is the design to changes of commodity prices
cheaper Lithium-ion batteries yield?
For further elaborating the sensitivity of the design of the energy system, parameters were systematically varied. Isolated changes of the natural gas price, the electricity price, the CO2 emission price and the interest rate were analyzed for the CPT airport. Figure 4.17 shows the resulting optimal capacities (discrete samples indicated by vertical lines).
With increasing natural gas price, internal combustion engine CHPs became economically unattractive (Figure 4.17 (a)). Instead, heating was supplied by gas boilers (GB) and heat pumps (both CHC and rHP). Eventually, also gas boilers were replaced by electric boilers. The capacities of the compression chiller and thermal energy storages were fairly constant. The plot in Figure 4.17 (b) is almost a mirror image of Figure 4.17 (a).
However, at mean annual electricity prices greater than 5.17 ct/kWh (peak prices of 8.15 ct/kWh), PV panels were economically feasible and should be installed. Increasing CO2
emission prices had the same effects as increasing natural gas prices (Figure 4.17 (c)).
Finally, Figure 4.17 (d) points out that heat pumps (both CHC and rHP) were partly replaced by less capital intense heating technologies (i.e., the gas boiler, GB) with increasing interest rates. Furthermore, ice storages (ITES) tended to have lower capital costs than chilled water storages (CWS) and therefore replaced them at higher interest rates (compare also Figure B.8 in the appendix). For similar reasons, in some cases in Figure 4.17 (a) – (c), ITES in combination with ammonia-water absorption chillers (ACi) were installed instead of CWS. For example, in Figure 4.17 (b), waste heat from the internal combustion engine could be utilized with ACi and ITES.
Figure 4.17: Cape Town airport energy system: Sensitivity analysis of the (a) Gas price (Ref = 3.48 ct/kWh), (b) Electricity price (Ref = 4.13 ct/kWh), (c) CO2 emission price (Ref = 2 $/t) and (d) Interest rate (Ref = 7%).21
For evaluating how disruptive technologies such as stationary lithium-ion batteries could change the design of the energy system, a sensitivity study of the lithium-ion batteries specific capital costs was performed. Sauer (2016) forecasted the total hardware costs of stationary lithium-ion batteries from 450 – 520 €/k h in 201 to 300 – 3 0 €/k h in 2050. Being even more optimistic, this study evaluated specific capital costs from 500 $/kWh down to 100 $/kWh (which is the price only for the cell material according to Sauer (2016)). CPT, MEX and SYD, locations with high TES capacities before, HNL, where a very small (80 kWh) lead-acid battery was installed before and
21 The electricity price is the mean annual electricity price. Note the time-of-use (TOU) tariff in CPT (see Table D.2).
Ref Ref
Ref Ref
108 4.2 Key results of the use case studies
PHX, a location with small storage capacities before, serve as reference locations for this study.
Figure 4.18: Lithium-ion battery capacity as percentage of all storages for different specific capital costs.22
Figure 4.18 shows the resulting optimal specific lithium-ion battery capacities (percentage of the overall installed storage capacity) as function of the specific capital costs of lithium-ion batteries. The figure shows that in four out of five cases, lithium-ion batteries were not economically attractive at projected minimum lithium-ion battery prices for 2050 (331 $/kWh) under the assumptions of this Thesis. Considering further use cases for electrochemical energy storages (e.g., operating reserve), stationary lithium-ion batteries might already become economically feasible at capital costs greater than 300 $/kWh. However, Figure 4.18 also shows that the storage capacity at very optimistic prices of 100 $/kWh would still be lower than 20% of all installed storages, in particular thermal energy storages. Therefore, this study concluded that lithium-ion batteries play a minor role in storage applications that only focus on aspects of energy (e.g., peak shaving and load shifting).
Finally, for the Madrid airport energy system, the sensitivity of the maximum PV capacity constraint was investigated. The economic dispatches for the months of July and December were shown in Figure 4.11 before. The PV capacity was systematically varied from 0 MW to 100 MW (discrete scenarios indicated by vertical lines in Figure 4.19). Note that the electric peak load was 21.5 MW (excluding electric loads from the compression chillers or other equipment). Figure 4.19 (a) shows that the minimum total expenditures were achieved at a PV capacity of 20 MW; so at approximately peak load capacity. Up to 20 MW, the increase in capital expenditures (CAPEX) were compensated by savings in operating expenditures (OPEX). Exceeding 20 MW, the power generation from PV became so large in some instances in time that they could not be handled economically anymore (e.g., electricity was sold at the wholesale market at rather low prices). With increasing PV capacity, the capacity of the internal combustion engine CHP plant and the gas boiler could only be slightly reduced (see Figure 4.19 (b)). Remarkably,
22 The discrete scenarios are indicated by markers and connected by a line only for better visualization of the individual cases.
for this particular case, the capacity of the hot water storage (HWS) was not increased with increasing PV capacity.
Figure 4.19: Evaluation of the PV capacity for the Madrid airport energy system: (a) Total expenditures, (b) Optimal converter and storage capacities.
The sensitivity analysis in this subsection outlined the influence of commodity price changes on the design of the energy system. Depending on the boundary conditions, the design of the energy system could be optimized in a way to achieve minimum total expenditures. However, in an actual application, the future pricing trends should be carefully investigated to achieve minimum total expenditures over the entire lifetime of the energy system. The ESD method could be extended for enabling a multiple year analysis with investment decisions in different years. Unfortunately, this would also increase the computational effort tremendously. A combination of both a simple multiple year analysis (with, e.g., time steps over an entire year) and the detailed ESD method for a single year introduced in this Thesis could fix this problem.
This subsection showed that lithium-ion batteries were not economically feasible for the Madrid airport at capital costs predicted for the year 2050 (300 €/k h or approximately 331 $/kWh), when not taking any further use cases (such as operating reserve) for lithium-ion batteries into consideration. Finally, this Thesis also showed that a certain maximum PV capacity in terms of economical feasibility existed.